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University of Technology, Sydney
Faculty of Engineering and Information Technology
Extending the LTE-Sim for LTE-Advance with CoMP and Relaying in Heterogeneous 4G
Mobile Networks
Haider Al Kim 11569249
Supervisor: Associate Professor Kumbesan Sandrasegaran
The work contained in this report, other than that specifically attributed to another
source, is that of the author(s). It is recognised that, should this declaration be found to
be false, disciplinary action could be taken and the assignments of all students involved
will be given zero marks.
Signed:
Date: 21/11/2014
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Acknowledgement
First of all, I would like to express my warm thanks to Imam Sahib Al Zaman
(as) who is always a beacon shining on my way to success.
This master thesis project is the final stage in obtaining the master degree in
telecommunication networks at the University of Technology Sydney (UTS). This
project was conducted in the Centre for Real-Time Information Networks (CRIN) in the
faculty of engineering and information technology in the UTS. I have been working in
this project from March 2014 to November 2014. During this project I have had much
support from several people. I would like to express my honest gratitude below.
Associate Professor Kumbesan Sandrasegaran has been my supervisor for this project.
He was been a great support providing guidance, advice, constructive criticism and
encouragement over the course of the last year. In addition, I am deeply and forever
indebted to my parents. My sincere appreciation and gratitude to them is for their efforts
and their distinctive role in all fields of my life, besides their faith in me and allowing
me to be as ambitious as I wanted. Your prayer for me was what sustained me thus far.
Importantly, my grateful thanks are extended to my wife, Ruwaida. Her support,
encouragement, quiet patience and unwavering love were undeniably the bedrock upon
which the past five years of my life have been built. Warm thanks for my brothers and
sisters for their unwavering supports.
Finally, for all of these people who motivated me to do the best and were
confident that I will be the best, I offer this modest gift to express thanks.
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Acknowledgement....................................................................................................................... i
Contents ..................................................................................................................................... ii
List of Figures ........................................................................................................................... iv
List of Tables.............................................................................................................................. v
Abbreviation List ...................................................................................................................... vi
Abstract ...................................................................................................................................... x
1. Chapter 1: Introduction ...................................................................................................... 1
1.1. Background 1
1.2. Motivation and goal of the project ...................................................................................... 3
1.2.1. Motivation ........................................................................................................................ 3
1.2.2. Thesis objective ................................................................................................................ 3
1.2.3. Thesis Scope .................................................................................................................... 3
2. Chapter 2: LTE-A ............................................................................................................... 4
2.1. Introduction 4
2.2. LTE- Advance Enhancements............................................................................................. 5
2.2.1. Air Interface Enhancement .............................................................................................. 5
2.2.1.1. Channel Bandwidth Structure ....................................................................................... 5
2.2.1.2. Carrier Aggregation ...................................................................................................... 6
2.2.1.3. Effective and Guard bands ............................................................................................ 9
2.2.2. Improving spectral efficiency ........................................................................................ 10
2.2.2.1. Heterogeneous Network (HetNets) ............................................................................. 11
2.2.2.2. HetNets Challenges ..................................................................................................... 14
2.2.2.3. Higher Spectrum Utilization. ...................................................................................... 15
2.2.3. Signaling Optimizations ................................................................................................. 15
2.2.3.1. Frequency Domain ICIC: ............................................................................................ 15
2.2.3.2. Time Domain ICIC ..................................................................................................... 16
2.2.4. Network Based Techniques............................................................................................ 19
2.2.4.1. Advanced MIMO Scheme .......................................................................................... 19
2.2.4.2. Transmission/Reception Coordinated Multi-Point ..................................................... 21
2.2.4.3. Relays .......................................................................................................................... 24
2.3. Summary 32
3. Chapter 3: Radio Resource Management ...................................................................... 34
3.1. Introduction 34
3.2. RRM in both DL and UL .................................................................................................. 35
3.2.1. Connection Mobility Control (CMC)............................................................................. 35
3.2.1.1. Handover ..................................................................................................................... 36
3.2.1.2. Future Trends of Handover ......................................................................................... 40
3.2.1.3. Handover Phases in LTE-A ........................................................................................ 40
3.2.2. Admission Control ......................................................................................................... 47
3.2.3. Packet Scheduling (PS) .................................................................................................. 49
3.2.3.1. Downlink Packet Scheduling ...................................................................................... 51
3.2.3.2. Packet Scheduling Algorithms in Downlink Direction ............................................... 53
3.2.3.3. Uplink Packet Scheduling ........................................................................................... 57
3.2.4. Power Control (PC) ........................................................................................................ 58
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3.2.5. Balancing of Carrier Load .............................................................................................. 60
3.2.5.1. Carrier Load Balancing ............................................................................................... 60
3.2.6. Interference Management............................................................................................... 61
3.3. Summary 62
4. Chapter 4: LTE-Sim Heterogeneous Network Deployment .......................................... 65
4.1. Introduction 65
4.2. Downlink System Model of LTE ...................................................................................... 66
4.3. Packet Scheduling Algorithms .......................................................................................... 68
4.3.1. Proportional Fair (PF) Algorithm................................................................................... 68
4.3.2. Maximum Largest Weighted Delay First (MLWDF) Algorithm .................................. 69
4.3.3. Exponential/Proportional Fair (EXP/PF) Algorithm ..................................................... 70
4.4. Simulation.1- Single Macro Cell with two Pico Cells ...................................................... 70
4.4.1. Simulation.1 Environment ............................................................................................. 71
4.4.2. Simulation.1 Results ...................................................................................................... 74
4.4.2.1. Throughput .................................................................................................................. 74
4.4.2.2. Packet Loss Ratio (PLR) ............................................................................................. 75
4.4.2.3. Delay ........................................................................................................................... 76
4.4.2.4. Fairness Index ............................................................................................................. 77
4.5. Simulation.2-Single Macro Cell with two Pico Cells (Different Speed Comparison) ..... 78
4.5.1. Simulation.2 Environment ............................................................................................. 79
4.5.2. Simulation.2 Results ...................................................................................................... 79
4.5.2.1. Throughput .................................................................................................................. 79
4.5.2.2. Packet Loss Ratio (PLR) ............................................................................................. 80
4.5.2.3. Delay ........................................................................................................................... 81
4.5.2.4. Fairness Index ............................................................................................................. 81
4.6. Simulation.3- Single Macro Cell with Increasing Pico Cells ........................................... 82
4.6.1. Simulation.3 Environment ............................................................................................. 82
4.6.2. Simulation.3 Results ...................................................................................................... 84
4.6.2.1. Throughput .................................................................................................................. 84
4.6.2.2. Packet Loss Ratio (PLR) ............................................................................................. 86
4.6.2.3. Delay ........................................................................................................................... 88
4.6.2.4. Fairness Index ............................................................................................................. 90
4.7. Conclusion 91
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List of Figures
Figure 2.1 Evolution of LTE-Advance ..................................................................................... 4
Figure 2.2 Carrier Aggregation .................................................................................................. 7
Figure 2.3 LTE-A Protocols Stack ............................................................................................. 8
Figure 2.4 Aggregation Process ................................................................................................. 9
Figure 2.5 Effective and Guard Bands with Aggregation Calculations .................................. 10
Figure 2.6 Heterogeneous Network Example .......................................................................... 11
Figure 2.7 Driving Factors and enablers for small cell deployment ....................................... 12
Figure 2.8 Main Comparison between HetNets layers, MLC (Minimum Coupling Loss) .... 13
Figure 2.9 Small Cell Extension concepts Usage to Offload Macro Cell ................................ 14
Figure 2.10 CA-based ICIC in HetNets .................................................................................... 16
Figure 2.11 ABS concept to provide interference free in HetNets ........................................... 17
Figure 2.12 Flowchart indicate ABS information elements exchange over X2 ........................ 18
Figure 2.13 SU-MIMO and MU-MIMO .................................................................................... 19
Figure 2.14 Advanced MIMO .................................................................................................... 20
Figure 2.15 Coordinated Scheduling/Beamforming .................................................................. 21
Figure 2.16 Joint Processing [28]............................................................................................... 23
Figure 2.17 Uplink Coordinated Scheduling ............................................................................. 23
Figure 2.18 Relays Node (RN) architecture ............................................................................... 25
Figure 2.19 Relays Duplexing Schemes .................................................................................... 27
Figure 2.20 FDD/TDD relay system .......................................................................................... 28
Figure 2.21 A repeater protocol stack (layer 1 performing relaying) ........................................ 29
Figure 2.22 Layer 2 Protocol Stack (Decoding/Encoding) ........................................................ 30
Figure 2.24 Protocol stack of RN ............................................................................................... 31
Figure 2.23 Protocol stack (Layer 3).......................................................................................... 31
Figure 3.1 RRM functions and the mapping to the lower layers ............................................. 34
Figure 3.2 Principle of Macro Diversity Handover ................................................................. 37
Figure 3.3 Principle of Fast Base Station Switching Handover ............................................... 37
Figure 3.4 Hard Handover ....................................................................................................... 38
Figure 3.5 Multicarrier Handover ............................................................................................ 39
Figure 3.6 X2 Initiation Phase [34] .......................................................................................... 41
Figure 3.7 X2 based Handover –Preparation Phases ............................................................... 42
Figure 3.8 S1 based Handover – Preparation Phases ............................................................... 43
Figure 3.9 Handover Execution Phase ..................................................................................... 45
Figure 3.10 Handover Completion Phase-X1 based Handover ................................................. 46
Figure 3.11 Handover Completion Phase-S1 based Handover .................................................. 47
Figure 3.12 RRM Framework in LTE-A ................................................................................... 50
Figure 3.13 Interactions between HARQ, PS and LA ............................................................... 52
Figure 3.14 Frequency DPS Concept ........................................................................................ 52
Figure 3.15 Uplink RRM Functionalities inter-work with LA and PS ..................................... 58
Figure 3.16 eNB Classification for LTE Rel 8 and LTE-A Arrival UEs .................................. 60
Figure 4.1 An Example of HetNets .......................................................................................... 65
Figure 4.2 Downlink Packet Scheduler of the 3GPP LTE System .......................................... 68
Figure 4.3 Applied HetNets (Macro with 2 Picos) .................................................................. 72
Figure 4.4 Average System Throughput (Macro with 2 Picos) ............................................... 74
Figure 4.5 Average System Throughput (single Macro cell) ................................................... 75
Figure 4.6 PLR of Video Flows (single Macro cell) ................................................................ 75
Figure 4.7 PLR of Video Flows (Macro with 2 Picos) ............................................................ 76
Figure 4.8 Packet Delay of Video Flows (single Macro cell) .................................................. 77
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Figure 4.9 Packet Delay of Video Flows (Macro with 2 Picos) .............................................. 77
Figure 4.10 Fairness Index of Video Flows [15] ....................................................................... 78
Figure 4.11 Fairness Index of Video Flows Macro with 2 Picos ............................................... 78
Figure 4.12 Throughput of Video in Macro with 2 Picos ........................................................... 80
Figure 4.13 PLR of Video in Macro with 2 Picos (3 Km/h and 120 Km/h speed) ..................... 80
Figure 4.14 Delay of Video in Macro with 2 Picos (3 Km/h and 120 Km/h speed)................... 81
Figure 4.15 Fairness Index in Macro with 2 Picos (3 Km/h and 120 Km/h speed) .................... 82
Figure 4. 16 Applied HetNets (Macro with Multiple Picos Scenarios) ...................................... 83
Figure 4.17 Throughput Gain of Video traffic in Macro with 2-10 Picos Scenarios .................. 85
Figure 4.18 Throughput Gain of Video traffic in Macro with 2-10 Picos Scenarios .................. 86
Figure 4.19 PLR Video traffic Comparison in Macro with 2-10 Picos Scenarios ...................... 87
Figure 4.20 PLR of Video traffic in Macro with 2-10 Picos Scenarios ...................................... 87
Figure 4.21 Delay of Video traffic Comparison in Macro with 2-10 Picos Scenarios ............... 89
Figure 4.22 Comparison Delay of Video traffic in Macro with 2-10 Picos Scenarios ............... 89
Figure 4.23 Fairness Index in Macro with 2-10 Picos Scenarios ................................................ 90
Figure 4.24 Fairness Index in Macro with 2-10 Picos Scenarios ................................................ 91
List of Tables
Table 2.1 LTE-A agreed requirements.......................................................................................... 5
Table 2.2 Carrier Aggregation Models ......................................................................................... 7
Table 3.1 QCI Parameters for EPS Bearer QoS Profile .............................................................. 48
Table 4.1 Mapping between instantaneous downlink SNR and data rate ................................... 67
Table 4.2 LTE System Simulation Parameters ........................................................................... 73
Table 4.3 Pico Cells Positions in meters into the Macro Cell (Radius 1 Km) ............................ 83
Table 4.4 Throughput Gain Values and An Average of The Values .......................................... 85
Table 4.5 PF Throughput Gain Values and An Average of The Values..................................... 88
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Abbreviation List
1G First Generation
2G Second Generation
3G Third Generation
4G Fourth Generation
3GPP Third Generation Partnership Project
3GPP2 Third Generation Partnership Project 2
AC Admission Control
ACK Acknowledgement
AMBR Aggregate Maximum Bit Rate
AMC Adaptive Modulation and Coding
APFS Advanced Proportional Fair Scheduler
ARP Allocation Retention Priority
ARQ Automatic Repeat Request
AS Access Stratum
ATB Adaptive Transmission Bandwidth
BM-SC Broadcast Multicast Service Centre
BS Base Station
CA Carrier Aggregation
CC Carrier Component
CCCH Common Control Channel
CDMA Code Division Multiple Access
CN Core Network
CoMP Cooperative Multipoint Transmission and Reception
CP Cyclic Prefix
CQI Channel Quality Indicator
CRC Cyclic Redundancy Check
CRS Cell specific Reference Signal
CS/CB Coordinated Scheduling/Beamforming
CSI Channel State Information
CSI-RS Channel State Information Reference Signal
DCCH Dedicated Control Channel
DFT Discrete Fourier Transform
DL Downlink
DM-RS Demodulation Reference signal
DRA Dynamic Resource Allocation
DTCH Dedicated Traffic Channel
DwPTS Downlink Pilot Time Slot
EDGE Enhanced Data Rates for GSM Evolution
EHR Efficient HARQ Retransmission
eNB Evolved Node Base station
EPC Evolved Packet Core
EPF Enhanced Proportional Fair
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EPS Evolved Packet System
E-UTRAN Evolved UMTS Terrestrial Radio Access Network
EV-DO Evolved Data Only
EV-DV Evolved Data Voice
FBSS Fast Base Station Switching
FDD Frequency Division Duplex
FDMA Frequency Division Multiple Access
FDPS Frequency Domain Packet Scheduling
FFR Fractional Frequency Reuse
FFT Fast Fourier Transform
FRF Frequency Reuse Factor
FSHO Fractional Soft Handover
GBR Guaranteed Bit Rate
GP Guard Period
GPRS Generalized Packet Radio System
GSM Global System for Mobile communication
HARQ Hybrid Automatic Repeat Request
HAS HARQ Aware Scheduling
HHO Hard Handover
HOL Head-Of-Line
HSDPA High Speed Downlink Packet Access
HSS Home Subscriber Service
ICI Inter Cell Interference
ICIC Inter cell Interference Coordination
IDFT Inverse Discrete Fourier Transform
IFFT Inverse Fast Fourier Transform
IMT 2000 International Mobile telecommunication 2000
IS 95 Interim Standard 95
IMT-Advanced International Mobile Telecommunication Advanced
ITU-R International Telecommunication Union
Radio-communication
JP Joint Processing
LA Link Adaptation
LTE Long Term Evolution
LTE-A Long Term Evolution Advanced
MAC Medium Access Control
MBMS Multimedia Broadcast Multicast Channel
MBMSGW MBMS Gateway
MBR Maximum Bit Rate
MBSFN Multimedia Single Frequency Network
MCCH Multicast Control Channel
MCE Multi-cell/Multicast Coordination Entity
MDHO Macro Diversity Handover
MH Mobile Hashing
viii
MIMO Multiple Input Multiple Output
MISO Multiple Input Single Output
M-LWDF Modified-Largest Weighted Delay First
MME Mobility Management Entity
MTCH Multicast Traffic Channel
MU-MIMO Multi User Multiple Input Multiple Output
NACK Negative Acknowledgement
NAS Non Access Stratum
OFDM Orthogonal Frequency Division Multiplexing
OFDMA Orthogonal Frequency Division Multiple Access
OLLA Outer Loop Link Adaptation
PARP Peak-to-Average Power Ratio
PBCH Physical Broadcast Channel
PC Power Control
PCCH Paging Control Channel
PCFICH Physical Control Format Indicator Channel
PCRF Policy Charging Rule Function
PDCCH Physical Downlink Control Channel
PDCP Packet Data Convergence Protocol
PDSCH Physical Downlink Shared Channel
PF Proportional Fair
PFS Proportional Fair Scheduling
P-GW Packet Data Network Gateway
PHICH Physical HARQ Indicator Channel
PHY Physical Layer
PMCH Physical Multicast Channel
PMI Precoding Matrix Indicator
PRACH Physical Random Access Channel
PRB Physical Resource Block
PS Packet Scheduling
PSD Power Spectral Density
PUCCH Physical Uplink Control Channel
PUSCH Physical Uplink Shared Channel
QCI QoS Class Identifier
QoS Quality of Service
RAN Radio Access Network
RAPF Retransmission Aware Proportional Fair
RAS Retransmission Aware Scheduling
RB Resource Block
RE Resource Element
RLC Radio Link Control
RN Relay Node
ROHC Robust Header Compression
RR Round Robin
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RRM Radio Resource Management
RRU Radio Resource Unit
RSRP Reference Symbol Received Power
SAE System Architecture Evolution
SC-FDMA Single Carrier Frequency Division Multiple Access
SFR Soft Frequency Reuse
S-GW Serving Gateway
SIMO Single Input Multiple Output
SINR Signal to Interference plus Noise Ratio
SIR Signal to Interference Ratio
SISO Single Input Single Output
SHO Soft Handover
SRS Sounding Reference Signal
SSDT Site Selection Diversity Transmission
SSHO Semi Soft Handover
SU-MIMO Single User Multiple Input Multiple Output
TB Transmission Block
TDD Time Division Duplex
TDMA Time Division Multiple Access
TPC Transmit Power Control
TSN Time Sequence Number
TTI Transmission Time Interval
UE User Equipment
UL Uplink
UMTS Universal Mobile Telecommunication System
UpPTS Uplink Pilot Time Slot
WCDMA Wideband Code Division Multiple Access
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Abstract This report presents heterogeneous network (HetNets) in the Long Term Evolution
(LTE) to introduce Long Term Evolution-Advanced (LTE-A). The evolution in the next
generation of mobile network has been stated in this study using the Pico with Macro
HetNets. Such networks are under what is so-called 4G technology that meets users’
aspirations in terms of data rate and system accessibility. LTE and LTE-A provide high
speed access to the packet data rate; therefore, various devices such as notebook, IPods,
smart phones, laptops, and cameras currently could be connected to the internet to work
in their full features. Most recent networks depend on the functionality of enhanced
base station to perform the complex operations; thereby, rely on Radio Resource
Management (RRM) functionalities that is placed in enhanced Node B. RRM is
demonstrated focusing on its functions such as packet scheduling and handover
management. Taking the advantage of HetNets while utilizing of LTE-based operations
such as Carrier Aggregation (CA), Multi-in Multi-out antenna MIMO and Cooperation
Multipoint transmission and reception CoMP has been widely adopted by mobile
operators since the cost of HetNets (adding small cells) is considerably accepted. This
mixing of HetNets with LTE specific technologies improves spectral efficiency,
enhances the system coverage and capacity, as well as minimizes the overall cost of the
operating. More importantly, it is expected that it boosts the data rate to 1 Gbps in the
downlink direction and 500 Mbps in the uplink direction and supports a speed of
mobility up to 500 Km/h. The Third Generation Partnership Project (3GPP) target was
obtaining 100 Mbps high peak data rate in the downlink and 50 Mbps in the uplink
using the 20 MHz bandwidth of LTE system comparing with the previous systems. Due
to the limited available radio resources, RRM performs packet scheduling to allocate
resource fairly among instantaneous arrived users. The system performance is affected
by the packet schedulers that play an essential role in the resource allocations. This
study is based on three selected packet scheduling schemes that have been built in the
used simulation platform. Real Time algorithms such Maximum-Largest Weighted
Delay first (M-LWDF) algorithm and the exponential/proportional fair (EXP/PF) have
been implemented. The Non-Real Time algorithm that is used is Proportional Fair (PF).
The performance of these schemes is evaluated via the metric of the throughput, Packet
Loss Ratio PLR (also called Packet Error Rate), delay (latency) and fairness index.
1
1. Chapter 1: Introduction
1.1. Background
The mobile telecommunication systems have been developed since 1980s. The first generation 1
G started the domination on the mobile market using the analogue scheme besides Frequency
Division Multiple Access (FDMA) technology. The features of 1G involve consuming of high
power and using narrow frequency bands; therefore, 1G was ineffective system. The second
generation 2G came to overcome the drawbacks of 1G; as a result to the revolution in the
digitized cellular networks. For example, Interim Standard 95 (IS-95) and Global System for
Mobile communication (GSM) are second generation mobile schemes. Qualcomm, an American
company, designed IS-95 as a mobile technology in USA. IS-95 was built based on the technique
of Code Division Multiple Access (CDMA) to support maximum bit rate 14.4 Kbps. In the early
1987, Europe initially proposed GSM to provide roaming service. Later, since the use of
harmonized spectrum, the international roaming can be applied throughout the globe and hence
GSM is accepted by various countries. It allows to the subscribers to be served from most of the
places on the plant that operate GSM using the same mobile number. GSM was based on circuit-
switched network for voice call only, but later the data services are added to the system. The
technology that was utilized by GSM was Time Division Multiple Access (TDMA) and the
maximum bit rate that could be reached with GSM was 9.6 Kbps.
