lte-planning

17 Informa Telecoms & Media

Fig. 7

Capacity limited Design

Coverage limited Design

18

Capacity Planning Principles

Informa Telecoms & Media

service area

Having established the performance capabilities of LTE and the vendor specific equipment the job of planning must then determine the capacity or coverage objectives. The objectives will of course vary from area to area depending on the planning criteria.


Fig. 8 area to be served

Land Use

Clutter Value

20



population Demographic

The marketing research carried out during the planning period will make use of the area classifications mentioned above and also the population demographics. Analysis of typical demographic data will allow the planner to determine the likely number of subscribers in a given location at different times of the day.

Population and population distribution are particularly important as this will give a base level for planning the capacity and coverage of the system. Other factors such as age, ethnicity, employment status will help the marketing researchers to determine the likely number of subscribers that can be captured.

Typical Demographic Data Presentation

n 10,000 or overn 7,500 9,999n 5,000 7,4999n 2,500 4,999n 2,499 or under

1 Islington 2 Tower Hamlets 3 Barking and Dagenham 4 Hammersmith and Fulham 5 Kensington and Chelsea 6 Westminster 7 City of London 8 Richmond upon Thames 9 Wandsworth 10 Lambeth 11 Southwark 12 Lewisham 13 Kingston upon Thames


Fig. 9

Other Demographic FactorsHousing Type

Land Use

Ethnicity

Age

Income

Disabilities

Mobility (in terms of travel time to work or number of vehicles available)

Educational attainment

Home ownership

Employment status

22



Marketing inputs

It is of critical importance that the planning process is carried out with input from the marketing department. Based on the demographic statistics the marketing researchers will be able to provide data regarding the total number of subscriber and the area over which they will be distributed, these are of course factors to be considered when designing the system.

Typical factors accounted for include:

Expected Service Take-up (penetration)Service Types Fully Mobile USB Dongle/PC cardExpected Level of Service Data throughput Contention Ratio

The service type, acceptable contention ratio and population penetration are most important for capacity planning.


Fig. 10 Marketing inputs to the planning process

Expected Service Take-up (penetration)

Service Types fully mobile USB dongle/PC card

Expected Level of Service data throughput contention ratio

24



Data throughput and Contention ratio

Data rates available to mobile subscriber have been increasing steadily over the last few years and will continue to do so, promoted by the additional capability of LTE. However the capacity of the radio sector is not unlimited and careful though must be applied to the type of service sold to the subscriber. Present systems may promise upto 7 or 10Mbps but rarely deliver due to radio condition or network overloading.

Of course the best way to manage the traffic load in the network is to support different service levels and mange the flow os data using QoS mechanisms. Most mobile systems currently in use do not use this approach, instead they may offer and upto service with best effort QoS on a flat rate data plan.

However the only effective way to manage traffic in data system is to discriminate at the subscriber and application level. This will be particularly important when planning for VoIP and other real time services.


Fig. 11 typical Mobile Data service Data rates

standard Family primary Use

radio tech

Downlink (Mbit/s)

Uplink (Mbit/s)

notes

lte UMTS/4GSM

General 4G OFDMA/MIMO/SC-FDMA

326.4 86.4 LTE-Advanced update to offer over 1 Gbit/s speeds.

UMts W-CDMa HsDpa+ HsUpa Hspa+

UMTS/3GSM

General 3G CDMA/FDD

CDMA/FDD/MIMO

0.38414.442

0.3845.7611.5

HSDPA widely deployed. Typical downlink rates today 2 Mbit/s, ~200 kbit/s uplink; HSPA+ downlink up to 42 Mbit/s.

UMts-tDD UMTS/3GSM

Mobile Internet

CDMA/TDD 16 16 Reported speeds according to IPWireless using 16QAM modulation similar to HSDPA+ HSUPA.

1xrtt CDMA2000 Mobile phone

CDMA 0.144 0.144 Succeeded by EV-DO.

eV-DO 1x rev.0 eV-DO 1x rev.a eV-DO rev.B

CDMA2000 Mobile Internet

CDMA/FDD 2.453.14.9xN

0.151.81.8xN

Rev B note: N is the number of 1.25 MHz chunks of spectrum used. Not yet deployed.

802.16 WiMAX Mobile Internet

MIMO-SOFDMA

3 3 WiMAX II IMT-Advanced update to offer over 1 Gbit/s speeds.

Flash-OFDM Flash-OFDM

Mobile internet mobility up to 200mph (350km/h)

Flash-OFDM

5.310.615.9

1.83.65.4

Mobile range 18miles (30km) extended range 34 miles (55km).