While the revolution was continuing in the wireless networks, more enhancements for both IS-95
and GSM were introduced. These developments emerged to support more bit rate and utilize of
the available spectrums efficiently. IS-95B was the enhanced IS-95 to while Generalized Packet
Radio System (GPRS) are included in GSM to support data services since the GSM as
aforementioned was developed initially to voice service. Further improvements to GSM system
were done to introduce what is well-known as Enhanced Data Rates for Global Evolution
(EDGE). IS-95, GPRS and EDGE are under the 2.5G.
In the late of 1990s, Third Generation Partnership Project (3GPP) which is a united group of
telecommunications standard organizations defined the third generation (3G). The 3G was based
on the Wideband CDMA (WCDMA) technology that provides 5 MHz wideband of CDMA
besides supporting a frequency reuse operation of 1. Another feature of WCDMA was the data
rates integration on a single carrier using the flexible physical layer. In theory, the data rate of
2
WCDMA should be 2 Mbps. On the other hand, Third-Generation Partnership Project 2 (3GPP2)
standardized mobile technologies in USA; thereby, cdma2000 was the evolved IS-95B. Video on
demand, video conferencing and mobile TV are real-time applications that use 3G networks [1].
3GPP and 3GPP2 launched High-Speed Downlink Packet Access (HSDPA) and cdma2000 1×
Evolved Data Only (1×EV-DO) respectively in beginning of 2000. These technologies are
classified under 3.5G, which contain new enhancement methods for the mobile network such as
Hybrid Automatic Repeat Request (HARQ), distributed architecture, scheduling operation and
modulation and coding schemes (MCS) [2]. Six years later, IEEE released the Worldwide
Interoperability for Microwave Access (WiMAX) that was standardized as IEEE 802.16e.
WiMAX competed HSDPA and EV-DO technologies offering high data rate and better spectral
efficiency. It relied on Orthogonal Frequency Division Multiplexing (OFDM) as its access
technology.
The Long Term Evolution (LTE) of the Universal Mobile Telecommunication System (UMTS)
has been developed as a consequence of the demand for a competitive technology in order to
satisfy users’ experiences. The main goals of LTE system are enhancing the performance,
increasing capacity and coverage and reducing delay time and deployment cost while
maintaining the simplicity of the network. Using 20 MHz of bandwidth, LTE was planned to
support maximum bit rate of 100 Mbps /50 Mbps in the downlink /uplink respectively.
Moreover, the latency of the user plane was decided to be reduced to less than 5 ms while the
delay of the control plane was aimed to be less than100 ms. 350 Km/h was proposed as the speed
of mobility for LTE users and 100 Km as a coverage area for LTE network. 3GPP website
(www.3gpp.org) has the full LTE requirements and features for detailed information.
More recently, the advanced LTE, also called Release 10, have taken the attention of the network
operators. LTE-A is an enhanced system of LTE that is anticipated to surpass LTE. The planned
features of LTE-A are mainly introducing higher bit rate (up to 1 Gbps in the downlink and 500
Mbps in the uplink) and attaining higher speed of mobility (500 Km/h). Rel 10 (LTE-A) has
adopted number of new technologies in order to achieve that. These technologies involve:
heterogeneous networks (Macro with Pico, Femto and relaying), Carrier Aggregation (CA),
CoMP and advanced MIMO scheme.
3
1.2. Motivation and goal of the project
1.2.1. Motivation
The encouragement to do this project arises from the demand to investigate the performance of
LTE-A which is expected to dominate the future mobile networks. More users will be switched
to LTE and LTE-A as predicted 80% of mobile broadband users in the near future.
Due to the fact that the operation cost should be minimized and the utilization of the available
radio resources should be as efficient as possible, Radio Resource Management (RRM) is
considered the key tool that has to be focused on to be improved. It has the functions that can be
configured to improve the current telecommunication networks. The trade-off between deploying
RRM functionalities is the main goal of investigating these mechanisms in order to obtain more
reliable system, higher throughput besides lower transmission delay. Since applying
heterogeneous networks is cost effective method to improve the LTE, the focus is on HetNets.
1.2.2. Thesis objective
This study has mixed between investigating the current LTE system performance and
introducing the LTE-A by deploying heterogeneous networks. The first purpose has been
achieved by investigating one of the main RRM functions that is packet scheduling in the
downlink direction. The well-known scheduling algorithms; Proportional Fair (PF) algorithm,
Maximum Largest Weighted Delay First (MLWDF) algorithm and Exponential Proportional Fair
(EXP/PF) algorithm, have been used. An open source simulation platform called LTE-Sim has
been utilized that includes these algorithms. The second purpose is to develop a new code within
LTE-Sim platform that could be considered an extending to the current LTE-Sim to create LTE-
A environment in order to investigate LTE-A system performance. This integrated code is a
scenario of HetNets (Macro with Pico cells) using the aforementioned scheduling schemes. The
system using these algorithms is examined based on the metrics of Packet throughput, Packet
Error Rate, packet latency (delay), and fairness index.
1.2.3. Thesis Scope The thesis is organized as follows. Chapter 1 gives a historical overview and then states the
motivation and the objectives. Chapter 2 focuses on the HetNets and LTE-A besides LTE
technologies in general. Chapter 3 explores the main functions of RRM in both LTE and LTE-A
focusing on handover and packet scheduling. Chapter 4 is the technical papers of this thesis and
in the end a proposal for a doctoral study are included.
4
2. Chapter 2: LTE-A
2.1. Introduction
Long Term Evolution (LTE) was evolved to ensure that its technology satisfy the International
Telecommunication Union Recommendation requirements by using International Mobile
Telecommunication 2000 project (IMT-2000) of the ITU-R. This development ensures that the
LTE remains competitive for predictable future needs. LTE Rel-8 requirements are enhancing
system coverage and capacity, improving user experience by providing higher data rate and
lower latency. Moreover, decreasing cost of operation and deployment and seamless backward
compatibility are other LTE demands. LTE has to meet with the IMT-advanced, therefore;
further improvements were conducted in 2008. These improvements involve: firstly, data rate
increment from 100 Mbps up to 1 Gbps in downlink (DL) direction and from 75 Mbps up to 500
Mbps in the uplink (UL) direction. Secondly, spectral efficiency increment utilizing 8×8 antenna
layout in the DL direction to get 30 bps/Hz and using 4×4 antenna layout in the UL direction to
get 15 bps/Hz. Thirdly, declining latency of control plane in changeover from camped and
dormant to active state to be 50 ms and 10 ms respectively [11].Summarized Table 2.1 shows the
LTE-A required requirements. Several advancements have been proposed in order to reach these
demands in the network deployment and system performance, thereby, introducing the LTE-A
network. These improvements are involving carrier aggregation, advanced MIMO including
beamforming with spatial multiplexing enhancement in the UL/DL directions, relay nodes
deployment and transmission/reception cooperation multipoint CoMP. In this chapter, these
technologies are discussed. Figure.2.1 shows LTE-A development and number of technologies
and applications applied in release 8, 9 and 10 of LTE.
Figure 2.1 Evolution of LTE-Advance [11]
5
Items Requirements
Maximum data rate 10 Gbps – Downlink direction
500 Mbps – Uplink direction
Maximum spectral efficiency 30 bps/Hz (MIMO 8x8 ) – Downlink direction
15 bps/Hz (MIMO 4x4 ) – Uplink direction User spectral efficiency in Cell-edge 0.12 bps/Hz (MIMO 4x4 ) – Downlink
direction
0.07 bps/Hz (MIMO 2x4 ) – Uplink direction
User spectral efficiency in Average Cell 3.7 bps/Hz (MIMO 4x4 ) – Downlink direction
2 bps/Hz (MIMO 2x4 ) – Uplink direction
Latency of Control Plane 50 ms (Camped Active state)
10 ms (Dormant Active state) Latency of User Plane Lower than Rel 8
Table 2.1 LTE-A agreed requirements [2]
2.2. LTE- Advance Enhancements
It could be classified the main enhancements of LTE-A compare with LTE as the following
aspects:
2.2.1. Air Interface Enhancement
2.2.1.1. Channel Bandwidth Structure
In LTE Rel8/9, the total bandwidth is (20 MHz) represents one carrier component (CC). In LTE-
A using the heterogeneous networks where cells are overlapped, carrier aggregation can be
applied. It allows to multiple small bandwidth segments called carrier components to create
wider virtual frequency band in order to transmit at higher rates. The standard number of
aggregated CCs to represent 100 MHz of LTE-A bandwidth is five component carriers. This is
used to achieve 1 Gbps/500 Mbps in DL/UL directions. On the other hand, it offers backward
compatibility to LTE users, in which the LTE users can only use one component carrier (20
MHz) while the LTE-A users utilize up to 5 components carrier to achieve LTE-A users
6
requirements . However, no all the bands are available to be allocated to LTE-A users. This is
because the CC has two parts: effective band and guard band. The effective part consists of the
physical radio blocks (PRB) which is the efficient part of the band that can be allocated to the
subscribers [30].
2.2.1.2. Carrier Aggregation
In LTE-A (Release 10), carrier aggregation (CA) has been introduced for providing bandwidth
extension up to 100 MHz by aggregating multiple 20 MHz carrier components (CCs). It
maintains a compatibility with LTE releases 8 and 9 while increasing the required bandwidth to
meet LTE-A requirements. This increment in the bandwidth will increase the data rate in LTE-A
significantly to provide a peak up to1 Gbps (downlink) and 500 Mbps (uplink). Each CCs has
two parts: effective band and gap band. Effective bandwidth is equal to the total contiguous
physical radio block (PRB) times the total bandwidth subtracting the gab band (GP) [30].
Equation 1.1 illiterates the effective bandwidth that used in CA of each CC.
Effective BW = (1- GB%) x PRB [30] (2.1)
In general, CA could be classified into three sorts un the term of the mechanism in which
frequencies of CCs are companied as shown in Figure.2.2 [11]:
Intra-band aggregation, contiguous component carriers: duplexing mode is FDD or TDD.
While FDD allows asymmetric CA to get larger bandwidth in DL than UL, TDD
provides symmetric CA since the same carriers has been used in DL and UL. However, it
is possible to TDD to provide asymmetric CA using various time splits in downlink and
uplink [2].
Intra-band aggregation, non-contiguous component carriers: FDD or TDD is the
duplexing mode.
Inter-band aggregation, non-contiguous component carriers of different frequency band
(multi-band). The duplexing mode is FDD or TDD. Table 2.2 provides more details about
all possible scenarios.
7
Figure 2.2 Carrier Aggregation [29]
In the advanced LTE, 3GPP differentiated four implemented models for carrier aggregation, as
illustrated in Table 2.2 [29]. These models comprise both non-contiguous multiple frequency
bands CA using FDD and TDD modes and contiguous single frequency bands using FDD and
TDD modes.
Models Carrier Aggregation Deployment model
A Uplink: 3.5 GHz - 2x20 MHz
Downlink: 3.5 GHz - 4x20 MHz
FDD contiguous allocation: single band (Uplink: 40
MHz, Downlink 80 MHz)
B Uplink: 2.3 GHz - 5x20 MHz
TDD contiguous allocation: single band (100 MHz)
C FDD non-contiguous allocation: multi band for (Uplink:
30 MHz, Downlink: 30 MHz)
D TDD non-contiguous allocation: multi band (90 MHz)
Table 2.2 Carrier Aggregation Models [20]
8
There is another group of spectrum bands provided by 3GPP in addition to aforementioned LTE-
A carrier aggregation spectrums; these spectrums are [20]:
The 3.4 – 3.8 GHz bands
The 3,4 – 3.6 GHZ and 3.6 – 4.2 GHz bands
The 450 – 470 MHz bands
The 698 – 862 MHz bands
The 790 – 862 MHz bands
The 2.3 – 2.4 GHz bands
The 4.4 – 4.99 GHz bands
There is a similarity between LTE Rel-8 and LTE-A protocol architecture, the LTE Rel-8
control plane architecture is applied to CA of LTE-A. However, in the user plane; the LTE-A has
a difference in which PDCP and RLC layers cannot see CCs operation. On the other hand,
HARQ of each CC in the MAC layer handle to the physical layer in the DL direction or from the
physical layer in the UL direction. Figure.2.3 shows protocols stack for LTE-A [20].
Figure 2.3 LTE-A Protocols Stack [20]
9
2.2.1.3. Effective and Guard bands
There are different algorithms to aggregate the carrier components in the intra-band and the more
complicated algorithms that applied in the inter-band. The procedure that responsible for
allocation component uses the “Effective” bands to be allocated to the LTE-A users. The
Effective bands are the actual affordable bands that can be used to be allocated to the requested
user in LTE-A. This leaves a gap to separate between these effective bands, which is called
Guard band. Guard bands are mainly used to avoid Doppler Effect for high mobility users. While
the orthogonality is used to avoid the interference between carrier components, this Doppler
Effect causes non-negligible impact on the orthogonality between frequency bands in LTE. As
mentioned before, there are actual bands that can be allocated which mean that it cannot allocate
all available bands. The following equation is used to calculate the total available bandwidth
(resource) to be allocated the LTE-A users. Guard band (GB) and PRB is Physical Resource
Blocks (consisted of subcarriers, the smallest elements that used to carry user data)
Effective Bands = (1- GB%) x PRB bandwidth.
To generalize the allocation procedure, the following diagrams shows that
Figure 2.4 Aggregation Process
10
In LTE, CA has supported only 5 CC each one with 20 MHz. Not all the bandwidth of 20 MHz
is available to be aggregated due to the gap band (Guard band). Hence, the total band that is used
to be allocated to LTE or LTE-A users can be calculated. The following Figure.2.5 illustrates the
concept of effective band, the guard band and the aggregation process. is the channel
bandwidth, is the subcarrier bandwidth,
is the contiguous subcarriers and is the total
percentage of guard band (GB) [30].
Figure 2.5 Effective and Guard Bands with Aggregation Calculations [30]
2.2.2. Improving spectral efficiency
Among different base stations, the same carrier frequency (co-channel deployment) is shared. In
addition, support of localized high traffic-densities (‘hot-spots’) and deliver an increase in
capacity simultaneously. The main improvement is using the Heterogeneous Network (HetNets).
11
2.2.2.1. Heterogeneous Network (HetNets)
The motivation factor for HetNets is that there are considerable technological and economic
causes for the rapid deployment of heterogeneous networks. The results of this technological
enhancement are expected to have profound effects on the future telecommunication. Normally,
any mobile operator installs new base stations to cope the increasing of traffic demand, choosing
the transmission power and antenna configuration in order to complement the existing cells. This
combination of large and small cells will lead to co-exist various Radio Access Technologies
(RATs). Generally, HetNets can be defined as a mix of macro cells ,low power cells such as
(Femto cells ,Pico cells, and relays), and remote radio heads (RRH) with multiple RATs
(Figure.2.6) , to bring the network closer to the end users and increase the user expectation. The
main reason behind adaptation of HetNets in the recent telecommunication (LTE-A) is that the
radio link performance, theoretically, has been reached its limitations. Hence, logically the next
performance jump must come from the diversity of wireless technologies. The main driving
factors to use small cells in turn create HetNets are illustrated in Figure.2.7.However, one of the
main challenges of applying HetNets is the intra-frequency interference [34]. One the other hand,
the measurement that is used to differentiate between base station classes (how close the user to
the base station) is Minimum Cabling Loss (MCL). If it is more that 70 dB, the base station type
is a wide range (macro cell over 300 meters coverage). When it is 53 dB, it is medium range base
station (micro cell, 100-300 meters coverage). For local area ones, the MCL is 45 dB which
means that the user is very close to the base station ( Femto or Pico cells, less than 50 meters
coverage) [34].
Figure 2.6 Heterogeneous Network Example
12
Mainly, there are five types (layers) of cells which can construct HetNets. The below explains
each sort:
A- Macro cell: it has a wide antenna to provide coverage for several square kilometers,
utilizing high power transmission and high mounted antennas [34].
B- Micro cell: it is outdoor antennas that are smaller than macro cells. It covers only a few
hundreds of meters by using low antennas deployments [34].
C- Pico cell: is a class of small cells, could be referred to as an enterprise femto cell or
metro femto cell (more details of femto in D). It reuses all available radio resource (it is
called Co-channel deployment) that is used by larger cells (macrocellular network) to
serve as an expansion of a macro cell [34]. Compare to the other class of small cells
(femto), this class usually has more subscribers. Moreover, it provides data and voice
services in larger promises than femto such as indoor in place coverage, for example,
shopping center or outdoor hotspot coverage for instant a busy shopping street. Pico cells
are designed to be environmentally hardened to be deployed outdoor, perfectly installed
with enhanced antennas. Unlike femto cells that are specified to be used by only the
members of the closed subscribers group, pico cells can be used by all qualified users.
However, it has been noted that there may not a huge different between femto and pico
with regard to the number of users and transmission power [36].
Figure 2.7 Driving Factors and enablers for small cell deployment [34]
13
D- Femto Cell: is the other class of small cells, and it is used as indoor cell only. The indoor
solutions can be placed in any building, shopping center, office or even at home, and it is
connected to macro cell base station using indoor antennas and RF cables [34]. It could
be defined that the Femto cell is a small cell that has Home evolved Node B (HeNB) in
order to provide UEs with the connections to a mobile operator’s network, for instance,
domestic IP broadband connections. It has low power capability; hence, the coverage of
HeNB is small, thus, the cell size is small. Low power femto cells can be interpreted to
lower cost equipments. This means motivation of scalability ubiquitous utilization. It is
considered, from the operator point of view due to the cost-efficient, the means of
capacity development and coverage expansion. The first standard-base Femto cell release
was enabled in Rel 8 that can be deployed in any vendor due to a number of agreed 3GPP
specifications. From the user viewpoint, there is no Femto since the operators provide a
high level of connectivity and services. It offers better connection to the mobile network.
On the other hand, it is used to offload the Macro cell providing enhanced service to the
mobile terminal [33]. The main reason behind using Femto cells is that it improves the
coverage and capacity in small promises such as home or small office [34]. Figure.2.8
shows a general comparison between the four main heterogeneous networks layers.
E- Relay: a network repeater that less cost than deploying new cell (more details in relay
section in this chapter later).
Figure 2.8 Main Comparison between HetNets layers, MLC (Minimum Coupling Loss) [34]
14
2.2.2.2. HetNets Challenges
While adoption heterogeneous network in the modern telecommunications networks has a
significant impact of future network utilization and satisfies users’ expectations, there are
considerable challenges encounter deploying it. Power disparity issue between large cells
(macro) and small cells (pico and femto) is one of the main problems. This comes through
different coverage area of macro cells and pico/femto cells. To solve this issue and to steer more
traffic toward small cells, range cell extension has been introduced which virtually increases the
size of a small cell. This can be done through the basic biasing; that means, the UE that receives
stronger signal from macro cells would be forced to connect to small cell nevertheless [34].It is
very effective and simple method to increase small cells offload. However, it should be noted
that using CRE should be with high care since it could be lead to problematic interferences
situations. Figure.2.9 illustrates the concept of range cell extension (CRE). The another obstacle
faces using HetNets is that the co-channel interference problems which means use same radio
resources by the operator for both small cells and large cells causing interference where the
macro cell receives interference from pico or femto cells and vies versa. The proposed solution
to solve the interference issue in LTE-A HetNets is that using what well known with enhanced
time domain inter-cell interference coordination (eICIC) with ABS (Almost Blank Subframes)
[32]. There is another type of (eICIC) based on carrier aggregation as elaborated in [35] which
called enhanced CA-based ICIC with cross carrier scheduling.
Figure 2.9 Small Cell Extension concepts Usage to Offload Macro Cell
15
2.2.2.3. Higher Spectrum Utilization.
Compare to LTE, the advanced LTE that is comprised from HetNets has higher spectrum
utilization. By companying multiple carrier components in LTE-A, so any effective PRB can be
aggregated to create the bandwidth (BW) for LTE-A subscribers. The other strategy to increase
the utilization of spectrum in LTE-A is that by using Statically Multiplexing (STM) method , in
which the user can utilize of any resource blocks as long as they are affordable to be assigned ,
then after finishing its transmission, it will release them. This means more efficient than static
allocation [30].
2.2.3. Signaling Optimizations
As it is mentioned before, there are two types of mechanisms to manage the problem of inter-cell
interference between HetNets proposed by 3GPP [36]. Carrier aggregation based ICIC
(frequency domain) and ABS (time domain ICIC) are these methods.
2.2.3.1. Frequency Domain ICIC
- Carrier Aggregation based ICIC: eNB can apply cross carrier scheduling if CA is
supported. It could be applicable when the eNB controls both the victim cell and the aggressor
cell. For example, the victim cell is the pico cell and the aggressor cell is the macro cell. In such
a scenario, eNB can use cross-carrier scheduling to avoid using PDCCHs on the same carrier
frequency. Details explanation of this scenario can be accessed in [36]. Figure.2.10 shows CA-
based ICIC of 2 separate component carriers, different network layers at a time are assigned the
primary component carrier (f1) and the second component carrier (f2). The f1 can be used by the
macro layer to schedule its control information. However, it can still schedule its users on both f1
and f2. In turn, the interference on control and data can be avoided by scheduling control and
data information for both macro and pico layers on different component carriers. As shown in the
third subframe in Figure.2.10, it is also possible to schedule data information of users in Pico
eNB on the same carrier that the Macro layer schedules its users, as the interference from the
aggressor cell (macro) on pico users can be tolerated. In contrast, pico UEs in the range
extension region are still scheduled in the other carrier where UEs of the macro are not
16
scheduled. One backward of CA with cross carrier scheduling is that only Rel 10 and onwards
users can be supported so this feature cannot be used by the old releases (8/9) [37].