HiperMan HIPERMAN Mobile Internet

OFDM 56.9 56.9

iBurst iBurst 802.20

Mobile Internet

HC-SDMA/TDD/MIMO

64 64 3-12 km.

Wi-Fi Wi-Fi Mobile Internet

OFDM/MIMO/CDMA

108 108 Mobile range (3km).

26



Contention ratio

Contention ratio or oversubscription is a convenient way of reducing the overall capacity that has to be provided in the network. Fixed ISPs still over subscribe their broadband service at 20:1 or higher. This is fine for web browsing services but real time services may suffer. To support good quality real time services the contention ratio must be lowered to 10:1 or even 5:1.

This still assumes that for services like VoIP the connection provided is over subscribed. If voice quality is to be maintained to similar standard of circuit switched networks the ratios may have to be even lower, ideally 1:1.


Fig. 12 typical Contention ratios

service Category Oversubscription ratioWeb surfing 10:1 to 25:1

VoIP 5:1 to 10:1

Multicast/unicst video/audio services 1:1

Video conferencing 1:1 to 2:1

Internet gaming 5:1 to 10:1

28



Calculating required system Capacity

Determining the capacity of a cell or sector is one of the key objectives in planning. The demographic will provide much of the information required to work out the average data density based on the land use and expected population density and penetration.

For data services it is often difficult to establish the exact pattern of behaviour since some applications will operate automatically, not requiring human intervention, e.g. push services, peer to peer etc.

The traffic offered to the system may be expressed in volumes of data, Mb. How much data each user will offer to the system per second or per hour will need to be established in order to determine the total load during the busy period.

e.g. A mobile user is expected to transmit and receive up to 10Mb of data during the busy period. If there are 250 users in a sector, what is the total busy period capacity required in the sector assuming a 10:1 over subscription?

10Mb transmitted over 1 hour = 2777bits/s peak data demand = 2777bits/s x 250 users = 694.2Kbps

For laptop users this will be considerably higher.


Fig. 13 requirements for Calculating system Capacity

How many Subs accessing during the peak period

Traffic offered by each subscriber/class of subscriber

Overhead (Transport and Protocol)

Determine link utilisation

Which modelling tool to use? single channel multiple channels

e.g. A mobile user is expected to transmit and receive up to 10Mb of data during the busy period. If there are 250 users in a sector, what is the total busy period capacity required in the sector assuming a 10:1 over subscription?

10Mb transmitted over 1 hour = 2777bits/s

peak data demand = 2777bits/s x 250 users = 694.2Kbps

30



link Utilisation and system Delay

The utilisation of the link will directly affect the delay performance. The actual delay experienced will depend on factors such as the number channels and the queuing method used. For single channel systems the delay is directly proportional to the link utilisation. For systems with multiple channels the delay probability rises less quickly and can be said to be more stable at higher levels of average utilisation.

Link utilisation = Total offered traffic

Maximum link rate

100%

Singlechannel

Multiplechannel

Link utilisation 100%

Pro

b of

del

ay

e.g. = 87.5%14Mbps

16Mbps


Fig. 14

link Utilisation and system Delay

32



80%

Peak Profile A

Off-peak 20%

Utilisation

80%

Peak Profile B

Off-peak 70%

Utilisation


Fig. 14

average and peak Utilisation

34



service time

Another factor that creates delay in the system is the amount of time it takes to service the data requiring transmission. E.g. a 1Mb packet transmitted at 1Mbps would take 1 sec to transmit (ignoring other factors). The expression shown opposite is used to find the service time for the average packet size in the system. Sometimes know as serialisation time, it is one element in the overall delay experience by data passing through the system.

Service time is cumulative

Service time = Bits/PDU

Link rate


Fig. 15 service time

36



Capacity Models

Littles law, shown a the top of the opposite page assumes on channel to serve the data. Simple models like this allow the total time and number of packets in the systems very easily, since there are only a couple of factors that determine the outcome.

The multi-channel, multi-queue system shown below is more complex to work out. If there were a single queue, models like Erlang C could be used to determine the performance of the system, however when there are multiple queues which are managed with different priorities the overall out come is more difficult to manage.

In LTE there will be multiple queues and multiple, dynamic channels with which to service the data. The service type i.e. VoIP, web browsing etc may be take in to account as well as the subscriber priority when determining how and when to send the data packets.