Figure 2.10 CA-based ICIC in HetNets [37]
2.2.3.2. Time Domain ICIC
In this mechanism, the subframes are partitioned into two sets to be used by the HetNets layers ,
the victim cells use one set while the other set is used by the aggressor cells. Certain subframes
used by the aggressor cell have to be muted by avoiding scheduling on those subframes so the
victim cell can use these subframes to scheduling its UEs. The interfering cell avoids using the
traffic channel during these blanked subframes. However, it still sends some essential
information and signaling. This muted subframe is called almost blank subframe (ABS) that will
be explained in more details in the following section [36].
- Almost Blank Subframes (ABS)
Because the muted subframes are still carrying the signaling and other information, these empty
subframes are called “Almost Blank” Subframes [36].It is almost blank to offer backward
compatibility with Rel8/9. In other words, ABS are subframes with decreased transmission
power including no transmission on some physical channels in the downlink direction. It is a
form of blanking time; macro cell does not be allowed to transmit during it. ABS can be used by
the victim cell (small cell) allowing cell range extension (CRE) UEs to get high quality signal
and transmit with better conditions [32]. The UEs that suffer from a high level of interference
should be served during these blanked subframes. In contrast, the users who are nearer to the
transmitting eNB that have not been impacted by interference can be served during the normal
subframes (co-channeled subframes) [37]. Figure.2.11 shows ABS concept.
17
As mentioned before, the Almost Blank Subframes are designed to continue sending signaling
and information. These signals are:
- Cell Specific Reference Signal (CRS);
- Acquisition channels for such as paging and broadcast, i.e.
PSS/SSS/PBCH/SIB1/Paging/PRS [37].
The pico users have been classified to two sets in term of ABS:
1- Cell Range Extension UEs: the users who suffer from high level of interference caused by
macro eNB should be serviced during ABS where the interference at its minimum value [37].
2- Center Pico Cell UEs: the users who are closer to the center of pico cell are not highly
impacted by macro cell interference since they maintain a good channel quality from their
serving eNB. As a result, the center pico users can be served with any subframes during ABS
or non-ABS [37].
Figure 2.11 ABS concept to provide interference free in HetNets [37]
18
- ABS Information Elements Exchange
It is a number of ABS bits used to assist the interfered cell with its process of scheduling. The
victim eNB is informed by each bitmap of ABS about the aggressing cell intention of power
level. ABS bitmap can be divided into two types: aggressor cell bitmap and victim cell bitmap.
The former has two main bitmaps which they are:
A- ABS Pattern Info: represents ABS bit to aid interfered (pico) cell with its scheduling
decisions. It is the first bitmap of ABS used to indicate which subframes the interfering
(macro) cell has configured to be ABS [32].
B- Measurement Subset: it is obvious from its name that they are a set of subframes used for
measurements objectives by the UEs of the victim eNB [32].
The later has three main bitmaps which they are:
A- Invoke Indication IE: requesting the ABS pattern from the aggressor eNB.
B- Usable ABS Pattern Info IE: is it intended to inform the sending eNB the ABS subframes
that are utilized by the receiving node [32].
C- DL ABS Status IE: indicates the ABS resource utilization status at the victim eNB to the
aggressor eNB [32].Figure.2.12 below shows the ABS information elements exchange.
Figure 2.12 Flowchart indicate ABS information elements exchange over X2
19
2.2.4. Network Based Techniques
2.2.4.1. Advanced MIMO Scheme
LTE Rel-8 uses (4×4 SU-MIMO) in which four antennas to the same user are dedicated in the
downlink transmission and only one antenna in the uplink transmission. In Rel8 , there are also
four main various downlink transmission data modes: UE-specific RS-based beamforming,
Multi-user MIMO, Open/Close loop spatial multiplexing and Open–loop transmit diversity
which have the following mode numbers ( 7; 6; (3,4&5); 2) respectively. Essentially, two
streams of data for a single user (SU-MIMO) or two users get the same stream of data
simultaneously (MU-MIMO).Mainly is geared towards TDD using Dedicated Reference Signals
(DRS). Figure.2.13 shows the SU-MIMO and MU-MIMO.
Figure 2.13 SU-MIMO and MU-MIMO
20
In LTE-A, MIMO operations are enhanced using new Rel10; mode number (9), in downlink and
uplink transmission. Before mode 9, mode 8 used in Rel9 is introduced that is mainly geared
toward TDD because the spatial multiplexing at the base station is got hold of using the sounding
reference signal (SRS) [39]. In the downlink direction, spatial multiplexing is developed to
support 8×8 antenna configuration to improve the performance and obtain eight data stream. This
results in higher peak data rate in which double value is reached over Rel8. In addition, an
evolved reference signal is deployed to assist a number of beamforming schemes. In the uplink
direction, on the other hand, the baseline is 2×2 MIMO antenna design while 4×4 could be
applied to provide peak data rate and improve the performance at the cell edge [28]. Recently,
the concept of Massive MIMO has been proposed in LTE-A by means of 3.5 GHz. It is possible
to align the individual antenna elements very close to each other. This enables the use of several
tens or hundreds of antenna elements together. In Massive MIMO, beamforming is used with
narrow beams. This reduces the interference and improves signal quality at cell edge because
energy will be concentrated in a small area. However, MIMO has many problems that have to be
addressed before the use of it in operational networks [31]. Figure.2.14 shows the advanced
MIMO
Figure 2.14 Advanced MIMO: http://mttwireless.com/blog/lte-advanced-45g-technology-
description
21
2.2.4.2. Transmission/Reception Coordinated Multi-Point
Cooperative Multi-point or what so-called (CoMP) is a scheme for coordination among diverse
number of eNBs. These eNBs are geographically separated and are linked via high speed
dedicated connection elements, such as microwave links or fiber optics links. The purpose of
CoMP is to enhance the users and system performance in the cooperation region[28]. As X2 is
the interface that connecting the eNBs in LTE-A, it will be used for performing CoMP process.
While the number of coordinating eNBs increases, the performance is getting better. The inter-
cell interference effect in both the uplink and downlink directions is mitigated using an
affirmative technique of coordination between eNBs. In the downlink direction, coordinated
transmission among eNBs can be conducted in which two operations have been proposed:
Coordinated Scheduling/Beamforming (CS/CB) and Joint Processing (JP).However, in the
uplink direction, coordinated reception among eNBs can relieve the interference. The only
scheme that has been applied is coordinated scheduling in this direction, below is a description of
each approach:
Coordinated Scheduling/Beamforming (CS/CB). One eNB takes the responsibility to
transmit data to the users. However, a group of eNBs shares control information
specifically scheduling/beamforming decision as shown in Figure.2.15.
Figure 2.15 Coordinated Scheduling/Beamforming [28]
22
Joint Processing (JP). In this scheme, to remove interference and enhance received signal
strength, several coordinated transmitting nodes altogether transmit data to the served
UE. There are two ways to perform JP: fast cell selection and joint transmission. In the
fast cell selection approach, the data is transmitted by one of the eNBs at a time as shown
in the right side of Figure.2.16. In contrast, in the joint transmission approach eNBs
participate simultaneously to send data to the served terminal as shown in the left side of
Figure.2.16. However, it is considered a waste of resources since multiple eNBs serve a
single UE. This is because the signal power from some eNBs may be feeble.
In the JP operation, the coordinated base stations are served one UE to increase the
micro-diversity. The operation depends on the CSI. Ideally, if CSI is available to the base
station in its optimum value for all channels, cooperated antennas of all base stations can
create a mechanism look like traditional MIMO. This can help of decreasing, and
managing interference occurred between the UEs signals by using zero-forcing
beamforming or multi-user MIMO techniques (MU-MIMO) or MMSE. The aim of using
MU-MIMO is to get near-optimum performance. However, it is highly sensitive to the
CSI accuracy. Because JP relays on CSI feedbacks, any delay in X2 interface can outdate
CSI and lead to inefficient JP. On the other hand, any delay of CSI can be reduced by
exchanging CSI through the air. However, this results in increasing the overhead and
causes the difficulty to manage the interference that comes through these control
messages. acts as a single base station
In Comparison to JP, CS/CM, from its detention perspective, seems as a single base
station serves the UE. It is more effective because the other eNBs that are participating in
the operation require less CSI messages between them. While CS/CS depends on the
cooperated cells to avoid the interference, it ignores the received traffics from other eNBs
in the system considering them as pure interference. However, the diversity and
multiplexing gain in CS/CM is less than JP since the UE served by one base station only
[32].
23
Coordinated scheduling approach. Several geographically separated base stations
corporate together by receiving the transmitted signal from UEs to increase cell-edge user
throughput as shown in Figure.2.17.Compare with aforementioned approaches, this is
used in the uplink direction.
Figure 2.16 Joint Processing [28]
Figure 2.17 Uplink Coordinated Scheduling [28]
24
- CoMP s challenges
CoMP approaches encounter the following obstacles:
• Extensive Overhead: could be per aggregated feedback or point feedback. It is a trade-off
between overhead, delay and accuracy.
• Specific Reference signals of UE: UEs are unaware of the detailed operation in the network.
Hence, some sorts of reference signals still may be required.
• Capacity of X2 interface or backhaul: massive information messages are needed for CoMP
implementing depending on low-latency and high-bandwidth X 2 interfaces.
• Overload of the control channel: two main corporation types Joint Proportional and
Coordinated Scheduling/Beamforming. Joint operation leads to increasing the number of UEs
that their scheduling is conducted in the same subframe. Due to capacity of recent PDCCH, this
could restrict the performance of scheduling that is required with CS/CB and JP. [32].
2.2.4.3. Relays
Relaying in LTE-A is another technique that is used in order to reduce the update of existing
LTE system. The major consideration of designing the relay node is to expand the cell coverage
area of LTE network. The Relay Node is a cost –effective which is a cheap approach to
providing coverage for far regions where the quality is poor or no service [38]. In addition, high
data rate, throughput at the cell edge, temporary deployment of network and group mobility can
be achieved by implementing relays in LTE-A [22]. Figure.2.18 shows the basic relays
representation architecture in LTE-A. There are two main interfaces in relay system: Uu and Un.
Uu interface is used to communicate the UE with the Relay Node (RN). Unique in LTE relay
system, new interface known as Un is introduced which is used in connection between a donor
eNB and relay node.
25
Terminology of LTE Relay:
Relay Node (RN): repeater station.
RN Cell: the area (Cell) that is covered by Relay Node.
User Equipment (UE): term that is equivalent to MS (mobile station) in GSM system. It
represents the end user terminal in LTE system.
Donor eNB (DeNB): the base station in the LTE architecture is called evolved node B
(eNB). If eNB supports relay in LTE, it is called “Donor eNB”.
Donor eNB Cell is the cell in LTE in which the relay functionality is supported by the
base station (DeNB).
Uu is the interface in which the user equipment can access the radio network. In relay
scenario, it is a link between the relay node (RN) and the UE. In LTE relay system, it is
also known as access link.
Un is the connector between the RN and the DeNB. In LTE relay system, it is called
backhaul link.
Figure 2.18 Relays Node (RN) architecture [28]
26
The user terminal is unaware whether it is connected to RN or eNB. An RN, from the terminal
perspective, looks like a normal cell in LTE system. This is; the data transfer and the signaling
messages are the same with the case of non-relay cell. However, the security level in relays adds
new challenges for system design of the relays. This is because the relay is new intermediate part
of LTE network. Similar to LTE-A eNB, RNs in LTE-A are required to be compatible with LTE
UEs [38]. On the other hand, there are two frequency bands (inband and outband) utilized in the
connection between RN and eNB. If the frequency band used in the connection between UE and
eNB is the same that connect between RN and donor cell. This type is used to reduce the
complexity. In contrast, the outband means various frequency bands are used in the link between
RN & eNB and eNB & UE.
- Deployment Scenarios of Relay Node (RN)
There are various scenarios that have been defined since the relay is deemed better than a normal
eNB installation. The following summarizes the identified scenarios:
A- Extension of Coverage: at a cell edge, a relay (RN) can be deployed to be used as an
extension of the coverage for the eNB. A normal deployment of RN would be in the rural
regions at the cell edge where less population is present [36].
B- Reduction of dead spots: in a dead spot in which a coverage hole exists, a RN can be
implemented to overcome it. The main reason behind existence a coverage hole is the
physical obstruction, for example tunnel, building and so on so forth [36].
C- Enhancement of throughput: to boost the throughput in a particular are such as an
indoor area or a hot spot, a relay (RN) can be deployed [36].
D- Temporary Coverage: when special events such as sport games and music courts are
held, a relay node can be deployed to offer reliable services for the UEs in the hosting
area which normally would be crowded [36].
E- Group Mobility: it is possible to deploy relay node (RN) in transportation such as a
train, bus, and so on. Compare with other aforementioned cases, the relay node in this
case is subjected to the mobility [36].
27
- Duplexing Schemes
Either TDD or FDD can be used by RN to connect with the UE and eNB. Essentially, while
TDD is a half-duplex communication, FDD is a full duplex communication. The following are
the basic duplexing modes adopted to use spectrum resources in communications between
network elements of LTE-A (UE, RN and eNB):
In the DL transmission between DeNB to RN and RN to UE, a basic TDD relay happens
in 1 and 2 timeslots respectively. However, in the UL transmission, connection between
UE and DeNB through RN happens in the next timeslots (3 and 4) respectively. Figure.2.
19 (a) illustrates that.
Both in downlink and uplink directions, a basic FDD relay requires pair of frequency
bands along with two time’s slots as shown in Figure.2.19 (b).
UE, RN and DeNB are communicated in the UL and DL simultaneously utilizing various
orthogonal frequencies to avoid traditional inter-cell interference and interference
between relay links (backhaul and access).The inband relay system is considered, so the
same frequency is used in Un and Uu. Such system is so-called extended FDD relay and
shown in Figure.2.19 (c).
Figure 2.19 Relays Duplexing Schemes [28]
28
- Inband Relay
As aforementioned previously, there are two sorts of inband relay system: the FDD and TDD.
Due to the additional interference that relay suffers from which is due to the use of the same
frequency in access and backhaul, the relay is designed to have subframe with nonoverlapping
time zone. In the uplink and downlink, a pair of carriers is used with a time gap to separate
backhaul link and access link. UE is unaware about these guard times and should connect to RN
normally. The approach that is used to avoid the confusion and keep the backward compatibility
is MBMS (Multimedia Broadcast Multicast Service) configuration. In this method, the relay
system deludes the UE that the unused time zone as a useful MBSFN (Multicast Broadcast
Single Frequency Network) subframe. This subframe is mainly used to provide MBMS in LTE
[38].
In general, the mechanism used to connect the RN to the DeNB is adopted from the method that
a UE connects to the eNB. The same protocol stack with some modifications over the UE
protocol stack is used. To keep backward compatibility, RN operates as eNB to serve UE.
Hence, the physical layer channel design has no significant difference in relay system. However,
the backhaul link (Un) has modifications to meet the relay operations. New physical channels
have been developed to meet the requirement of relay operation in the backhaul side of the relay
network. Relay is similar to the conventional LTE physical signaling channel and data
transmission channels (in DL and UL).It has similar PDCCH (physical download control
channel) which is called R-PDCCH (relay physical download control channel), and
Figure 2.20 FDD/TDD relay system
29
PDSCH/PUSCH (physical downlink shared channel/ physical uplink shared channel) which
called R- PDSCH/R-PUSCH.
Relay can be categorized with regard to various characteristics. This classification can be
according to its functionality at each layer, duplexing types or according to the frequencies used
in communication in Un and Uu links [28].
- Layers
The classification of relay nodes can be conducted depending on which layers they work in.
A repeater or what so called a layer 1 RN is responsible for amplification the arrived
signal, then forwarding it to another network element which is another RN or a UE in the
telecommunication network of the heterogeneous network. It is normally as a repeater
amplifies any useful signal it receives as well as the undesirable signals such as noise and
interference. This fact implies that it is used only in an environment where a high SNR.
The layer 1 relay has a main advantage which is very fast method to forward the received
signal. That is, it could be interpreted as a small delay appeared as furthermore multipath
to the UE since no data passing over to the upper layers to be handled. It works in the
physical layer, in which a donor eNB RRC controls it [29, 36]. Figure.2.21 shows layer 1.
Figure 2.21 A repeater protocol stack (layer 1 performing relaying) [36]
30
Decoding and Forwarding Relay: a layer 2 (L2) relay. It is responsible for decoding and
re-encoding the arriving traffic before retransmitting it to the required UE. Unlike layer 1
relay node, it chooses only the desirable signal to amplify it. For this reason, it can be
applied in a low SNR situation. Although the processing time is increased slightly, the
layer 2 decoding and encoding process can override noise and interference. Since RLC
and MAC layers are below the layer 2 relay type, it performs the upper layer functions of
radio resource management such as data formatting, scheduling, and retransmission. As
layer 1, it has to be controlled by DeNB since there is no RRC in the RN [29, 36].
Figure.2.22 shows layer 2.
RRC layer: a layer 3 (L3) relay. The similarity between layer 3 and layer 2 is that the
noise and interference can be discarded by the processing of relay node L2. However, it
is unlike layer 2 since it is capable of performing full L3 functions. Moreover, it has its
own RRC together with layer 1 and layer 2 capabilities. Hence, it can control its cells
without the need to DeNB RRC with their PCIs apparently to the UEs as a conventional
eNB element. RRC layer RN can be deemed as a wireless eNB backhaul which is the
disadvantage of this layer. Obviously, more signaling overhead and high efficiency are
required in the wireless connection in this scenario, in turn, this increases the processing
delay [29, 36]. Figure.2.23 shows layer 3 RN.
Figure 2.22 Layer 2 Protocol Stack (Decoding/Encoding) [36]
31
- Radio Interface Protocol Stack of Relay Network
Figure 2.24 Protocol stack of RN
Figure 2.23 protocol stack (Layer 3) [36]
32
As in traditional LTE, two main interfaces connect the relay system components. They are X2
and S1. While X2 interface is used to connect the donor eNB (DeNB) to another eNB in the
network, S1 interface connects the far core network to the donor eNB. However, the relay system
use proxy term referring to donor eNB that used as a proxy for RN, more specifically, X1 Proxy
and S1 Proxy architecture are used [36].
2.3. Summary
To sum up, the first chapter discusses the detailed improvements on Rel-8 network to create
LTE-A environment, in which considerable requirements such as data rate increment, delay time
reduction and cell edge performance issue have been discussed. This chapter also deals with the
challenges that confront the development LTE and. A detailed description of technologies that
are adopted by LTE-A has also been proposed in this chapter. These technologies are mainly
carrier aggregation, HetNets, advanced MIMO antennas, transmission and reception coordination
multipoint, and the relay node. It should be noted that this chapter has detailed explanations for a
specific issues such as inter-cell interference and the proposed solutions that overcome them as
instance ABS operation.
33
References
[28] I. F. Akyildiz, D. M. Gutierrez-Estevez, and E. C. Reyes, "The evolution to 4G cellular
systems: LTE-Advanced," Physical Communication, vol. 3, pp. 217-244, 2010.
[29] AL-Jaradat, Huthaifa 2013, ‘Radio Resource Management in LTE and LTE-A’
[30] Zhang, R.; Zheng, Z. ; Wang, M. ; Shen, X. (Sherman); Xie, L., 'Equivalent Capacity
Analysis of LTE-Advanced Systems With Carrier Aggregation', pp. 6118-22.
[31] Korhonen, J. 2014, 'Introduction to 4G Communications', pp. 219-24.
[32] Su, T.; Pang, J.; Su, HJ. Jun 2012, 'LTE-Advanced Heterogeneous Networks: Release 10
and Beyond', pp. 6999-7003.
[33] SeungJune Yi, S.C., YoungDae Lee, SungJun Park, SungHoon Jung 2012, Radio Protocols
for LTE and LTE-Advanced
[34] Holma H, Toskala A 2012, LTE-Advanced 3GPP Solution for IMT-Advanced
[35] Hu, Rose Qingyang Qian, Yi 2013, Heterogeneous Cellular Networks (2nd Edition).
[36] Yi, Seunglune Chun, SungDuck Lee, YoungDae 2012, Radio Protocols for LTE and LTE-
Advanced.
[37] Shaer, H.E. 2012, 'Interference Management in LTE-Advanced Heterogeneous Networks
Using Almost Blank Subframes'.
[38] Dixit, H.-Y.W.J.R.S., WiFi, WiMAX, AND LTEMULTI-HOP MESH NETWORKS: Basic
communication protocols and Application Areas WILEY.
[39] A. Ghosh and R. Ratasuk, Essentials of lte and lte-a: Cambridge University Press, 2011.
34
3. Chapter 3: Radio Resource Management
3.1. Introduction
In the recent telecommunication networks, an important and new tool called Radio Resource
Management (RRM) has been used. The increments of the required services with a high level of
transmission reliability and throughput, as well as the minimum level of delay, are the main
reasons behind using the RRM. It is not only the aforementioned reasons, but also the radio
elements are decreasing due to the increasing of users’ demands. In general to achieve the
maximum resource utilization, RRM is using the affordable adaptation approaches such as link
adaptation, users scheduling and hyper automatic repeat request (or so called HARQ). On the
other hand, RRM manages the users according to their QoS requirements that have been agreed
by both users and the networks providers.
In the Figure 3.1, the RRM functionality and the mapping process from RRM to the various
lower layers factions are shown. It also shows the control plane and users plan at the enhanced
node B (eNB). Mainly, the factions of RRM are classified into two sorts: semi-automatic and
fully automatic. The former functions are performed at the third layer when a data flow is started,
for example, admission control and permanent scheduling and management of QoS. Unlike
semi-automatic, the fully-automatic functions are conducted the lower layers (1 and 2) at each
new transmission time period which is normally 1 ms. Examples of such functions are link
adaptation (LA), H-ARQ and scheduling of packets [3].