Lq

Lq = .Tq Lw = .Tw Ls = .Ts

Tq

Lw Ls

Number in the queue/system

Number in the queue/system

Tw Tw

Channel

ChannelChannel Channel Channel


Fig. 16

littles law

erlang C

38



resource scheduling in lte

Resource Scheduling will play a very important part in the system performance of LTE. Give the dynamic nature of the 2 dimensional transmission resource i.e. time and frequency, the resource scheduler has many operational options to maintain through put for the UEs. The channel state and measurement of traffic capacity are used to inform the resource scheduler. The eNB may provide this information directly or feedback via signalling channels. The more feedback and information the scheduler has the more efficient the scheduling may be, however at the expense of signalling overhead.

There are several options for scheduling, the actual scheduling algorithm is vendor dependant.

Resource Scheduling Algorithms Ergodic Capacity (Shannon) Maximum Rate Proportional Fair Delay Limited Capacity

Ergodic capacity is the maximum rate which data can be sent over the channel with asymptotically small error rate.

Maximum rateUsing channel state information the scheduler will use the highest possible modulation scheme to maximise the through put for each user, this however creates an optimal throughput that takes no account of the delay requirement.

proportional FairWhen latency attributes are included in the QoS profile for an application fairer scheduling methods need to be considered. Proportional Fair will account for the latency requirement and schedule the user transmission when the instantaneous quality of the channel is higher than the average condition. Over long periods of time the Maximum Rate and Proportional Fair provide the same average throughput, however over short periods the proportional fair tends to a round robin scheduling.

Delay limitedSome application may have tighter constraints on delay than the proportional fair method can provide. In this case the throughput must be guaranteed under all channel conditions.

DL queue state information from RRC

Channel qualityinformation

DL dataqueuefor UE0

DL dataqueuefor UE1

DL dataqueuefor UEk

Traffic loadinformation for

UL transmission

Differentmodulation andcoding schemes

may be usedin the differentallocated RBs

Time

Freq

uenc

y

Scheduler function


Fig. 17 Wideband resource scheduling

Resource Scheduling Algorithms Ergodic Capacity (Shannon) Maximum Rate Proportional Fair Delay Limited Capacity

40



Capacity in spectrum limited or single Channel Deployments

Capacity dimensioning in LTE has additional problem encountered in spectrum limited deployments. UEs operating at the edge of the cell will encountered higher interference and therefore the though put is likely to suffer as the systems seeks to improve the quality by using more robust modulation and coding schemes, higher interference will also result in a greater number of HARQ retransmissions reducing the spectral efficiency of the channel.

C2C1

I1

I2

C1

Distance

I1

C2

Distance

I2

Pow

er

Pow

er

Impact of Increased Interference on Bit Rate

-10 -8 -6 -4 -2 0 2 4 6 8 100

10

20

30

40

50

60

70

80

90Rate loss (%)

(dB)


Fig. 18

increased interference at the Cell edge

impact of increased interference on Bit rate

42



Factional Frequency reuse

LTE uses the Reference Signals and Sounding RS to maintain a picture of the uplink and downlink channel quality across all the radio blocks, this information can be used to perform frequency domain scheduling.

At the edges of the cell the users will experience the maximum interference, LTE can use frequency domain scheduling to perform interference coordination. At its most extreme it is possible to build single frequency systems that automatically coordinate the interference at the edge of the cell. The eNBs are able to discuss the allocation of radio blocks of the extent of the potential interference directly with each other over the X2 interface.

X2 interface and interference Coordination

For downlink transmissions the eNBs can exchange a bitmap referred to as the Relative Narrowband Transmit Power (RNTP). This bit map can exchange between the eNB in the neighbour area to indicate if it is planning keep the transmit power for a particular radio block below an predetermined upper limit. This information enable the eNB to schedule resource taking into account the likely level of interference from the neighbouring cells.

Regarding the uplink there are two messages that may be exchanged. The Overload Indicator (OI) is exchanged to indicate the physical layer measurement of average uplink interference. Levels of low, medium and high can be expressed. Also a more pro-active indicator can be exchanged known as the High Interference Indicator (HII). This message informs the neighbouring eNB that it will be scheduling uplink transmissions from cell edge UEs at some time in the near future. The neighbour eNB may then account for this when performing their own cell edge scheduling.

Frequency

Pow

er

Frequency

Pow

er

Frequency

Pow

er

Frequency

Pow

er


Fig. 19

Fractional Frequency reuse

44



X2

X2X2


Fig. 19

interface and interference Coordination

X2 Interface; eNB exchanges signalling to assist with frequency domain resource scheduling

Overload Indicator Reactive low, medium, high (interference+noise)

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