Figure 3.1 RRM functions and the mapping to the lower layers [3]
35
The network element that is responsible for the RRM functions in the LTE and LTE-A is the
enhanced node B (eNB) due to the distributed network architecture and removing the functions
of Radio Network Controller (RNC). However, basic reports and information are still required
such as Channel State Information (so-called CSI) in order to guarantee the best utilization of
resources. These are the resources that can be allocated to the UEs by the resource allocator
according to the status of the channel.
3.2. RRM in both DL and UL
The Radio Resource Management is a collection of methods and algorithms that manage
telecommunication system elements such as frequency, power, and modulation/coding. It
ensures that the users get the agreed QoS while utilization from the finite affordable radio
resources as efficient as possible. In the uplink and downlink, the main functions of RRM are
similar. However, there are some limitations encounters each direction that can be detailed
separately. The following are the main strategies that used in RRM:
3.2.1. Connection Mobility Control (CMC)
In the Radio Resource Control RRC, there are two main mobility modes of connection, idle
mode and connection mode.CMC is responsible for the managing the radio resources in the
(RRC IDLE) or (RRC CONNECTED) in which the connection parameters are set. The
threshold and hysteresis are the parameters that used in the idle mode to enable the users from
defining a cell or re-selecting new cell using reselection algorithms. More complexity has to be
applied in the connection mode in which the resources mobility has to be presented (i.e.,
Handover).The eNB and UE feedbacks and reports can be used to measure the required
handover decision. However, more parameters could be utilized to take this decision such as
the load in the adjacent cells, the predefined-policies of the operator and the traffic allotment.
On one hand, it should be noted that in the idle mode the handover is made explicitly by the UE
even though there is information provided by the network about cell selection and reselection.
On the other hand, the mobility of UE in the connected mode is made by eNB with or without
measurements and reports from the UE to take the handover decision as mentioned previously.
36
3.2.1.1. Handover
Handover could be defined as the operation in which new radio link is created between the
serving eNB (so-called source eNB) and new target eNB to hand the active UE to the better
receiving signal eNB. In general, there are two different sorts of handover; within the wireless
system technology is call intra-handover such as handover in the LTE network between base
stations and with other wireless communication systems called inter-handover. An example of
inter-handover is the one that occurred between GSM and LTE. Further classification of
handover whether intra or inter is that soft handover (SHO) and hard handover (HHO). The soft
handover is shown in the legacy system such as GSM where the UE creates a new connection if
the single strength is better with the target base station before leaving the serving one (source
BS). This rule is a well-known as “make before break”. The soft handover supports the data to be
delivered to the UE simultaneously from more than BS. Although the soft handover algorithms
are more complex than hard handover, it provides smoother handover and reduces the probability
of outage[28]. SHO has two main techniques in wireless telecommunication networks explaining
in the following:
1- Macro Diversity Handover (MDHO): In this technique, there are a set of BSs called active
set or diversity set that the UE can connect. While data is sent from all the BSs in the
diversity set to the UE in the downlink direction, in the uplink direction, all active group BSs
are responsible for receiving and processing data sent by the UE. In the system, there are also
adjacent BSs for the active group. These BSs are monitored by the UE and can receive UE
signals. However; the signal strength is insufficient to add the neighboring BSs to the active
list. MDHO provides seamless, fast and stable handover which in turn reaches the system to
a better performance. The drawback of this method is that the complexity in term of its
algorithm and handover procedure compare with the hard handover. As a consequence, it is
also considered that it wastes network resources and increases the system overhead due to the
parallel synchronization between BSs from one side and between UE and BSs from the other
side. MDHO is applied in UMTS and WiMAX [29].Figure 3.2 shows the principle of Macro
Diversity Handover (MDHO).
37
Figure 3.2 Principle of Macro Diversity Handover [29]
2- Fast Base Station Switching (FBSS): Similarly, to MDHO, the UE connect to the group of
BSs known as the active set. The different in this technique is that the UE monitors all BSs in
the diversity set and decides; considering the signal strength, one of them as the anchor BS
[29]. The UE is capable of connecting to only the anchor BS in the active list BSs for all
downlink and uplink exchanges including control messages. For this reason, it is obvious that
the overhead will be reduced using FBSS comparing with MDHO. In addition, the smoother
traffic transfer from the serving base station to the receiving base station is supported using
this type of handover. However, FBSS suffers higher data lost latency and higher outage
probability in comparison to MDHO. Figure 3.3 illustrates the principle of this handover.
Figure 3.3 Principle of Fast Base Station Switching Handover [29]
38
Hard handover, on the other hand, is based on the rule break before make that means that the UE
is connected to the target eNB after breaking up its connection with the serving eNB. In E-
UTRAN, only one cell is always serving the UE, in turn, the soft handover is not supported
because it needs more than a single connection simultaneously to make the handover operation.
For this reason, only hard handover is used in LTE system [33]. If the signal strength of the
target eNB is higher than the original signal received from the source eNB by the UE, the UE is
hard handed over. Figure 3.4 illustrates the HHO.
As aforementioned before, LTE uses the only hard handover which has some drawbacks that
have to be addressed. The following methods have been adopted in LTE to overcome the HHO
shortages.
1- Semi-Soft Handover Mechanism (SSHO): this technique is adopted based on the macro
diversity mechanism (MDHO). It is a mix of hard handover and soft handover, so it
utilizes the advantages of both. It is considered the best solution to the multicarrier
networks and proven in [30] by simulations and analysis that it gives better performance
than using SHO and HHO separately. It is also so-called Site Selection Diversity
Transmission (SSDT). The idea of SSDT is that depending on the channel quality
indicator it selects and sends each DL symbol. As shown in [30], the researchers use the
SSDT OFDM-based broadband networks with zero-adding to cope the obstacles facing
HHO and SHO. For an instance as proven in [30], SSDT has the lower probability of
outage comparing to either hard handover or soft handover. Therefore, it is expected that
it will be broadly used in a high-speed multimedia services.
Figure 3.4 Hard Handover
39
2- Combined SHO and Partial reuse: it is integration between soft handover and partial reuse
in the downlink direction of OFDMA system to mitigate the inter-cell interference effect.
The target of such mechanism is that the increment of the average throughput specifically
at the cell edge while sustaining the data rate fairness among system UEs. This technique
is also used to decrease overhead of the SHO. The idea of this system is electing the
better signal quality between the SHO system and Partial reuse system for UEs at the cell
boundary.
3- Multicarrier Handover Mechanism: this technique can provide an increment in the cell
capacity and data rate service. In this system, the UEs can to keep its connection with
the source eNB while performing the handover with the target eNB concurrently which
means fast and seamless handover. Figure.3.5 states the multicarrier handover scheme.
As shown from the figure, the UEs move from the baste station 1(in LTE eNB1) to the
base station 2. The carrier 1 is used to keep the connection with the serving BS while the
other carrier (Carrier 2) searching for the best target BSs depending on the active target
BSs list. At the hysteresis point, the UE performs the handover operation using carrier 2,
then disconnecting from BS1 that is made using carrier 1 [29]. The following figure (3.5)
illustrates this scheme.
Figure 3.5 Multicarrier Handover [29]
40
4- Fractional Soft Handover Mechanism (FSHO): this technique divides the services as
VoIP and non-VoIP. This classification of services helps to treat the traffic separately in
which the VoIP services use soft handover while the rest of the supported services are
utilized of hard handover. It is proven in the simulation in [31] that this scheme is better
than SHO in terms of probability of outage and overhead which are both lower. The
backward compatibility of this system with LTE gives it a chance to be the preferred
option among other HO schemes in order to provide mobility enhancement in LTE-A
system.
3.2.1.2. Future Trends of Handover
One of the main trends in the modern system such as LTE-A is that the fast and
seamless handover procedure. It relies on the applied services for instant real-time
services (RTS) such as video streaming where there is a need to high data rate and
broader bandwidth. This results in reducing the connection for the RTS during the
HO process while the users move from serving eNB to the target eNB. However, this
is not the case in the non-RTS such as internet browsing in which the need for high
data rate and wider bandwidth is unnecessary. The user has not observed any effects
during the handover operation [29].
The next factor that could be considered as a future trend of handover is that the
backward compatibility and supporting legacy systems such as GSM, UMTS and
EDGE. That is; LTE-A and its UE is compatible with the legacy system of
telecommunications; thus, its handover techniques have to support the previous
communication systems.
3.2.1.3. Handover Phases in LTE-A
In general, the handover procedure can be divided into four phases as the following:
- Initiation phase.
- Preparation phase.
- Execution phase.
- Completion phase.
It should be mentioned that some telecommunication resources have divided handover into three
phases only, combining Initiation and Preparation in one phase and re-called it Preparation
phase. Because LTE-A has two interfaces X2 interfaces and S1 interface, the handover could be
41
classified based on these interfaces. While X2-based handover obviously happens between eNBs
only when there is no need to change the serving MME as a consequence for handover operation,
S1-based handover takes place when the MME is changed because of the handover. It further
affects the network since it reaches MME node, and it takes more time than the X2-based HO.
The main different between those two sorts is the network signaling that happened between
source and target eNBs and in some cases core network (CN). However, the signaling over the
radio link has no change in which same RRC procedure are conducted, and the UE behavior is
unchanged [33]
1- Initiation phase: in this phase, the source eNB chooses from the neighboring competitive
eNBs as a target where the UE will switch to. In addition, the serving eNB decides when the
UE has to be moved to the chosen target eNB [33].Figure.3.6 explains the initiation phase.
Figure 3.6 X2 Initiation Phase [34]
2- Preparation phase: this is the phase where not only the measurement reports are important
as input to the handover decision to be taken, but also the MME could provide another
important input to the handover decision. This input is a handover specific list of competitive
target eNBs used by the serving eNB to filter the target eNBs [33].The handover decision is
important to specify whether the handover is X2 type or S1 handover. X2-based handover in
this phase has the following procedure as shown in Figure.3.7.
42
Figure 3.7 X2 based Handover –Preparation Phases [33]
Source eNB is responsible for initiating the handover request through X2 interface, so it sends a
request to the target eNB asking for the permission to hand its user and prepare the HO
operation. Generally, in the handover preparation phase, the serving eNB informs the target eNB
about all the inter-node RRC-information related to the served UE. This information involves
settings of RRC that are already being applied, RRM specific information of the UE, and the
information about the connected UE’s capability of radio access. These details are required to
configure the target eNB to be capable of serving the UE during the handover and after
completing the HO operation. To recover the probability of handover failure, the source eNB
includes other important information via inter-node RRC information called re-establishment
information used in reestablishing the connection. Via X2 interface, target eNB acknowledges
the handover request of the source eNB directly using Handover Request Acknowledgment
message.
43
In S1-based handover, on the other hand, the source eNB sends the initiated message
(Handover Request Message) to the MME through S1 interface informing about the need
to trigger the handover preparation with the target cell. Handover Request Message has
valuable information such as priority and QoS that it is important to configure the target
eNB to be ready to serve the transferring UE.
Figure 3.8 S1 based Handover – Preparation Phases [33]
44
While the target eNB gets the Handover Request Message, it can accept or refuse the request of
handover depending on the feedback in the Handover Request Message. In another words, target
eNB performs the admission control relying on the available radio resources, eNB configuration
and information in Handover Request Message. If there is a one affordable enhanced radio
access bearer (E-RAB) at the target eNB, this eNB prepares the required resources to serve the
new transferred UE and acknowledges the source eNB by sending HO Request ACK message.
ACK message is sent to the MME. It contains the required configuration changes that have to be
aware by the UE while moving to the target eNB. Finally, MME sends back an explicit message
called “Handover Command message” to the source eNB containing the RRC connection
configuration through S1 interface. S1 based handover is shown in Figure.3.8.
3- Execution Phase
It is a phase in which the target eNB commands the source eNB to start the handover by sending
the RCC reconfiguration message. The source eNB forwards without updating the
reconfiguration message received from the target eNB to the UE. The content of the
reconfiguration message is the mobility control info (Handover Command) which is used to
order the mobile to reset the current MAC and RRC sessions and to signal with new eNB. The
Handover Command includes information such as used frequency, target cell downlink and
uplink bandwidths, and the target eNB physical ID. It also has new C-RNTI that is utilized at a
target eNB to define the UE and provide the required information to access the common
channels (RACH). Moreover; the security information is included in the mobility control info
message. If there is data being under transmitting while the handover occurs, the source eNB
forwards the data to the target eNB to prevent data loss. In the X1 based handover, the data is
sent through the GTP tunnel directly from the source to target eNBs. Unlike X1 based handover,
the S1 handover avoids data loss during the handover operation by sending the data via indirect
route through S-GW.
It should be notice that there is a time limit for handover operation that is set using a timer. When
the timer is expired while the handover is still occurring, the UE announces that the handover is
unsuccessful and starts the procedure of reconnection establishment to cope that failure. Any
delay in handover can be reduced by preventing UE from reading the target cell system
information before accomplishing random access operation. After the handover is completed, all
45
required system information could be requested by the transferred UE from the target eNB. The
handover exaction is shown in Figure.3.9.
Figure 3.9 Handover Execution Phase [33]
4- Completion Phase
It is the phase that from the UE perspective is finished when it sends the RRC connection
reconfiguration complete message. In comparison, from the system point of view is that when
the network performs further procedures such as releasing the radio resource of the source eNB
and transferring the data to the target eNB. However, different procedures are taken place in this
phase regarding whether X1 based handover or S1 based handover. In X1 based handover, the
completion indication message called Path Switch Request message is sent by the target eNB to
MME. Similarly, in S1 based handover, but the message is called Handover Notify message.
Upon MME getting either message, it connects with the serving gateway (S-GW) to arrange data
switching from the serving eNB to the target cell.
46
The source eNB releases UE and the used radio resources when it is notified by the target eNB in
X1 based handover or MME in S1 based handover that the handover is completed. This can be
conducted using the UE Context Release message or UE Context Release Command message
respectively. As aforementioned before, all handover phases are limited by handover timers.
These timers are used to guarantee that the handover operation is conducted properly. For
instance, if the source eNB does not receive a completion messages from other participating
nodes (target eNB or MME as explained before), the source eNB will force the MME to send the
UE Context Release Command by sending the Context Release Request message. Figures 3.10
and 3.11 show the completion phase in X1 based handover and S1 based handover respectively.
Figure 3.10 Handover Completion Phase-X1 based Handover [33]
47
3.2.2. Admission Control
To satisfy SLA and QoS that agreed with the networks’ customers in the modern
telecommunication networks, admission control (AC) is applied which is one of the fundamental
and crucial method. AC is not 3GPP standard in which different providers use various AC
algorithms to meet their network and customer needs. Therefore, it is specified by the vendor for
each eNB in the system to guarantee that the newly admitted traffic will not affect the current
applied QoS for the served flows [23]. Different restrictions limit AC decision, for example, the
required QoS for both new and admitted bearers, the affordable radio resources, and the type of
traffic. Mainly, AC operation accepts or rejects the requested EPS - Evolved Packet System
bearers in the system. EPS contains a profile that clarifies the QoS requirements involving
several numbers of auto-modified parameters.
Figure 3.11 Handover Completion Phase-S1 based Handover [33]
48
The following details clarify EPS auto-modified downlink parameters:
1- QoS Class Identifier (QCI). It is one of the most important parameters that have different
values for other parameters such as packet error rate of layer 2, packet latency of layer 2 and
priority of scheduling. These parameters can achieve the required HOL delay target by
prioritizing different queues. Resources allocation is based on QCI, for example, if UE uses
VoIP and browsing services, the higher priority (VoIP) is allocated resources firstly then the
browsing. 3GPP has defined nine QCIs with their characteristics as shown in Table 3.1
QCI# Bite Rate Type Priority L2- Packet Error Rate L2-Packet Delay Example services
1 (GBR) 2 10-2 100ms Conventional voice
2 (GBR) 4 10-3 150ms Conventional video
3 (GBR) 5 10-6 300ms Buffered streaming
4 (GBR) 3 10-3 50ms Real-time gaming
5 (non-GBR) 1 10-6 100ms IMS signaling
6 (non-GBR) 7 10-3 100ms Live streaming
7 (non-GBR) 6 10-6 300ms Buffered streaming, email,
8 (non-GBR) 8 10-6 300ms browsing, file download,
9 (non-GBR) 9 10-6 300ms file sharing, etc.
Table 3.1 QCI Parameters for EPS Bearer QoS Profile [3]
2- Guaranteed Bit Rate (GBR). It is the parameter that grants a certain bit rate to the bearer that
is identified as GBR bearer. In the case of non-guaranteed bit rate bearer sort, another
parameter called AMBR (Aggregate Maximum Bit Rate) is assigned. A bearer can be
allocated a maximum bit rate (MBR) in certain conditions.
3- Allocation Retention Priority (ARP). It is sixteen integer values starts 1 and ends with 16.
APR performs admission control decisions prioritization. There is confusion about the
different between ARP and QCI. APR relates to services and bearers allocation while as
mentioned before, QCI concerns about resource allocation. An example of ARP is that UE
aims to setup VoIP (higher ARP priority) along with browsing service; the eNB will reject
the browsing request and admit only the VoIP request in order not to be overloaded.
49
The Radio Resource Management at eNB is responsible for managing and handling different
load conditions (i.e., low load, moderate load and excessive load). At the excessive load
condition, occurrence of a received packet blocking is highly possible. On the other hand, in the
situation of low load there is no possibility for packet blocking since the active UEs are few, in
turn, the amount of transmitted data is small and the inter-cell interference level is at its
minimum value. Moreover, the minimum QoS requirements for the active users are guaranteed.
In LTE network, the system starts utilizing all available physical radio resources as the number
of admitted UEs into the system increases. Additionally, in order to satisfy QoS constraints for
various users, the operation of layer 2 scheduling for more UEs is increased. At a full load using
all available PRBs, there is a possibility that the system may admit more UEs while marinating
agreed QoS level of the current served users unchanged. The packet scheduler entity will allocate
fewer resources to the best effort bearers if the allocated resources for the users with stricter QoS
(i.e., GBR) increase. However, further optimizations may be required as the system is loaded
with more users. Due to the fact that there are both RT traffic and Non-RT traffic in one
scenario, the switching between L2 scheduling (dynamic scheduling) and L3 scheduling (semi-
persistent scheduling) is beneficial. It is obvious that more regulation is required while the traffic
increases. However, the admission control entity will begin blocking arriving new users’ traffic
although the RRM functionalities (i.e., scheduling) aim to increase cell capability to serve more
users with their associated traffic types [24].
3.2.3. Packet Scheduling (PS)
Radio Resource Management entity at the eNB for a multi-carrier advanced LTE network is
shown in Figure.3.12. Essentially, the main two parts of RRM are: carrier component (CC)
allocation and Packet Scheduling (PS). Carrier component allocation is that RRM selects and
allocates CCs for each UEs while Packet Scheduling (PS) is responsible for assigning radio
resources to each user within each CC. The PS decision is made at each transmission time
interval TTI (1 ms) or at resource-block-pair (RB of o.5 ms subframe over 180 kHz), taking into
account the feedback from the users using Channel Quality Indicator CQI. It helps eNB to
estimates the reachable throughput for each user using the feedback information. Furthermore,
eNB informs the users about the affordable allocated resources [25]. Even though the load status
and the user past throughput are present in the eNB, only uplink CQI feedback is useful from the
eNB point of view to make a decision about resources allocation.
50
One the other hand, each UE measures the received signal to interference ratio (SINR) carried on
the reference signal sent by the serving base station in the downlink direction. A user is usually
moving in the cell coverage; thereby the time-selective fading and multi-path fading natures
exist. This results in different calculated SINR values on each subcarrier at each Transmission
Time Interval. The measurements, specifically effective SINR values, aid UE to feedback its
channel status to the serving eNodeB. The values of effective SINR are used by the base station
to select modulation and coding scheme (MCS) in the downlink packet direction [35].The later
(MCS) is related to the data rate determination, in which the bits that are supported by users are
determined based on MCS. Not only finding out the data rate in two contiguous RBs as
mentioned before, but also selecting the priority of the users in channel-depending scheduling is
supported using the effective SINR. The packets for each user are buffered upon arriving at
eNodeB, and time stamped by the scheduler. Then, the First-In-First-Out (FIFO) technique is
used to handle user’s packets. To control the queuing operation and avoid long waiting time for
the packet, Head Of Line (HOL) packet latency has been utilized. It is the different between the
current time of a certain packet and arrival time of the same packet [35]. The HOL delays are
assigned for different traffic types based of the classification of the traffics as Real Time (RT)
and Non-Real Time (NRT) services. The threshold point of the HOL is when it exceeds the
delay’s deadline; at this point the queued packets are deleted.
Figure 3.12 RRM Framework in LTE-A [25]
51
Packet scheduling can be classified into two types: in the downlink direction which is the most
important one since it is related to eNB and performed by RRM, and in the uplink direction
which is conducted by UE.
3.2.3.1. Downlink Packet Scheduling
Due to the fact that there is a limited number of available radio resources for each network
operators, PS is proposed to meet the goal of maximizing the utilization of these resources, and
in the meantime satisfying the agreed level of QoS for connected UEs. The decision of
scheduling is made at each transmission time interval; hence, UEs are allocated different amount
of radio resources blocks (PRBs) each TTI according to their requested services. The decision
not only includes PRBs allocation, but also Modulation and Coding Schemes (MCS) or what so-
called link adaptation to be used in the downlink packets communication. PDCCH is used to
carry the allocated resources to the users. The link between the eNB and users has two main L2
flows: one carries the data (data plane), and one carries the control information (control plane).
In the downlink direction, there is interaction between the packet scheduler and Hybrid ARQ
entity as shown in Figure.3.13. Retransmission is managed by Hybrid ARQ manager and
scheduled dynamically by the PS in frequency/time domains. While the frequency domain
scheduling means that the user is allocated PRBs, the time domain scheduling means that the
user is selected to be scheduled at TTI. The scheduler serves all UEs and ensures there is fairness
among them by sending either a new flow or awaiting Hybrid ARQ flow to each scheduled UE
in one TTI. If the scheduler schedules both flows simultaneously to one user, other users in the
system will suffer starvation [24]. Figure 3.3 also shows Link Adaptation mechanism which
interacts with scheduling operation to provide the suitable modulation and coding schemes
(QPSK, 16QAM or 64 QAM) according to the utilized physical resource blocks for each UE.
The CQI receiving from the users and QoS at the eNB are used in LA decisions [3].
52
Figure 3.13 Interactions between HARQ, PS and LA [3]
The higher channel quality user is the selected user to be scheduled in the frequency domain
scheduling schemes (FDPS) since frequency selective fading is achieved. Accordingly, any
PRBs with deep fade are avoided by FDPS [24] as shown in Figure.3.14.
Figure 3.14 Frequency DPS Concept [3]
There are two methods that have been used to conduct the packet scheduling: per each carrier
component (CC) so-called independent scheduling or cross CC scheduling. The cross CC
scheduling is more complex than independent scheduling since it based on all other available
CCs in the system. This is; the metric of scheduling is calculated differently in each one [25].
53
Independent CC PS. the similarity to the traditional PS in a single carrier system is shown
in this method, in which there is no need to consider the transmission characteristics on
other CCs. Dividing the instantaneous throughput by the average throughput of the
selected user is the used method to calculate the scheduling metric.
(3.1)
the estimated throughput for user k on ith
CC at the jth
PRB group is represented by ,
the average throughput at the past for the same user on the same CC is represented by
.
The equation is considered to Rel8. For LTE-A, since it could be assigned more than one
CC, the same equation is used multiplied by total number (N) of allocated CCs for LTE-
A UEs.
Cross-CC PS. considering the transmission characteristics of all CCs, PS fulfills better
resource allocation than independent packet scheduling. Unlike independent PS, the past
user throughput over the all aggregated CCs is taken into account to calculate the
scheduling metric.
(3.2)
3.2.3.2. Packet Scheduling Algorithms in Downlink Direction
The packet scheduling algorithms are various based on RT and NRT services. The common
adopted PS algorithms according to [26] and [35] are:
First-In-First-Out (FIFO). The user with the highest packet delay HOL at each TTI is
given transmission priority. It provides considerable fairness among users who have
similar packet’s characteristics such packet size and channel status [35].
Round Robin (RR). In this algorithm, transmission time interval is divided equally
among users, in which each user is allocated equal time to transmit its packet in a circular
order. This algorithm is similar to FIFO that provides a high level of fairness. However,
the throughput performance in RR is higher than FIFO.
54
Maximum Rate scheduler (Max Rate).Once the highest achievable data rate is reached,
the UE is selected to be scheduled. Equation 3.3 expresses Max Rate scheduling
algorithm:
(3.3)
is the reachable data rate for a UE denoted by k at time t based on the received
SINR at eNB where and SINR are directly proportional. Because this algorithm is
designed to schedule users with maximum data rate regarding with their best channel
conditions, it provides the best system throughput. Accordingly, the poor fairness is
obvious in Maximal Rate PS algorithm since the lower received SINR value the less
opportunity for user to be selected for transmission. Moreover, UE’s resources starvation
could happen since the user is probably never selected for scheduling.
Proportional Fair (PF). PF algorithm balances the system performance between the
throughput and the fairness among users, giving a trade-off between them. A user is
allocated resources if it has the maximum ratio between the instantaneous achievable rate
and the transmission rate divided by the average throughput.
(3.4)
, is the average throughput of user k at time slot t. It is calculated by considering the
window size as follows:
(3. 5)
when UE k is selected for transmission, the value equals 1, otherwise the value
equal 0.
The reason behind a good throughput and fairness performance is that PF algorithm
performs incorporation for the feasible data rate with an average throughput [35].
Frame Level Scheduler (FLS). The FLS is a combined algorithm that has two levels of
scheduling; upper and lower level, thereby, separate algorithm for each one. Upper level
is less complexity in allocation of resources since it depends on the theory of discrete
time linear control. The task of the upper level is that satisfying delay constraint by
calculating the amount of data that each real-time source should send within a single
55
frame. Equation 3.16 shows the calculation of the aforementioned amount of data at
upper level of FLS. The lower level, on the other hand, is more complexity since it uses
PF algorithm to allocate resources to the UE [36].
(3.6)
denotes the data amount that is sent within the frame n for flow. is the
filtered signal by which is a time-invariant linear filter with pulse response.
According to the results in [11] cited in [36], the FLS provides restricted delays and
lower PLR values for a video traffic ,thereby, the performance of FLS ensures the best
quality of the video service for the scheduled users.
Modified-Largest Weighted Delay First (MLWDF). This algorithm is introduced to
support Real Time services. The metric of scheduling is shown :
(3.7)
where;
(3.8)
HOL packet delay of user at time is denoted by , is the delay’s deadline that
the maximum HOL probability to exceed it is .
The benefit of MLWDF is that using PF properties along with the HOL packet delay
consideration introducing a better throughput, fairness and Packet Loss ratio than PF
algorithm.
Exponential/Proportional Fair (EXP/PF). The aim of proposing this algorithm is to be
used for multimedia services for both Real Time and Non-Real Time services
simultaneously. The metric for RT and NRT is shown below:
(3.9)
where,
(3.10)
(3.11)
56
denotes the average number of packets queued in the buffer at time t, k and in equation
(3.11) are predefined values, is the highest HOL packet delays for the packet awaiting for
RT services, and is the maximum delay of RT service users.
Although EXP/PF is adopted for both real time and non-real time users, it precedes RT users
over the NRT if the RT users’ packets reach the transmission threshold[35].
Logarithmic (LOG) Rule scheduler. The LOG Rule allocates the resources to the
scheduled UEs increasing current throughput by supposing the channel status and traffic
arrival are realised. The main propose that LOG Rule is designed to provide QoS
balancing in term of robustness and mean delay. According to [13] cited in [36], the
simulation results prove that LOG Rule is a superior algorithm that has the best packet
delay decreasing. Although this algorithm is an experimented practically as a good
solution, it is not proven as an optimal method for mean-delay achievement [36]. LOG
Rule and EXP Rule algorithms are a type of opportunistic scheduling, in which they
exploit the desirable channel to schedule the active users, for example, the users with the
highest rate.
Exponential (EXP) Rule. Similarly to LOG Rule, the goal of proposing this algorithm
was basically to satisfy QoS requirements in the wireless network. The balance between
the throughput and mean-delay is conducted by maintaining minimum value of delay and
at the mean time a considerable value of throughput, thereby, mean-delay is obtained. It
works on the concept of wireless channel sharing among arrival users and queues their
data as a random stream to be prepared for transmission. This scheduler enables users
accessing the services during each time interval. Optimal throughput is determined
according to [12] cited in [36]. The difference with LOG rule is that there is no previous
estimation of traffic arrival and channel statistics. However, the EXP Rule explicitly
utilizes received channel statistics information and guarantees achieving stable queues.
Two exponential rules have been introduced in this scheme: EXP Waiting time (EXP-W)
and EXP Queuing (EXP-Q). The algorithm selects one rule at a time for scheduling users
with different fix positive parameters (i.e., and ) as
shown in equations (3.12) and (3.13).
57
(3.12)
(3.13)
where,
and
(3.14)
is the total number of queued users who are selected for transmission at time .
3.2.3.3. Uplink Packet Scheduling
In the UL scheduling, the user is aware of packets scheduling, and it has to buffer the arrived
flows. The finite size of the users’ buffers degrades the performance of scheduling operation at
the UEs since the base station in LTE is unaware of the size of UEs’ buffer. Not only the
buffering limitation at the UEs, but also the power limitation in uplink direction emerges another
constraint for the uplink scheduling. Obviously, eNB power in the downlink is much higher than
the UEs power. On the other hand, resource allocation restriction exists since single carrier
modulation has been used with uplink scheduling. In consequence, solely adjacent PRBs can be
assigned to each UE.
CSI report is the feedback information that is used to choose the modulation and coding scheme.
Relying on the Sounding Reference Signal (SRS) sent by the UE, the CSI is determined. The
integration in the uplink direction between RRM, LA and PS is shown in the Figure.3.15. Link
Adaptation compromises adaptive modulation and coding, Outer Loop Link Adaptation (OLLA)
and Power Control (PC). PS has scheduling request, buffer status report and Adaptive
Transmission Bandwidth (ATB). There is also a relation as seen in Figure.3.15 between LA and
PS, in which PC and AMC of LA interact with PS. That is, on the channel state, the packet
scheduler receives required information related to the transmission bandwidth from AMC for a
certain user. Uplink PC main purpose is that maintaining SINR to a certain level called SINR
threshold according to the agreed QoS while limiting the ISI [3].
58
Figure 3.15 Uplink RRM Functionalities inter-work with LA and PS [3]
3.2.4. Power Control (PC)
The Orthogonal Frequency Division Multiple Access OFDMA and the Single Carrier Frequency
Domain Multiple Access are the radio technologies used in LTE and LTE-A. The reason behind
adopting OFDMA and SC-FDMA in the modern networks is that to elevate the effect of intra-
cell interference that is the interference between users within a single cell. The orthogonality is
used to avoid users having the same peak at a certain point of time instead only one user could be
served at that peak. However, another interference causing by adjacent cells, which is well-
known as inter-cell interference cannot be negligible, introducing a real challenge since
orthogonal modulations is not designed to solve such interference. It requires other mechanisms
to solve it that the power control is one of them. Since the PC limits the cell boundary, it can
eliminate the impact of inter-cell interference. The control of the transmitted power can be
performed at UE in the uplink direction or the base station (eNodeB) in the downlink direction
[32].
59
The UE transmits the power in the uplink direction based on the equation (3.15).
(3.15)
Where and are the UE’s maximum allowed transmit power based on the UE power
classification and the number of allocated physical radio resources on the PUSCH respectively.
UE measures the downlink path loss which is denoted by , denotes closed-loop power
control correction that eNB transmits (details can be found in 3.8.4 of [37] ).
are parameters of PC. The can be computed as follows [32]:
(3.16)
where is the target of open loop SNR (details can be found in 3.8.3 of [37]), and are
the PRB noise power and the number of PRBs required to fulfill the target SNR with full power,
respectively.
UE initiates a transmission power based on and the calculation of the path loss
performed by the UE. Since eNB signals the value of to UE who already has completed
setting the initial power, it does not contribute in the initiation operation. Hence, by ignoring the
value of as well as , the equation (3.15) can be written as following:
[dBm] (3.17)
It represents the calculation of the initial transmitted UE power.
The number of scheduled PRBs is denoted by in which the UE allocates power based on
PRB. That is; the amount of power for each PRB is equal.
To calculate the UE’s Power Spectral Density (PSD) to each PRB, the value of is
neglected and the equation (3.17) is changed to be as the following [32]:
[dBm/PRB] (3.18)
The power control has two types depends on the value of in Equation (3.18). If the value of
is between 0 and 1, the power control mode is called fractional power control.
When the value of is 1, the power control mode is called conventional power-control. Other
types of power control have to be mentioned here which they are: open loop power control and
close loop power control. Detailed descriptions of the power control modes can be found in [37].
60
3.2.5. Balancing of Carrier Load
LTE and LTE-A can coexist together in the same network due to the backward compatibility of
LTE-A. As mentioned before the maximum prescribed bandwidth of LTE is 20MHz. To achieve
LTE-A bandwidth that is 100 MHz, 5 CCs of Rel8 have to be aggregated. In LTE, UEs are
allocated a single CC while in LTE-A UEs are assigned multiple CCs based on their channel
conditions. The flowchart in Figure.3.16 explains the LTE-A’s eNB classification operation
whether the case of LTE UE or LTE-A UE to make a decision of radio resources allocation on
CC(s). To balance the load on all available CCs, UEs are equally scheduled on all CCs using a
smart load balancing mechanism. This could guarantee an exploitation of all affordable resources
on CCs. The following sections discuss the load balancing methods.
Figure 3.16 eNB Classification for LTE Rel 8 and LTE-A Arrival UEs [25]
3.2.5.1. Carrier Load Balancing
As aforementioned, Rel 10 has a backward compatibility with Rel8. For a user in LTE, the
system allocates one CC while the system could allocate number of CCs based on the QoS and
user’s feedback reports for a user in LTE-A. The CCs’ balanced distribution among the served
users can be performed by deploying balancing methods as the following [27]:
61
Round Robin (RR) Balancing Method: in this method, the user is allocated 1 CC. The
newly arrived user is assigned the least exploited carrier by other users. The aim of that is
to divide UEs equally on all available CCs. An issue of this method is that the CCs load
could have a minor difference due to the probability of uneven number of users or due to
the fact that the users could free up the allocated CC at random.
Mobile Hashing (MH) Balancing Method: also well-know independent carrier channel
assignment. Similarly to RR, a user is allocated 1 CC. However, MH differentiates from
RR by using hash algorithm calculations of the terminals. The purpose of considering the
output of hash values is that providing a long-term CCs load balancing. In order to
achieve that, it requires uniformly distributing of the values of hash outputs among a
limited set that CC indices are mapped directly on it.
3.2.6. Interference Management
The interference is one of the big challenges encounter LTE and LTE-A especially with HetNets,
in which the small cells (Pico, Femto, RRH or relay node) use the same carrier frequency of the
Macro cells. The higher power eNB (Macro cell) is overlaid with small lower power cells that
are used with less care or uncoordinated manner. The technology that has been implemented to
relieve the impact of the interference between adjacent cells is the Inter-cell Interference
Coordination (ICIC). ICIC is the operation in which the interference could be mitigated if high
transmission power on PRBs is avoided. That is; the users on the cell edge can be served in the
neighboring cells. There are two classes of ICIC schemes based on the way it deals with the
interference. The first class is reactive ICIC that is responsible for monitoring the system. That
is; if it observes a high level of the interference, the suitable procedures will be implemented.
Examples of the reactive ICIC are packet scheduling and power control for the purpose of
interference reduction to an appropriate status. The other class is proactive that is responsible for
avoiding the interference before the high level is detected. That could be performed through the
eNBs coordination in which neighboring eNBs receives feedback from the eNB informing about
the future plans of scheduling its users. These reports can be considered to avoid low value of
Signal- to- Interference Ratio (SIR) that could occur [3]. There is a relation between proactive
ICIC and Relative Narrowband Transmit Power (RNTP). RNTP is a PRB’s peak downlink
transmission power. Neighboring eNB receives RNTP through X2 interface, then these RNTP
62
values can be utilized by the neighboring eNB to make a decision for scheduling its UEs.
Especially, the UEs who are more likely existed at the cell edge have a high probably to suffer
from neighboring cells interference (LTE case) or small cells and neighboring cells (LTE-A
case).Thus, RNTP facilitates the proactive ICIC in the downlink direction. Various parameters
are considered to perform the proactive and reactive ICIC in the uplink direction. The High
Interference Indicator (HII) and Overload Indicator (OI) are used to support proactive and
reactive ICIC schemes respectively. HII carries a serving eNB message to its adjacent cells over
X2 interface indicating which PRBs will be exploited for scheduling boundary cell UEs such as
the higher interference expectation of PRBs from the neighboring cells perspective. Hence, the
adjacent cells allocate those PRBs to the lower interference UEs. This is the reason that why HII
is seen as a technique of proactive ICIC.
As mentioned before, OI is related to reactive ICIC scheme and its task essentially is to carry
reports of the measured uplink interference on reporting eNB’s PRBs at three levels (low,
average and high). The adjacent eNBs deal with these measurements once they are received by
adjusting the scheduling behavior to the extent that enhances the SIR of the OI releasing eNB
[11].
3.3. Summary
RRM is the entity that is mainly responsible for the following: Handover, Admission Control,
Packet Scheduling, Power Control and Interference Management. Thus, it plays a vital role in the
most recent LTE and LTE-A networks where the most important functions in managing a mobile
network is performed at eNB using RRM. While the LTE-A is introduced through HetNets, the
importance of RRM has increased due to the increment of the issues related to interference,
handover and scheduling. Since the simulation and practical outcomes in the next chapter mainly
concern with Handover and Packet Scheduling and its algorithms, the focus in this chapter is on
these RRM functionalities.
63
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4. Chapter 4: LTE-Sim Heterogeneous Network Deployment
4.1. Introduction
In the Long Term Evolution so-called LTE, the requirements for larger coverage area, more
capacity, and high data rate and low latency have led to search for cost-effective solutions to
meet these demands. Hence, the development in the telecommunication networks has adopted
different directions to enhance the LTE system taking into account the International Mobile
Telecommunications (IMT-2000) standards that have to be satisfied [1]. Network-based
technologies such as Multiple Input and Multiple Output MIMO/ advanced MIMO and
Transmission/Reception Coordinated Multi-Point CoMP are LTE enhancements that introduce
LTE Advance (LTE-A). Other fewer cost enhancements based on air interfaces are proposed,
such as improving spectral efficiency involving using Heterogeneous networks (HetNets).
HetNets are small and lower power cells within the main Macro cells with different access
technologies to close up the network to the end users and increase their expectation
[16].According to [2], there are two main practical HetNets classes: Macro with Femto and
Macro with Pico. Femto and Pico are the small and lower power cells. To save the cost,
operators use the same carrier frequency in the large and small cells which, on the other hand,
proposes interference challenges. Figure.4.1 gives the main concept of HetNets. To clarify, user
in LTE is well-known as a UE.
Figure 4.1 an Example of HetNets
66
In LTE and LTE-A, the element that is responsible for Radio Resources Management (RRM) is
enhanced Node Base station (so-called eNB). The eNB does all required management including
Packet Scheduling (PS) which is the focus in the paper. PS can guarantee the agreed quality of
service demands (QoS) because it is responsible for the best and effective utilizing of the
affordable radio resources and in charge of data packets transmission of the users[3].
3rd Generation Partnership Project (3GPP) has left the scheduling algorithms to be a vendor
specific according to user’s requirements and network capability. Therefore, various PS
algorithms have been proposed depending on the traffic sorts and provided services. PF,
MLWDF and EXP/PF algorithms [4][5][6] are used in this paper to study and compare between
the system behaviours in HetNets (single Macro with 2 Pico cells) using these three types of
algorithms. Scheduling algorithms ensure that QoS requirements have been met. This can be
conducted by prioritizing each link between the eNB and the users, the higher priority
connection the first handled in the eNB.
4.2. Downlink System Model of LTE
The basic element in the downlink direction of the LTE networks is called Resource Block
(RB).Each UE is allocated certain number of resource blocks according to its status, the traffic
type and QoS requirements. It could define the RB in both frequency domain and time domain.
In the time domain, it comprises single (0.5 ms) time slot involving 7 symbols of OFDMA
(orthogonal frequency division multiple access). In the frequency domain, on the other hand, it
consists of twelve 15 kHz contiguous subcarriers resulting in 180 kHz as a total RB bandwidth
[7].
As aforementioned before, the eNB is responsible for PS and other RRM mechanisms. The
bandwidth that is used in this study is 10 MHz considering the inter-cell interference exists. The
period that eNB performs new packet scheduling operation is the Transmission Time Interval
(TTI). TTI is 1 ms that mean the users are granted 2 contiguous radio resource blocks (2RBs).
The scheduling decision in the serving eNB is made based on the uplink direction reports come
from the UEs at each transmission time interval. The reports comprise the channel conditions on
each RB, such as signal to noise ratio (SNR). The serving eNB uses the SNR value involved in
the reports to specify the DL data rate for each served UE in each TTI. For example, how many
bits per 2 contiguous RBs [8].
67
The data rate for user i at j sub-carrier on RB and at t time can be determined by using
equation (4.1) as proposed in [9].
(4.1)
A =
B =
C =
D = rgg
The number of bits per symbol is “A”. The number of symbols per slot is “B”. While “C”
represents how many slots per TTI, “D” clarifies how many sub-carriers per RB. Table 4.1
summarizes the mapping between SNR values and their associated data rates.
Minimum SNR Modulation and Data Rate
Level (dB) coding (Kbps)
1.7 QPSK (1/2) 168
3.7 QPSK (2/3) 224
4.5 QPSK (3/4) 252
7.2 16 QAM (1/2) 336
9.5 16 QAM (2/3) 448
10.7 16 QAM (3/4) 504
14.8 64 QAM (2/3) 672
16.1 64 QAM (3/4) 756
Table 4.1 Mapping between instantaneous downlink SNR and data rate
Upon the packets reach the eNB, they are buffered in eNB in a specific container allocated for
each active UE. Moreover, the buffered packets are assigned a time stamp to ensure that they
will be scheduled or dropped before the scheduling time interval is expired, and then using First-
In-First-Out (FIFO) method they are transmitted to the users in the downlink direction. To
explain the scheduling operation, PS manager (is a part of eNB functionalities) at each TTI
priorities and classifies the arriving users’ packets according to preconfigured scheduling
algorithm.
68
Scheduling decision is made based on different scheduling criteria that have been used in various
algorithms. For example channel condition, service type, Head-of-Line (HOL) packet delay,
buffer status, and so on so forth. One or more RBs could be granted to the selected user for
transmission with the highest priority. Figure.4.2 shows the packet scheduler in the downlink
direction at eNB.
4.3. Packet Scheduling Algorithms
The efficient radio resource utilization and ensuring fairness among connected users, as well as
satisfying QoS requirements, are the main purposes of using PS algorithms [11].The PS
algorithms that have been used in this study are : Proportional Fair (PF) algorithm, Maximum-
Largest Weighted Delay First (MLWDF or ML) and the Exponential/Proportional Fair (EXP/PF
or EXP) algorithm. It should be noted that these algorithms are used.
4.3.1. Proportional Fair (PF) Algorithm
For non-real time traffic, the PF was proposed which is used in a Code Division Multiple
Access- High Data Rate (CDMA-HDR) system in order to support Non-Real Time (NRT)
traffic. In this algorithm, the trade-off between fairness among users and the total system
throughput is presented.
Figure 4.2 Downlink Packet Scheduler of the 3GPP LTE System [10]
69
This is, before allocating RBs, it considers the conditions of the channel and the past data rate.
Any scheduled user in PF algorithm is assigned radio resources if it maximizes the metric k that
calculated as the ratio of reachable data rate of user i at time t and average data rate of
the same user at the same time interval t:
(4.2)
where;
(4.3)
is the window size used to update the past data rates values in which the PF algorithm
maximizes the fairness and throughput for any scheduled user. Unless user i is selected for
transmission at , = 0.
4.3.2. Maximum Largest Weighted Delay First (MLWDF) Algorithm
If the traffic is a Real Time (RT), the MLWDF is introduced which is used in CDMA-HDR
system in order to support RT data users [11].It is more complex algorithms compare with PF
and is used in different QoS user’s requirements. This is because it takes into account variations
of the channel when assigning RBs. Moreover, if a video traffic scenario, it takes into
consideration time delay. Any user in MLWDF is granted RBs if it maximizes the equation
below:
(4.4)
where;
(4.5)
where is a difference in time between current and arrival times of the packet that known as
the Head Of Line (HOL) packet delay of user i at time t.
Similarly to PF equation, while the achievable data rate of user i at time t is , the average
data rate of the same user at the same time interval t is . and are the delay threshold
for a packet of user i and the maximum HOL packet delay probability of user i respectively. The
later is considered to exceed the delay threshold of user i.
70
4.3.3. Exponential/Proportional Fair (EXP/PF) Algorithm
Since PF is not designed for multimedia applications (only for NRT traffic), an enhanced PF
called EXP/PF algorithm was proposed in the Adaptive Modulation and Coding and Time
Division Multiplexing (AMC/TDM) systems. The EXP/PF algorithm is designed for NRT
service or RT service (different sorts of services). The metric is used for both RT nad Non-RT
in which RBs are assigned to users based on .
(4.6)
where,
(4.7)
(4.8)
where the average number of packets at the buffer of the eNB at time t is represented by , k
and in equation (8) are constants, is explained in MLWDF, is the HOL packets
delay of RT service and is the maximum delay of RT service users. The EXP/PF
differentiates between RT and NRT by prioritizing RT traffic users over the NRT traffic users if
their HOL values are reaching the delay threshold.
4.4. Simulation.1- Single Macro Cell with two Pico Cells
This simulation has been performed to compare between a telecommunication system that
involves only Macro cell and same telecommunication environment with adding two small low
power cells called Pico cells.
71
4.4.1. Simulation.1 Environment
LTE-Sim simulator is used to do the entire analysis and study [12]. The most recent version of
LTE-Sim (version 5) has not involved yet any code regarding the HetNets type (Macro with Pico
cells). The developed code used in this study could be considered as an enhancement of the
released LTE-Sim versions. However, LTE-Sim has a detailed code (or what authors are named
it: scenario) which can be used to simulate and examine HetNets type (Macro with Femto). This
simulation is based on a scenario of a single Macro cell with 2 small Pico cells that are reduced
their powers. More Picos can be added to the system, and enhanced system behaviour will be
presented (details are discussed in simulation 3). However, according to [2], while the number of
Pico cells is increased, more inter-cell interference is experienced since the same carrier
frequency is used in each cell (Macro and Picos). Figure.4.3 shows the entire system that is
deployed: Macro cell of 1 km and 2 Pico cells of 0.1 km located on the Macro edge. This design
is chosen to emulate a real system aimed to cover larger area and more users, especially the users
at the cell edge where they suffer from lack of connectivity with Macro cell. The inter-cell
interference is modeled. Video and VoIP traffic are used to represent user’s data. Each user has
50 % Video traffic and 50% VoIP flows.
Handover is activated. Each cell starts a certain number of users. Non-uniform user distribution
within the cells is deployed, and 3km/h constant speed is utilized as the user speed mobility. In
addition, the 3GPP urban Macro cell propagation loss model has been implemented including
path-loss, penetration loss, multi-path loss and shadow fading which are summarized below [13]:
Pathloss: , d refers the distance between the eNB and the user in
kilometers.
Penetration loss: 10 dB
Multipath loss: using one of the well-known methods called Jakes model
Shadow fading loss (recently it could be used as a gain in LTE-A): log-normal distribution
- Mean value of 0 dB.
- Standard deviation of 10 dB.
72
Figure 4.3 Applied HetNets (Macro with 2 Picos)
Packets throughput (see equation 4.9), Packet Loss Ratio (PLR) as viewed in equation (4.10),
packet delay (latency) and fairness index (equation 4.11) are the concepts used in the
aforementioned algorithms to evaluate the system performance. Jain’s method is applied to
implement fairness among users [14]. According to [1], fairness should reach the value of 1 to be
considered as a fair algorithm that sharing the resources suitably among users. It can be
calculated as the value of one minus the value of the difference between the maximum and
minimum size of transmitted packets of the most and least scheduled users. Equation (4.11)
calculates the fairness value.
(4.9)
(4.10)
(4.11)
73
Obviously, while is the size of transmitted packets, is the size
discarded or lost packets during the connection. is the summation of all arrived packets
that are buffered into serving eNB [1].
The aforementioned total size of transmitted packets of the best served UE and the worse served
UE are represented in equation (11) as and .Table 4.2
shows the entire system simulation parameters [1].
Parameters
Simulation time
Flow duration
30 s
20 s
Slot duration
TTI
Number of OFDM symbols/slot
Macro cell radius
Macro eNB Power
Pico cell radius
Pico eNB Power
0.5 ms
1 ms
7
1 km
49 dBm
0.1 km
30 dBm
User speed 3 km/h
VoIP bit rate 8.4 kbps
Video bit rate 242 kbps
Frame structure type FDD
Bandwidth 10 MHz
Number of RBs 50
Number of subcarriers 600
Number of subcarriers/RB 12
Subcarrier spacing 15 KHz
Table 4.2 LTE System Simulation Parameters
74
In order to get better results and confirm the outcomes, five simulations have been conducted for
each algorithm (PF, MLWDF and EXP) in each point of users (10, 20, 30, 40, 50, 60, 70 and 80).
This yields 120 simulations outcomes. The average values have been taken to draw the
simulation graphs at each point of users.
4.4.2. Simulation.1 Results
The system is judged base on throughput, Packet Loss Ratio (PLR), delay and fairness.
4.4.2.1. Throughput
The average overall system throughput is shown in Figure.4.4. Comparing the throughput for
“single Macro cell” for the same simulation parameters as viewed in Figure.4.5, the pico cells in
the scenario “Macro with 2 Picos” boost the throughput by adding gain that shown as an overall
system throughput increment for the same number of users. For instance, at 40 users using
MLWDF, the throughput is 25 Mbps for the scenario with 2 Picos while the Macro scenario is
only 9.3 Mbps. This is almost a double value. Further points show duple and triple throughput
values in the scenario of 2 Picos. However, the gain will reach a saturation level where no more
gain could be obtained due to the fact of limited radio resources availability while more users are
added to the system. Although MLWDF and EXP have almost similar behaviour in both
scenarios, a higher throughput is acquired in the 2 Pico case using both algorithms. It could note
that PF algorithm behaves better than the scenario of single Macro cell as seen Figure.4.5. PF is
developed for NRT traffic, but the simulation is for Video flows (RT traffic); hence, the other
simulated algorithms outperform PF.
Figure 4.4 Average System Throughput (Macro with 2 Picos)
75
Figure 4.5 Average System Throughput (single Macro cell)
4.4.2.2. Packet Loss Ratio (PLR)
PLR shown in the Figure.4.6 according to [15] is the packet loss ratio for a single Macro cell.
While the system is charged with more than 20 users, the PLR is increased for all experienced
algorithms taking into consideration that the PF is the worst case with the video traffic. Adding
two Picos to the previous system to create “Macro with 2 Picos” scenario enhances the PLR
while maintaining similar system behavior for all algorithms. Approximately, the PLR in Macro
with 2 Picos case is reduced to be a quarter of PLR value of single Macro cell scenario. For
example, at 70 users, MLWDF has 0.1 PLR value while for the same number of users MLWDF
has 0.5 PLR value in the single Macro scenario. PF algorithm is the worst case in both simulated
cases comparing with the other scheduling schemes. Figure.4.7 illustrates PLR for Macro with 2
Picos.
Figure 4.6 PLR of Video Flows (single Macro cell) [15]
76
Figure 4.7 PLR of Video Flows (Macro with 2 Picos)
4.4.2.3. Delay
According to [15] and as illustrated in Figure.4.8 , the delay in single Macro cell scenario is close
to be constant for PF, MLWDF and EXP/PF with value less than 5 ms while it suffers from rapid
increasing after 40 users for PF algorithm. If two Pico cells are added to the aforementioned
system, a similar performance is shown, but the delay value is decreased. In addition, the
threshold of PF is shifted at 60 users instead of 40 users in the single Macro case. To compare
MLWDF and EXP/PF in both scenarios, a certain point in Figures.4.8 and 4.9 could be
explained. For example at 60 users, in a single Macro cell the delay value is 50 ms while the
value is 20 ms in the Macro with 2 Picos. As a consequence, for MLWDF and EXP/PF, the delay
value with two Picos is approximately half the delay value without Pico cells. One of the
purposes of HetNets is to enhance the latency, and this is viewed in a practical simulation
illustrated in Figure.4.9. However, the delay manifests lower values (nearly 10 times lower) in
the scenario of the single cell with 2 Picos using PF scheme.
77
Figure 4.8 Packet Delay of Video Flows (single Macro cell)
Figure 4.9 Packet Delay of Video Flows (Macro with 2 Picos)
4.4.2.4. Fairness Index
When the number of users increases in single Macro cell more than 30, the fairness index of all
simulated algorithms is deviated down of the value “1”. At 40 users, PF experiments further
deviation close to value 0.8 compare with other algorithms that they are around 0.9 as seen in
Figure.4.10. The fairness index behaves similarly in the scenario of Macro with 2 Picos as shown
in Figure.4.11. However, the PF shows a minor different in which at 50 users it starts to decline
to get the value 0.8.
78
Figure 4.10 Fairness Index of Video Flows [15]
Figure 4.11 Fairness Index of Video Flows Macro with 2 Picos
4.5. Simulation.2-Single Macro Cell with two Pico Cells (Different Speed
Comparison)
This simulation has been done to compare between telecommunication systems that compromise
of a Macro cell with two small low power Pico cells where the users are moving in 3 Km/hand in
one scenario and 120 Km/h in the other scenario.
79
4.5.1. Simulation.2 Environment
Similar simulation environment that have been mentioned in Simulation1 is applied in this
simulation. LTE-Sim platform is used with the added code that demonstrates the new scenario of
Macro with two Picos. The parameters in the Table 4.2 are applied, but the speed is changed to
be 120 Km/h instead of 3 Km/h. Similar Pico cells positions in the Macro cell as seen in
Figure.4.3 is considered. This distribution is more likely close to the normal Pico positions in the
practical networks, in which operators locate Pico cells in Macro boundary to extend the
coverage, increase capacity and boost the throughput. Useless Pico cells will be if their base
stations near the Macro eNB position, that is, the Macro eNB already serves the UE. Handover is
activated, and 3GPP urban Macro cell propagation loss model has been performed as
aforementioned in simulation1. Initially, each HetNets cell has a certain number of users who
can be handed over during the simulation between Macro and Picos and vice versa. In this
simulation, number of users increase equally in all cells. However, theoretically Pico cell could
serve 16-32 UEs simultaneously [17]. Each user has 50% video flows and 50% VoIP. The
outcomes are based on the video traffic.
4.5.2. Simulation.2 Results
It could predict the simulation results since high speed degrades the system behaviour the users’
connectivity with system’s cells will be worse. The degradation is shown as reducing overall
system throughput while increasing PLR, latency and fairness.
4.5.2.1. Throughput
As seen in Figure.4.12, the dashed lines denote PF, MLWDF and EXP/PF in the case of 120
Km/h speed. It is obvious that the system is degraded due to the speed increment for each user.
For example, the point 60 users has 16 Mbps throughput value if the mobility speed is 120 km/h
while in the case of 3 Km/h the same point has more than 25 Mbps for all scheduling schemes.
However, if it is compared with Figure.4.5 (throughput in Macro cell only at speed of 3 Km/h),
the system manifests better performance although the speed is 120 Km/h. This is due to the
positive impact of adding two Pico cells. As an example, the maximum throughput value viewed
in Figure.4.5 is almost 12 Mbps due to the effect that there are no Pico cells.
80
4.5.2.2. Packet Loss Ratio (PLR)
The PLR value is highly affected by the speed of mobility. Packets are likely to suffer of errors
and could be dropped while the speed is increased due to the fact that the connectivity with the
base stations gets worse. As seen in Figure.4.13, the PLR value is higher in the scenario of 120
Km/h speed, in which the higher PLR, the worse system performance. Considering point 60 of
users, the average PLR values for all scheduling algorithms is 0.33 while the speed is 120 Km/h.
Same point at speed 3 Km/h illustrates lower PLR values for all schedulers, for example, PLR of
PF is 0.14 which is almost half the value of 0.33 in the 120 Km/h scenario. The scheduling
schemes are performing similarly. However, MLWDF and EXP/PF outperform PF in both
scenarios.
Figure 4.12 Throughput of Video in Macro with 2 Picos
(3 Km/h and 120 Km/h speed)
Figure 4.13 PLR of Video in Macro with 2 Picos (3 Km/h and 120 Km/h speed)
81
4.5.2.3. Delay
Figure.4.14 shows the delay of the system in both when the speed is 120 Km/h (the dashed line)
and the speed 3 Km/h (the straight line). The delay is higher in the scenario of 120 Km/h
especially with the PF scheme. Maximum delay in the case of 3 Km/h is 20 ms as experimented
in this simulation.EXP/PF and MLWDF have similar behaviours in the both scenarios although
the delay in the case of 120 Km/h is almost double the value of that in the case of speed of
walking. For instance, at 60 users in the 120 Km/h speed, the EXP/PF and MLWDF has a delay
of 44 ms while in the other case the delay is 20 ms which is nearly half the value of 44 ms.
4.5.2.4. Fairness Index
The system provides fairness values similar to those in the simulation1.Pf is outperformed by
MLWDF and EXP/PF where it shows more decline down the value of one as the number of
users increases. The speed has an impact on the fairness values. As it is seen in Figure.4.15, the
120 Km/h scenario enhances the fairness slightly than the 3 Km/h scenario for all scheduling
schemes. This gives a good indication that using HetNets (Macro with Pico cells) with high
speed mobility not only keeps the system performing similarly, but also could enhance the
fairness index. However, PLR, delay and throughput have lower values using high speed
mobility, thereby; the overall system is degraded when the users are moving fast.
Figure 4.14 Delay of Video in Macro with 2 Picos (3 Km/h and 120 Km/h speed)
82
Figure 4.15 Fairness Index in Macro with 2 Picos (3 Km/h and 120 Km/h speed)
4.6. Simulation.3- Single Macro Cell with Increasing Pico Cells
Third Simulation has been conducted to compare between different scenarios of a single Macro
cell telecommunication system by adding more Pico cells. The increment is constant; that is, in
each case two more Pico cells are added in new positions at the Macro cell edge.
4.6.1. Simulation.3 Environment
Same simulation environment has been used for the rest of the study. However, further updated
code has been used in LTE-Sim simulation platform to perform this analysis. The simulation is
based on a scenario of a single Macro cell with 2, 4, 6, 8 and 10 small Pico cells. Each Pico
transmits 30 dBm of power while the Macro cell transmits 49 dBm. Table 4.2 parameters are set
up in all scenarios to maintain same values for the system while increasing the Pico cells by
factor of 2. This ensures that all new results of the system performance come through the factor
of adding Pico cells only. However, flow duration and simulation time have been modified to 30
and 40 respectively. All other aforementioned simulation environment elements are similarly
utilised such as 3GPP urban Macro cell path loss and handover activation. Users at Pico cells are
not equal to the Macro cell users. Pico cannot serve more than 30 users [17] users, thereby, after
30 users there are no more users could be added. Nevertheless, all cells start with 10 users and
increase by factor of 10. Flows are equally divided into Video and VoIP flows, in which each of
them is 50% of the total system traffics. In this simulation, there are two sides have to be
considered. One of them is increasing the number of Pico cell gradually by factor of 2, and the
other one is increasing the number of users by the factor of 10. Because of this, 3D graphs are
83
used to represent the system performance besides using 2D graphs to study the system behaviour
in different scheduling schemes. The distribution of the Pico cells within Macro boundary
follows Figure.4.16. Table 4.3 summarises the (x,y) values for each position from the simulation
outcomes.
Figure 4.16 Applied HetNets (Macro with Multiple Picos Scenarios)
Macro (x,y) 2 Pico cells
(x,y)
4 Pico cells(x,y) 6 Pico cells (x,y)
id 0, position: 0, 0
id 1, position:
1000, 0
id 2, position: -
999.9 , 1.5
id 1, position: 500.4, 865.7
id 2, position: -499, 866.5
id 3, position: -501.8, -
864.9
id 4, position: 497.6, -867.3
id 1, position: 1000, 0
id 2, position: 500.4, 865.7
id 3, position: -499, 866.5
id 4, position: -999.9, 1.5
id 5, position: -501.8, -864.9
id 6, position: 497.6, -867.3
8 Pico cells(x,y) 10 Pico cells(x,y)
id 1, position: 1000, 0
id 2, position: 707.3, 706.8
id 3, position: 0.79, 1000
id 4, position: -706.2, 707.9
id 5, position: -999.9, 1.5
id 6, position: -708.5, -705.6
id 7, position: -2.3, -999.9
id 8, position: 705.1 ,-709
id 1, position: 1000, 0
id 2, position: 809.2, 587.5
id 3, position: 309.6, 950.8
id 4, position: -308.1, 951.3
id 5, position: -808.2, 588.8
id 6, position: -999.9, 1.5
id 7, position: -810.1, -586.2
id 8, position: -311.1, -950.3
id 9, position:
306.5, -951.8
id 10, position:
807.3, -590.1
Table 4.3 Pico Cells Positions in meters into the Macro Cell (Radius 1 Km)
84
4.6.2. Simulation.3 Results
As mentioned before, adding more Picos more likely enhances the system performance. This is
proven in this simulation demonstrated through the throughput, PLR, delay and fairness. Adding
2 extra Pico cell improves the overall system throughput with a certain value which cannot be
normalized .This is because number of reasons such as increasing the number of users,
increasing the effect of inter-cell interference while the number of users increases and simulation
parameters including power value, simulation time, flow duration affect that while the number of
users increases.
4.6.2.1. Throughput
The average overall system throughput for all scenarios is seen in Figure.4.17. Adding 2 Pico
cells provides almost constant gain in all applied scheduling schemes. To explain that, PF
algorithm (Table.4.4 in 5 cases) is taken as an example. Vertically, the number of users increases
by factor of 10, and by taking the cases (10 users) to (30 users) the gain value is 3.39 Mbps due
to UEs increments. For example, at 20 users the average value of for all scenarios is 6.78 Mbps
that equals the value of 3.39 at 10 users plus the 3.39 Mbps gain. The difference of average gain
between 30 users point and 20 users point is also 3.39 Mbps that proves adding 10 users
increases the throughput in constant value of the gain while adding 2 Pico cells to the system.
After 30 users, the Picos cannot serve more UEs, and the gain will continue at almost the same
value of the gain at 30 users, which is 10 Mbps as average. However, adding more users to the
system (only Macro users) boosts the throughput slightly with nearly 1 Mbps due to the effect of
scheduling algorithms only. Horizontally, moving up from 2 to 10 Pico scenarios the throughput
value increases by average gain of 10 Mbps. Figure.4.18 gives another view of the gain and
shows clearly the system performance in each case. All aforementioned values of the gain are not
constant, and they are based on the simulation parameters and system environment.
85
Figure 4.17 Throughput Gain of Video traffic in Macro with 2-10 Picos Scenarios
PF
Picos (Y-
axes)
Throughput(
Z-axes)
2 4 6 8 10 Average 2 Picos gain [Mbps]
10 5.09 8.48 11.88 15.28 18.67 3.39 Mbps increment
Users (X-
axes) 20 10.17 16.95 23.74 30.53 37.32 6.78 Mbps increment
30 15.124 25.21 35.36 45.46 55.64 10.13 Mbps increment
40 16.41 26.44 36.57 46.52 56.56 10.03 Mbps increment
50 17.26 27.11 36.93 47.05 57.19 9.98 Mbps increment
60 17.55 27.41 37.37 47.45 57.44 9.97 Mbps increment
70 17.29 27.14 37.35 47.46 57.80 10.12 Mbps increment
80 17.00 27.13 37.43 47.55 57.91 10.22 Mbps increment
Table 4.4 Throughput Gain Values and An Average of The Values
86
Figure.4.18 Throughput Gain of Video traffic in Macro with 2-10 Picos Scenarios
4.6.2.2. Packet Loss Ratio (PLR)
Although the number of users increases that means the PLR value increases accordingly, the
PLR values start getting down as the number of Pico cells raises. Adding more Picos can be
equivalent to the PLR increment due to more users is added to the system. For instance, PF
algorithm is the lower performance than other algorithms in most of the cases, in which the PLR
starts going up while the system is charged with more users. However, as seen in Figure.4.19 at
the 50 users, PF with 8 Pico cells case has the same PLR value of other schemes with 2 Pico
cells scenarios. This enforces the idea of equivalent; that is, adding more Picos enhances system
PLR of PF bringing it back to the value where other algorithms are in. Figure.4.20 gives 3D view
of the PLR behaviour in the dimension of adding more users and the dimension of adding more
Pico cells.
87
Figure 4.19 PLR Video traffic Comparison in Macro with 2-10 Picos Scenarios
Figure 4.20 PLR of Video traffic in Macro with 2-10 Picos Scenarios
88
4.6.2.3. Delay
Delay follows similar behaviour to the PLR. While the number of users increases, the delay gets
higher. Reverse of that, while Pico cells are added to the system, the delay becomes lower. Table
4.5 is an example of PF delay values that are obtained from the simulation to draw Figure.4.21
and 4.22. Similarly, MLWDF and EXP/PF have been drawn. PF has the higher delay values in
all scenarios and the highest value in the 2 Pico cell case while the number of users at the
maximum in this simulation. It is easily to notice that PF starts decreasing while the number of
Pico cells increases. Similar performance for all algorithms in all scenarios is viewed in
Figure.4.21. MLWDF and EXP/PF analogy the stairs, in which lower delay values are at 10 Pico
cells scenario climbing up to the higher at 2 Pico cells scenario.
Picos (Y-axes)
Delay
(Z-
axes) 2 4 6 8 10
10 6 5.8 5.64 5.53 5.56
Users
(X-
axes) 20 10.32 9.89 9.67 9.56 9.59
30 14.65 14.17 13.84 13.76 13.83
40 16.57 15.39 14.71 14.48 14.41
50 18.67 16.82 15.89 15.34 15.09
60 20.86 18.12 16.75 16.04 15.7
70 22.78 19.43 17.63 16.72 16.21
80 24.35 20.32 18.25 17.17 16.63
Table 4.5 PF Throughput Gain Values and An Average of The Values
89
Figure 4.21 Delay of Video traffic Comparison in Macro with 2-10 Picos Scenarios
Figure 4.22 Comparison Delay of Video traffic in Macro with 2-10 Picos Scenarios
90
4.6.2.4. Fairness Index
The fairness index has to be closer to the value of one. Adding more users affects this value that
starts slope down. Figure.4.23 shows the fairness index of the system that has 2 to 10 Pico cells.
The value slightly declines from one for the MLWDF and EXP/PF while the PF suffers further
drop from the value of one. Adding more Pico cells has no effect on the fairness as shown from
the Figure.4.23 and Figure.4.24.Compare with the same system without Pico cells (as seen in
Figure.4.10), the system has similar behaviour although adding more cell slightly enhances the
overall system fairness value. From the values of all algorithms, the worst scenario of the
fairness index is at 8 Pico cells in which PF shows the lowest fairness value when the number of
users is 80 and the scenario is 8 Pico cells. MLWDF and EXP/PF also suffers further drop in the
same point as aforementioned in PF. Figure.4.24 illustrates that.
Figure 4.23 Fairness Index in Macro with 2-10 Picos Scenarios
91
4.7. Conclusion
This chapter investigates scheduling algorithms that are developed to enhance the LTE network
performance by sharing radio resources fairly among users utilizing all available resources.
These algorithms depend on traffic class and number of users, hence; different outcomes are
presented for each algorithm. To further boost the overall system performance, this study uses
heterogeneous networks concept by adding small cells (initially 2 Pico cells). This enhancement
is experienced through a throughput, PLR, delay and fairness. In the throughput the system gains
more data rate while in PLR the system suffers less packet loss values. Moreover, delay is
decreased and fairness stays similar. Approximately from the simulation1 outcomes, the overall
system performance is as follows: throughput is duplicated or nearly tripled relaying on the
number of users, the PLR is almost quartered, the delay is reduced 10 times (PF case) and
changed to be a half value (MLWDF/EXP cases), and the fairness stays closer to value of 1. On
the other hand, high speed mobility in simulation2 degrades the overall system performance
although the system appears better fairness index.
Figure 4.24 Fairness Index in Macro with 2-10 Picos Scenarios
92
Lastly, as the number of small cell increases as determined in simulation3, the system manifests
more enhancements as seen in 2D and 3D graphs for throughput, PLR, delay and fairness.
However, it is expected that a saturation state will be reached after a certain point of the number
of Pico cells and the number of users. The reason behind that is the inter-cell interference will
limit the performance since the same carrier frequency is used in all system’s cells. Considering
all scenarios, MLWDF manifests the best performance for video flows followed by EXP/PF.
Further enhancement could be applied in future papers such as almost blank subframes (ABS),
enhanced inter-cell interference cancelation (eICIC), cell range extension CRE concepts. and
using Carrier Aggregation (CA) and CoMP within HetNets.
References
[1] H. A. M. Ramli, R. Basukala, K. Sandrasegaran, and R. Patachaianand, "Performance of well known
packet scheduling algorithms in the downlink 3GPP LTE system," in Communications (MICC), 2009 IEEE
9th Malaysia International Conference on, 2009, pp. 815-820.
[2] Seung June Yi, S.C., Young Dae Lee, Sung Jun Park, Sung Hoon Jung 2012, Radio Protocols for LTE
and LTE-Advanced.
[3] [1] B. Liu, H. Tian, and L. Xu, "An efficient downlink packet scheduling algorithm for real time
traffics in LTE systems," in Consumer Communications and Networking Conference (CCNC), 2013 IEEE,
2013, pp. 364-369.
[4] A. Jalali, R. Padovani, and R. Pankaj, "Data throughput of CDMA-HDR a high efficiency-high data rate
personal communication wireless system," in Vehicular Technology Conference Proceedings, 2000. VTC
2000-Spring Tokyo. 2000 IEEE 51st, 2000, pp. 1854-1858.
[5] M. Andrews, K. Kumaran, K. Ramanan, A. Stolyar, P. Whiting, and R. Vijayakumar, "Providing quality of
service over a shared wireless link," Communications Magazine, IEEE, vol. 39, pp. 150-154, 2001.
[6] J.-H. Rhee, J. M. Holtzman, and D. K. Kim, "Performance analysis of the adaptive EXP/PF channel
scheduler in an AMC/TDM system," Communications Letters, IEEE, vol. 8, pp. 497-499, 2004.
[7] J. Zyren and W. McCoy, "Overview of the 3GPP long term evolution physical layer," Freescale
Semiconductor, Inc., white paper, 2007.
[8] B. Riyaj, M. R. H. Adibah, and S. Kumbesan, "Performance analysis of EXP/PF and M-LWDF in
downlink 3GPP LTE system," 2009.
[9] X. Qiu and K. Chawla, "On the performance of adaptive modulation in cellular systems," Communications,
IEEE Transactions on, vol. 47, pp. 884-895, 1999.
[10] S. C. Nguyen, K. Sandrasegaran, and F. M. J. Madani, "Modeling and simulation of packet scheduling in
the downlink LTE-advanced," in Communications (APCC), 2011 17th Asia-Pacific Conference on, 2011,
pp. 53-57.
[11] A. Alfayly, I.-H. Mkwawa, L. Sun, and E. Ifeachor, "QoE-based performance evaluation of scheduling
algorithms over LTE," in Globecom Workshops (GC Wkshps), 2012 IEEE, 2012, pp. 1362-1366.
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[12] G. Piro, L. A. Grieco, G. Boggia, F. Capozzi, and P. Camarda, "Simulating LTE cellular systems: an open-
source framework," Vehicular Technology, IEEE Transactions on, vol. 60, pp. 498-513, 2011.
[13] M. Iturralde, T. Ali Yahiya, A. Wei, and A. Beylot, "Resource allocation using shapley value in LTE
networks," in Personal Indoor and Mobile Radio Communications (PIMRC), 2011 IEEE 22nd International
Symposium on, 2011, pp. 31-35.
[14] R. Jain, D.-M. Chiu, and W. R. Hawe, A quantitative measure of fairness and discrimination for resource
allocation in shared computer system: Eastern Research Laboratory, Digital Equipment Corporation, 1984.
[15] AL-Jaradat, Huthaifa 2013, ‘On the Performance of PF, MLWDF and EXP/PF algorithms in LTE’.
[16] Holma H, Toskala A 2012, “LTE-Advanced 3GPP Solution for IMT-Advanced”.
[17] Hu, Rose Qingyang Qian, Yi 2013, ‘Comparison Femto cell and Pico cell key features”, Heterogeneous
Cellular Networks (2nd Edition).
1
Research Proposal
LTE-Advance
Enhancement Using CA and CoMP within
HetNets
By
Haider Al Kim
November 2014
Supervisor: Dr. Kumbesan Sandrasegaran
2
Introduction
The telecommunication networks have rapidly been updated since 1980’s where 1G of mobile
telecommunication was proposed. Low traffic capacity, poor call quality and higher power usage
are characteristics of 1G network. Available network resources have to be utilized efficiently to
increase cell capacity, coverage and satisfy Quality of service QoS requirements. Most recent
trends of researchers are designing models that can meet users’ expectations. Although modern
networks have been designed carefully to fulfill the requirements needed by the end users;
significant challenges have emerged. There is a limited bandwidth that has to be used
sufficiently. RRM and air interface techniques have become the research interest fields for the
researchers.
3
Contents
Mobile Telecommunications Trends
Technology Review
Focus Area
Statement of the problem
Methodology
Research Timeline
Bibliography
4
Mobile Telecommunications Trends
Mobile networks have already grown rapidly passing some remarkable signs. Rapid computer
technologies have led to short-period mobile evolution which is aimed to meet the increment of
higher data rate requirements and satisfy a certain agreed QoS. This emulation is shown in
Figure.1.3GPP standardizes the most important demands that have to be met in order to cross the
mobile system to the new generation that is 4G. 4G fulfills the IMT-Advance constraints which
are agreed to increase the user expectation. At the top of the hierarchy, LTE-A, a subset of Rel-
10, has been proposed with significant challenges. The term LTE-A also refers to 4G although
informally the term 4G is used for WiMAXTM.4G is commercially used as a term by some
operators to describe HSPA evolution. International Telecommunications Union Radio
communication Sector (ITU-R) has involved in the development of the proposed system by
3GPP introducing the Release 10 or what so-called recently LTE-A. The ITU-R involvement in
specifying the LTE-A requirements has complicated the process of setting up Rel-10. Although
Rel-8 could meet most of the 4G requirements, LTE-A has other features that could not be
satisfied by LTE. These LTE-A-based requirements are higher bandwidth coming from carriers
aggregating (CA), and higher efficiency could be conducted using higher uplink multiple access
technologies and enhanced multi-in-multi-out MIMO antennas. Further enhancements could be
as essential parts of LTE-A network, but they do not have to be LTE-A requirements. These
features are:
- Support for heterogeneous networks (HetNets) and Relaying
- Coordinated multipoint transmission/reception (CoMP)
- LTE self-optimizing network (SON) enhancements
- Mobility enhancements for Home enhanced-node-B (HeNB)
- RF requirements for fixed wireless customer premises equipment (CPE)
5
Figure.1 Wireless evolution 1990–2012 and beyond: www.low-powerdesign.com
Technology Review
Different access technologies have been introduced with each mobile generation network trying
to address the problems in the previous versions. FDMA network that is an access method used
in the first generation of the mobile telecom-systems has been modified presenting what so-
called orthogonal FDMA that is adopted to be applied in the new mobile generations.
Technically, FDMA is a divided available system bandwidth into non-overlapping frequencies.
The main usage of FDMA was for analogue systems that have been changed later to modern
digitized systems. For the second generation 2G, TDMA is applied as an access technology. That
is; the division is based on the time intervals for each call. Analogue-to-digital converters are
used in TDMA to produce digital signals constructing consolidated digital stream that can be
carried on a single radio channel. While the telecommunication systems continued development,
modern access methods have been adopted. CDMA is the new access technique that is used with
3rd
generation (3G). It is considered a very efficient method to avoid overlapping of FDMA and
the limitation of the time interval of TDMA. Using the code to separate between conversations is
what CDMA has brought. More data rate is required in the recent days due to the demand of
high-resolution video streams and high-quality voice conversations.3GPP provided the standards
of long-term evaluation system LTE. LTE uses most recent technologies in mobile networks.
6
One of them is Orthogonal Frequency Division Multiple Access technology OFDMA that is
utilized mainly to minimize interference effect for overlapped frequencies. Another technology is
MIMO that plays a major role in the LTE system performance that further enhanced to propose
advanced MIMO. LTE with these technologies provides higher efficiency of the spectrum, lower
delay and seamless handover, thereby, performs better than the previous systems.
OFDMA: it is one of a key element in LTE network which is basically used to robust the
resistance to multipath fading and interference as well as it is considered as a digital signal
processing techniques. It guarantees little updating to the existed air interface while flexible
deploying over available frequencies. It also provides an average value of the inter-cell
interference caused by neighboring cells and an average value for intra-cell interference caused
by overlapped frequencies. By spreading the carriers over the available spectrum, OFDMA
provides frequency diversity and excellent coverage. It uses large, narrow band (180 kHz) sub-
carriers for multi-carrier transmission to carry data. Figure.2 shows the basic LTE downlink
physical resource where OFDM symbols are grouped into resource blocks.
Figure.2 Basic LTE downlink physical resource using OFDMA: www.tutorialspoint.com
- MIMO/Advanced MIMO: it is antenna structure that is adopted to robust the data rate
and maximize the performance in LTE-A. The expected LTE-A MIMO is 8x8 downlink
antenna configuration while (4x4) antenna configuration is proposed to be utilized in the
uplink direction. It is one of the suggested smart antenna technologies. The significant
benefit of MIMO is that it provides higher data rate without the need to increase the
7
bandwidth or the transmission power. This can be conducted by spreading the used power
of the transmission among the antennas to enhance the spectral efficiency by obtaining
array gain.
- Relaying and Heterogeneous networks (Macro with Pico or Femto cells): relay, Pico and
Femto are small low power nodes that inserted within or on the edge of the large mobile
cells to enhance the throughput and increase the capacity and coverage. A relay is slightly
different since it protocol structure recently reaches layer 3 (router more than to be a
repeater only). However, the main purpose of it is that retransmitting the received signal
without modifying to the far end that it is out of the main coverage area of large cell.
Small cells and relay are considered an effective air interface enhancement methods
which require lower cost and little modifying to the existing mobile networks.
- Carrier Aggregation CA: in LTE, single carrier is allocated to the LTE user. When LTE-
A is proposed, the demand for more data rate that has to be provided to the LTE-A user is
studied. Hence, CA is applied to increase the bandwidth, thereby, it increases the bit rate.
On the other hand, backward compatibility exists with legacy schemes Rel8/9 that means
they can co-exist with LTE-A where the CA is based on Rel8/9 carrier component. The
maximum LTE available bandwidth is 20 MHz. By aggregating 5 of 20 MHz, the new
LTE-A bandwidth is 100 MHz that provides a higher rate of throughput. Recent studies
are proposed different algorithms to aggregate carrier in LTE-A based on that if the
carriers are on the same frequency band (contiguous or non- contiguous) or cross-carrier
frequency (non- contiguous only).
- Coordinated Multi-Point (CoMP) Transmission/Reception is a mechanism, in which a
number of geographically separated eNBs are cooperated to serve one user in the network
in order to improve the performance the users in the covered areas. The suggested
method of connecting these eNBs is using high speed dedicated connections, for
example, microwave links or optical fiber. The inter-cell interference impact is
affirmatively minimized using CoMP in both the downlink and uplink directions [4].
8
Focus Area
Deploying Heterogeneous networks (HetNets) approach is one of the probable
key features of future LTE-A networks. There are different methods to apply
HetNets in wireless systems. Using separate frequency band in a small cell from
the frequency in a large cell is to avoid the interference. This method is call
dedicated carrier HetNets. There is a drawback of using dedicated carrier, in
which the probability of inefficient usage of the frequency band exists. Moreover,
intra-frequency handover is required while the user is moving between HetNets
cells. The most common approach of HetNets (Macro with small cells) is
applying the same frequency band in all cells with HetNets. This increases the
inter-cell interference, but it could introduce higher spectral efficiency. However,
careful interworking between HetNets cells is vital in the scenario of using the
same frequency in all HetNets cells. That is; it requires a centralized node to
control the HetNets cells, which is called Remote Radio Heads (RRH). According
to NTT DoCoMo [5], new base station is proposed that using advanced
centralized Radio Access Network structure. Once this centralized architecture is
deployed using multiple bands, it is possible to use carrier aggregation in Rel-10
as an extension of a base station. CA could combine contagious or non-
contiguous frequency bands to create LTE required bandwidth. Normally, CA is
conducted on the same cell using the available carriers. However, CA is enhanced
to be involved within multi-cells using the centralized node. With HetNets, a
small eNB has been introduced as a low-cost base station with a reduced
transmission power. Rel-11 provided a multi-carrier aggregation using the timing
advance enhanced uplink power control [6]. Figure.3 illustrates HetNets with
primary cell (large-Macro cell) and secondary cell (small–Pico or Femto). In this
scenario, the Large cell is responsible for providing control signaling, system
information and limited data transmission while the small cell is responsible for
providing the required high data rate. It is beneficial in both cases, CA with
dedicated frequency or co-channel. Due to some drawbacks of this CA in HetNets
such as users’ terminal compatibility a with multi-carrier aggregation of Multiple
9
Timing Advance, another method that does not depend on the centralized node
can be used. That is, large and small cells can operate with own control signaling
for both layered frequencies. This approach requires enhanced interference
management such as ICIC. However, ICIC is limited to the PDSCH data;
therefore, it requires new solutions to separate the control channels. PDCCH is
used to provide full control channel protection especially if it is used as cross-
carrier scheduling. In this case, the interference will be at its minimum value if the
small cell does not use the PDCCH. Figure.4 shows the concept of using PDCCH
in co-channel HetNets.
Figure.3 Multi-Carrier Aggregation in LTE-A HetNets [6]
Figure.4 CA in co-channel scenario in LTE-A HetNets [6]
10
Statement of the problem
Compare with Time Domain Interference Coordination using ABS (Almost Blank
subframe) in eICIC, the aforementioned Frequency Domain Interference
Coordination using PDCCH cross-carrier scheduling has some benefits. Using
eICIC introduces more complexity in the network, for example, signaling and
measurements are more likely to be higher in a co-channel deployment.
However, there is a probability that Macro cell passes out the PDCCH since it
uses cross-carrier scheduling. Moreover, to support MIMO, enhanced PDCCH is
required (ePDCCH) that is already addressed in 3GPP Rel-11 [6].
The current deployment of small cell and relays is using the ideal backhaul which
depends on a centralized architecture and supports easily CA and CoMP
operations [4]. Studies are proposed new methods of deploying small cell with
non-ideal backhaul. Currently in Rel-11, it could aggregate two TDD carriers with
different configuration of uplink and downlink. Such configuration requires UE
has an ability to transmit and receive in parallel. This could lead to that such
system is similar to FDD. Hence, operators could combine FDD and TDD
spectrums in one solution. For HetNets, a clustered TDD small cell deployment
could be possible as shown in Figure.5. By separating these clusters, a dynamic
adjacent of uplink / downlink frame structure could be possible relying on the
need of local traffic in the small cells.
11
Figure.5 Dynamic TDD in LTE-A HetNets [6]
Using HetNet with CA and CoMP is the key evolution of future networks.
Investigating using HetNets small cell as corporative cells to apply CA and CoMP
techniques is a major interest in this proposal. Intensive most recent papers will be
reviewed and studied that address and discuss the current challenges as motioned
before ideal backhaul as a centralized architecture where CA and CoMP rely on.
Figure.6 shows the suggested scenario for future HetNets. Hence, HetNets
deployment not only supports large cell to serve some users who suffer from bad
connectivity with Macro cell, but also could be utilized simultaneously as
corporative cells to apply CA and CoMP concept. It could further increase
throughput, coverage and capacity besides reducing the latency.
More enhancements for small cell will be considered, such as using 256 QAM to
enhance spectral efficiency, enhanced inter-frequency measurement and enhance
interference coordination to improve small cell operation [6].
13
Methodology
Technology Review Searching State of the art scientific
papers
Identifying existed problem/Technology limitation
Preparing developing model/writing paper
Code writing and Simulation implementation
Results/ Conclusions
Writing Thesis
14
Research Timeline
Task First Year Second Year Third Year Forth Year
1st Semester
2nd Semester
3rd Semester
4th Semester
5th Semester
6th Semester
7th Semester
8th Semester
Technology Review Searching State of
the art scientific papers
Identifying existed problem/Technology limitation
Preparing developing model/writing paper
Code writing and Simulation implementation
Results/ Conclusions
Writing Thesis /Extension if required
15
Bibliography
[1] A. T. Moray Rumney, LTE and the Evolution to 4G Wireless: Design and
Measurement Challenges, Second Edition. John Wiley and Sons, Ltd, 2013.
[2] A. Toskala and H. Holma, WCDMA for UMTS HSPA Evolution and LTE,
Fourth Edition. John Wiley and Sons, Ltd, 2007.
[3] D. K. Sandrasegaran, \Lecture note, lte radio resource management," tech.
rep., University of Technology, Sydney.
[4] I. F. Akyildiz, D. M. Gutierrez-Estevez, and E. C. Reyes, "The evolution to
4G cellular systems: LTE-Advanced," Physical Communication, vol. 3, pp. 217-
244, 2010.
[5] Press Release NTT DoCoMo TOKYO, JAPAN, February 21, 2013:
“DOCOMO to Develop Next generation Base Stations Utilizing Advanced C-
RAN Architecture for LTE-Advanced”
[6] Eiko Seidel, “LTE-A HetNets using Carrier Aggregation” , NoMoR Research
GmbH, Munich, Germany, June 2013.
1
APPLIED CODE
1- Simulations Parameters
Type (Shell Code, .sh)
2- Simulations Parameters
Type (C++, .h)
2
3- Single Macro with Multiple Pico Cells - Cells Positions Part of
the Code
Type (C++, .h)
4- Single Macro with Multiple Pico Cells – Create Pico Cells Part
of the Code
Type (C++, .h)
3
5- Main LTE-Sim Execution File includes Single Macro with
Multi Pico Passing Parameters from the (.sh) file (C++ , .cpp)
6- An Example of The First Part of Simulation File Outcomes
International Journal of Wireless & Mobile Networks (IJWMN) Vol. 6, No. 5, October 2014
DOI : 10.5121/ijwmn.2014.6509 109
MACRO WITH PICO CELLS (HETNETS) SYSTEM
BEHAVIOUR USING WELL-KNOWN SCHEDULING
ALGORITHMS
Haider Al Kim1, Shouman Barua2, Pantha Ghosal2 and Kumbesan Sandrasegaran2
1Faculty of Engineering and Information Technology, University of Technology Sydney,
Australia {Haider.A.AlKim}1@student.uts.edu.au
{shouman.barua, pantha.ghosal, kumbesan.sandrasegaran}2@uts.edu.au
Abstract
This paper demonstrates the concept of using Heterogeneous networks (HetNets) to improve Long Term
Evolution (LTE) system by introducing the LTE Advance (LTE-A). The type of HetNets that has been chosen for
this study is Macro with Pico cells. Comparing the system performance with and without Pico cells has clearly
illustrated using three well-known scheduling algorithms (Proportional Fair PF, Maximum Largest Weighted
Delay First MLWDF and Exponential/Proportional Fair EXP/PF). The system is judged based on throughput,
Packet Loss Ratio PLR, delay and fairness.. A simulation platform called LTE-Sim has been used to collect the
data and produce the paper’s outcomes and graphs. The results prove that adding Pico cells enhances the
overall system performance. From the simulation outcomes, the overall system performance is as follows:
throughput is duplicated or tripled based on the number of users, the PLR is almost quartered, the delay is
nearly reduced ten times (PF case) and changed to be a half (MLWDF/EXP cases), and the fairness stays
closer to value of 1. It is considered an efficient and cost effective way to increase the throughput, coverage
and reduce the latency.
Keywords
HetNets, LTE <E-A, Macro, Pico, Scheduling algorithms & LTE-Sim
1. INTRODUCTION
In the Long Term Evolution so-called LTE, the requirements for larger coverage area, more capacity,
and high data rate and low latency have led to search for cost-effective solutions to meet these
demands. Hence, the development in the telecommunication networks has adopted different
directions to enhance the LTE system taking into account the International Mobile
Telecommunications (IMT-2000) standards that have to be satisfied [1]. Network-based technologies
such as Multiple Input and Multiple Output MIMO/ advanced MIMO and Transmission/Reception
Coordinated Multi-Point CoMP are LTE enhancements that introduce LTE Advance (LTE-A). Other
less cost enhancements based on air interfaces are proposed, such as improving spectral efficiency
involving using Heterogeneous networks (HetNets). HetNets are small and less power cells within
the main macro cells with different access technologies to close up the network to the end users and
increase their expectation [16].According to [2], there are two main practical HetNets classes: Macro
with Femto and Macro with Pico. Femto and Pico are the small and less power cells. To save the
cost, operators use the same carrier frequency in the large and small cells which, on the other hand,
proposes interference challenges. Figure 1 gives the main concept of HetNets. To clarify, user in LTE
is well-known as a UE.
International Journal of Wireless & Mobile Networks (IJWMN) Vol. 6, No. 5, October 2014
110
Figure.1 an example of HetNets
In LTE and LTE-A, the element that is responsible for Radio Resources Management (RRM) is
enhanced Node Base station (so-called eNB). The eNB does all required management including
Packet Scheduling (PS) which is the focus in the paper. PS can guarantee the agreed quality of
service demands (QoS) because it is responsible for the best and effective utilizing of the affordable
radio resources and in charge of data packets transmission of the users[3].
3rd Generation Partnership Project (3GPP) has left the scheduling algorithms to be vendor specific
according to user’s requirements and network capability. Therefore, various PS algorithms have
been proposed depending on the traffic sorts and provided services. PF, MLWDF and EXP/PF
algorithms [4][5][6] are used in this paper to study and compare between the system behaviours in
HetNets (single Macro with 2 Pico cells) using these three types of algorithms. Scheduling
algorithms ensure that QoS requirements have been met. This can be conducted by prioritizing each
link between the eNB and the users, the higher priority connection the first handled in the eNB.
This paper is organized as follows. Section II discusses the downlink system model of LTE. The
followed section (III) describes in more details packet scheduling algorithms, while Section IV
present simulation environment. Section V shows the outcomes of the simulation. Finally, conclusion
is given in Section VI.
2. DOWNLINK SYSTEM MODEL OF LTE
The basic element in the downlink direction of the LTE networks is called Resource Block
(RB).Each UE is allocated certain number of resource blocks according to its status, the traffic type
and QoS requirements. It could define the RB in both frequency domain and time domain. In the time
domain, it comprises single (0.5 ms) time slot involving 7 symbols of OFDMA (orthogonal
frequency division multiple access). In the frequency domain, on the other hand, it consists of twelve
15 kHz contiguous subcarriers resulting in 180 kHz as a total RB bandwidth [7].
As aforementioned before, the eNB is responsible for PS and other RRM mechanisms. The
bandwidth that is used in this study is 10 MHz considering the inter-cell interference is existed. The
period that eNB performs new packet scheduling operation is the Transmission Time Interval (TTI).
International Journal of Wireless & Mobile Networks (IJWMN) Vol. 6, No. 5, October 2014
111
TTI is 1 ms that mean the users are allocated 2 contiguous radio resource blocks (2RBs). The
scheduling decision in the serving eNB is made based on the uplink direction reports come from the
UEs at each transmission time interval. The reports comprise the channel conditions on each RB,
such as signal to noise ratio (SNR). The serving eNB uses the SNR value involved in the reports to
specify the DL data rate for each served UE in each TTI. For example, how many bits per 2
contiguous RBs [8].
The data rate for user i at j sub-carrier on RB and at t time can be determined by using equation
(1) as proposed in [9].
(1)
A =
B =
C =
D = rgg
The number of bits per symbol is “A”. The number of symbols per slot is “B”. While “C” represents
how many slots per TTI, “D” clarifies how many sub-carriers per RB. Table 1 summarizes the
mapping between SNR values and their associated data rates.
Table 1. Mapping between instantaneous downlink SNR and data rate
Minimum SNR Modulation and Data Rate Level (dB) coding (Kbps) 1.7 QPSK (1/2) 168 3.7 QPSK (2/3) 224 4.5 QPSK (3/4) 252 7.2 16 QAM (1/2) 336 9.5 16 QAM (2/3) 448 10.7 16 QAM (3/4) 504 14.8 64 QAM (2/3) 672 16.1 64 QAM (3/4) 756
Upon the packets reach the eNB, they are buffered in eNB in a specific container allocated for each
active UE. Moreover, the buffered packets are assigned a time stamp to ensure that they will be
scheduled or dropped before the scheduling time interval is expired, and then using First-In-First-Out
(FIFO) method they are transmitted to the users in the downlink direction. To explain the scheduling
operation, PS manager (is a part of eNB functionalities) at each TTI priorities and classifies the
arriving users’ packets according to preconfigured scheduling algorithm.
Scheduling decision is made based on different scheduling criteria that have been used in various
algorithms. For example channel condition, service type, Head-of-Line (HOL) packet delay, buffer
status, and so on so forth. One or more RBs could be allocated to the selected user for transmission
with the highest priority. Figure 2 shows the packet scheduler in the downlink direction at eNB.
International Journal of Wireless & Mobile Networks (IJWMN) Vol. 6, No. 5, October 2014
112
Figure.2 Downlink Packet Scheduler of the 3GPP LTE System [10]
3. PACKET SCHEDULLING ALGORITHMS
The efficient radio resource utilization and ensuring fairness among connected users, as well as
satisfying QoS requirements, are the main purposes of using PS algorithms [11].The PS algorithms
that have been used in this study are : Proportional Fair (PF) algorithm, Maximum-Largest Weighted
Delay First (MLWDF or ML) and the Exponential/Proportional Fair (EXP/PF or EXP) algorithm. It
should be noted that these algorithms are used.
3.1. Proportional Fair (PF) Algorithm
For non-real time traffic, the PF was proposed which is used in a Code Division Multiple Access-
High Data Rate (CDMA-HDR) system in order to support Non-Real Time (NRT) traffic. In this
algorithm, the trade-off between fairness among users and the total system throughput is presented.
This is, before allocating RBs, it considers the conditions of the channel and the past data rate.
Any scheduled user in PF algorithm is assigned radio resources if it maximizes the metric k that
calculated as the ratio of reachable data rate of user i at time t and average data rate of the
same user at the same time interval t:
(2)
where;
(3)
is the window size used to update the past data rates values in which the PF algorithm maximizes
the fairness and throughput for any scheduled user. Unless user i is selected for transmission
at , = 0.
International Journal of Wireless & Mobile Networks (IJWMN) Vol. 6, No. 5, October 2014
113
3.2. Maximum Largest Weighted Delay First (MLWDF) Algorithm
If the traffic is a Real Time (RT), the MLWDF is introduced which is used in CDMA-HDR system in
order to support RT data users [11].It is more complex algorithms compare with PF and is used in
different QoS user’s requirements. This is because it takes into account variations of the channel
when assigning RBs. Moreover, if a video traffic scenario, it takes into consideration time delay. Any
user in MLWDF is granted RBs if it maximizes the equation below:
(4)
where;
(5)
where is a difference in time between current and arrival times of the packet that known as the
Head Of Line (HOL) packet delay of user i at time t.
Similarly to PF equation, while the achievable data rate of user i at time t is , the average data
rate of the same user at the same time interval t is . and are the delay threshold for a
packet of user i and the maximum HOL packet delay probability of user i respectively. The later is
considered to exceed the delay threshold of user i.
3.3. Exponential/Proportional Fair (EXP/PF) Algorithm
Since PF is not designed for multimedia applications (only for NRT traffic), an enhanced PF called
EXP/PF algorithm was proposed in the Adaptive Modulation and Coding and Time Division
Multiplexing (AMC/TDM) systems. The EXP/PF algorithm is designed for NRT service or RT
service (different sorts of services). The metric is used for both RT nad Non-RT in which RBs are
assigned to users based on .
(6)
where,
(7)
(8)
where the average number of packets at the buffer of the eNB at time t is represented by , k and
in equation (8) are constants, is explained in MLWDF, is the HOL packets delay of
RT service and is the maximum delay of RT service users. The EXP/PF differentiates between
RT and NRT by prioritizing RT traffic users over the NRT traffic users if their HOL values are
reaching the delay threshold.
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4. SIMULATION ENVIRONMENT
LTE-Sim simulator is used in this paper to do the entire analysis and study [12]. The most recent
version of LTE-Sim (version 5) has not involved yet any code regarding the HetNets type (Macro with
Pico cells). The developed code used in this paper could be considered as an enhancement of the
released LTE-Sim versions. However, LTE-Sim has a detailed code (or what authors are named it:
scenario) which can be used to simulate and examine HetNets type (Macro with Femto). Our paper is
based on a scenario of a single Macro cell with 2 small Pico cells that are reduced their powers. More
Picos can be added to the system, and enhanced system behaviour will be presented. However,
according to [2], while the number of Pico cells is increased, more inter-cell interference is
experienced since the same carrier frequency is used in each cell (Macro and Picos).
Figure 3 shows the entire system that is used in this paper: Macro cell of 1 km and 2 Pico cells of 0.1
km located on the Macro edge. This design is chosen to analog a real system aimed to cover larger
area and more users, especially the users in the cell edge where they suffer from lack of connectivity
with Macro cell. The inter-cell interference is modeled. Video and VoIP traffic are used to represent
user’s data. Each user has 50 % Video traffic and 50% VoIP flows.
Handover is activated. Each cell starts a certain number of users. Non-uniform user distribution
within the cells is applied and 3km/h constant speed is utilized as the mobility user speed. In
addition, the 3GPP urban Macro cell propagation loss model has been implemented including path-loss,
penetration loss, multi-path loss and shadow fading which are summarized below [13]:
Pathloss: , d refers the distance between the eNB and the user in
kilometers.
Penetration loss: 10 dB
Multipath loss: using one of the well-known methods called Jakes model
Shadow fading loss (recently it could be used as a gain in LTE-A): log-normal distribution
- Mean value of 0 dB.
- Standard deviation of 10 dB.
Figure.3 Applied HetNets (Macro with 2 Picos)
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Packets throughput (see equation 9), Packet Loss Ratio (PLR) as shown in equation 10, packet delay
(latency) and fairness index (equation 11) are the concepts used in the aforementioned algorithms to
evaluate the system performance. Jain’s method is applied to implement fairness among users [14].
According to [1], fairness should reach the value of 1 to be considered as a fair algorithm that sharing
the resources suitably among users. It can be calculated as value 1 minus the value of the difference
between the maximum and minimum size of transmitted packets of the most and least scheduled
users. Equation (11) calculates the fairness value.
(11)
Obviously, while is the size of transmitted packets, is the size discarded
or lost packets during the connection. is the summation of all arrived packets that are buffered
into serving eNB [1].
The aforementioned total size of transmitted packets of the best served UE and the worse served UE
are represented in equation (11) as and .
Table 2 shows the entire system simulation parameters [1].
Table 2. LTE system simulation parameters
Parameters
Simulation time
Flow duration
30 s
20 s
Slot duration
TTI
Number of OFDM symbols/slot
Macro cell radius
Macro eNB Power
Pico cell radius
Pico eNB Power
0.5 ms
1 ms
7
1 km
49 dBm
0.1 km
30 dBm
User speed 3 km/h
VoIP bit rate 8.4 kbps
Video bit rate 242 kbps
Frame structure type FDD
Bandwidth 10 MHz
Number of RBs 50
Number of subcarriers 600
Number of subcarriers/RB 12
Subcarrier spacing 15 KHz
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In order to get better results and to confirm the outcomes, five simulations have been conducted for
each algorithm (PF, MLWDF and EXP) in each point of users (10, 20, 30, 40, 50, 60, 70 and 80).
This yields 120 simulations outcomes. The average values have been taken to draw the simulation
graphs at each point of users.
5. SIMULATION RESULTS
The average overall system throughput is shown in figure 4. Comparing the throughput for “single
Macro cell” for the same simulation parameters as shown in figure 5, the pico cells in the scenario
“Macro with 2 Picos” boost the throughput by adding gain that shown as an overall system
throughput increment for the same number of users. For instance, at 40 users using MLWDF, the
throughput is 25 Mbps for the scenario with 2 Picos while the Macro scenario is only 9.3 Mbps. This
is almost a duple value. Further points show duple and triple throughput values in the scenario of 2
Picos. However, the gain will reach a saturation level where no more gain could be shown due to the
fact of limited radio resources availability while more users are added to the system. Although
MLWDF and EXP have almost similar behaviour in both scenarios, a higher throughput is shown in
the 2 Pico case using both algorithms. It could note that PF algorithm as shown figure 5 behaves
better than the scenario of single Macro cell. PF is developed for NRT traffic, but the simulation is
for Video flows (RT traffic); hence, the other simulated algorithms outperform PF.
PLR shown in the figure 6 according to [15] is the packet loss ratio for a single Macro cell. While the
system is charged with more than 20 users, the PLR is increased for all experienced algorithms
taking into consideration that the PF is the worst case with the video traffic. Adding two Picos to the
previous system to create “Macro with 2 Picos” scenario enhances the PLR while maintaining similar
system behavior for all algorithms. Approximately, the PLR in Macro with 2 Picos case is reduced to
be a quarter of PLR value of single Macro cell scenario. For example, at 70 users, MLWDF has 0.1
PLR value while for the same number of users MLWDF has 0.5 PLR value in the single Macro
scenario. Comparing between scheduling schemes, the worst case is the PF algorithm in both cases.
Figure 7 illustrates PLR for Macro with 2 Picos.
According to [15] and as shown in figure 8 , the delay in single Macro cell scenario is close to be
constant for PF, MLWDF and EXP/PF with value less than 5 ms while it suffers from rapid
increasing after 40 users for PF algorithm. If two Pico cells are added to the aforementioned system,
a similar performance is shown, but the delay value is decreased. In addition, the threshold of PF is
shifted at 60 users instead of 40 users in the single Macro case. To compare MLWDF and EXP/PF in
both scenarios, a certain point in figures 8 and 9 could be explained. For example at 60 users, in a
single Macro cell the delay value is 50 ms while in the Macro with 2 Picos the value is 20 ms. As a
consequence, for MLWDF and EXP/PF, the delay value with two Picos is approximately half the
delay value without Pico cells. One of the purposes of HetNets is to enhance the latency, and this is
shown in a practical simulation illustrated in figure 9. However, the delay shows lower values (nearly
10 times lower) in the scenario of single cell with 2 Picos using PF scheme.
When the number of users increases in single Macro cell more than 30, the fairness index of all
simulated algorithms is deviated down of the value “1”. At 40 users, PF shows further deviation
close to value 0.8 compare with other algorithms which they are around 0.9. The fairness index
behaves similarly in the scenario of Macro with 2 Picos as shown in figure 11. However, the PF
shows a minor different in which at 50 users it starts to decline to get the value 0.8.
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5.1. Throughput
Figure.4 Average System Throughput (Macro with 2 Picos)
Figure.5 Average System Throughput (single Macro cell)
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5.2. Packet Loss Ratio (PLR)
Figure.6 PLR of Video Flows (single Macro cell) [15]
Figure.7 PLR of Video Flows (Macro with 2 Picos)
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5.3. Delay
Figure.8 Packet Delay of Video Flows (single Macro cell)
Figure.9 Packet Delay of Video Flows (Macro with 2 Picos)
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5.4. Fairness Index
Figure.10 Fairness Index of Video Flows [15]
Figure.11 Fairness Index of Video Flows Macro with 2 Picos
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6. CONCLUSION
This paper investigates scheduling algorithms that are developed to enhance the LTE network
performance by sharing radio resources fairly among users utilizing all available resources. These
algorithms depend on traffic class and number of users, hence; different outcomes are presented for
each algorithm. To further boost the overall system performance, this study uses heterogeneous
networks concept by adding small cells (2 Pico cells). This enhancement is experienced through a
throughput, PLR, delay and fairness. In the throughput the system gains more data rate while in PLR
the system suffers less packet loss values. Moreover, delay is decreased and fairness stays similar.
Approximately from the simulation outcomes, the overall system performance is as follows: throughput is
duplicated or nearly tripled relaying on the number of users, the PLR is almost quartered, the delay is reduced
10 times (PF case) and changed to be a half value (MLWDF/EXP cases), and the fairness stays closer to value
of 1. As a number of small cells increases, the system is expected to be more enhanced till a
saturation state is reached. The reason behind that is the inter-cell interference will limit the
performance since the same carrier frequency is used in all system’s cells. Focusing on macro with 2
Pico cells scenario, MLWDF shows the best performance for video flows followed by EXP/PF.
Further enhancement can be applied in future papers such as almost blank subframes (ABS),
enhanced inter-cell interference cancelation (eICIC) and cell range extension CRE concepts.
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Authors
Haider Al Kim got the B.Sc. in Information and Communication Engineering from Al-khwarizmi
Engineering College, University of Baghdad, Baghdad, Iraq in 2008. He pursues his Master degree in
Telecommunication Networks from University of Technology Sydney (UTS), Sydney, Australia in 2014
under the supervision A. Prof. Kumbesan Sandrasegaran. Working and research areas are Wireless
Telecommunication, Mobile Network, Network Management, Network Design and Implementation and
Data Analysis and Monitoring .He is senior network engineer with more than 5 years work experience in
networks and telecommunication industry at University of Kufa, Iraq. He is also a Cisco Certificate
holder (ID: CSCO11773718) and Cisco instructor at Al-Mansour College, Baghdad, Iraq in 2010-2011.
Alcatel-Lucent SAM certification holder, Alcatel University, Sydney Australia 2013.
Shouman Barua is a PhD research scholar at the University of Technology, Sydney. He received his
BSc in Electrical and Electronic Engineering from Chittagong University of Engineering and
Technology, Bangladesh and MSc in Information and Communication Engineering from Technische
Universität Darmstadt (Technical University of Darmstadt), Germany in 2006 and 2014 respectively. He
holds also more than five years extensive working experience in telecommunication sector in various
roles including network planning and operation.
Pantha Ghosal is a Graduate Research Assistant at University of Technology, Sydney. Prior to this, he
completed B.Sc in Electrical and Electronic Engineering from Rajshahi University of Engineering &
Technology, Bangladesh in 2007. He is an expert of Telecommunication network design and holds more
than 7 years of working experience in this area.
Dr Kumbesan Sandrasegaran is an Associate Professor at UTS and Centre for Real-Time Information
Networks (CRIN). He holds a PhD in Electrical Engineering from McGill University (Canada)(1994), a
Master of Science Degree in Telecommunication Engineering from Essex University (1988) and a
Bachelor of Science (Honours) Degree in Electrical Engineering (First Class) (1985). His current
research work focuses on two main areas (a) radio resource management in mobile networks, (b)
engineering of remote monitoring systems for novel applications with industry through the use of
embedded systems, sensors and communications systems. He has published over 100 refereed
publications and 20 consultancy reports spanning telecommunication and computing systems.
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