spectrum sharing in lte-a network operating in tv white ...meghnak/document/sharing_ppt.pdf · g....

$: Spectrum Sharing in LTE-A network operating in TV White ...meghnak/Document/sharing_ppt.pdf · G. Naik, S. Singhal, A. Kumar, and A. Karandikar, \Quantitative assessment of TV White$
Introduction Spectrum Sharing Problem Proposed Algorithm Performance Analysis Conclusion

Spectrum Sharing in LTE-A network operating in TVWhite Space

Meghna Khaturia, Sweety Suman, Abhay Karandikar and PrasannaChaporkar

Department of Electrical EngineeringIndian Institute of Technology Bombay.

February 27, 2018

Meghna Khaturia, IIT Bombay — NCC 2018 1/24


Outline

1 Introduction

2 Spectrum Sharing Problem

3 Proposed Algorithm

4 Performance Analysis

5 Conclusion



Outline

1 Introduction




5 Conclusion



Current Status of Broadband

52%1 of the global population is not using the Internet

In India, there are only 325 million2 broadband subscriptions in apopulation of 1.34 billion

Huge Rural-Urban divide in India2

1https://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2017.pdf

2http://www.trai.gov.in/sites/default/files/PIR_July_Sept_28122017.pdf


https://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2017.pdf

http://www.trai.gov.in/sites/default/files/PIR_July_Sept_28122017.pdf


Existing SolutionsLimitations

WiredConnectivity

Difficult toDeploy

Expensive

Distancelimitations

Cellular Systems

High CAPEXand OPEX

Low AverageRevenue perUser (ARPU)

Long DistanceWi-Fi

Strict LoSRequirement

EIRP Limits



Proposed SolutionTV UHF Band (470 - 585 MHz)

Good long distance propagation characteristics

Non Line of Sight (LoS) or Near-LoS connectivity

Highly underutilized in India3

Use of renewable energy is feasible

TV UHF Band

Low Energy

Large Coverage

Ease of Deployment

3G. Naik, S. Singhal, A. Kumar, and A. Karandikar, “Quantitative assessment of TV White Space in India,” in 2014

Twentieth National Conference on Communications (NCC), pp. 16, Feb 2014.



Outline

1 Introduction




5 Conclusion



Spectrum Sharing Problem

If multiple LTE-A middle mile networks are deployed, interferencebetween these networks will be a critical concern

Spectrum management is required to reduce the interference andoptimize the network performance



Spectrum Sharing ProblemSystem Model

1 Available TV UHF bandis divided into Morthogonal channels

2 Spectrum Managerallocates channels tooperators via GatewayController (GC)

3 Spectrum Managertreats all operatorsequally

Figure: Network Topology

CPE - Customer Premise Equipment

eNB - Evolved NodeB



Spectrum Sharing ProblemSystem Model

4 K eNBs deployeduniformly

5 Discuss spectrum sharingproblem with respect toan eNB irrespective ofthe operator

Figure: Network Topology

CPE - Customer Premise Equipment

eNB - Evolved NodeB



Spectrum Sharing ProblemNotations

Channel Allocation Matrix (A): We define channel allocationmatrix as A = {ak,m|ak,m ∈ {0, 1}}KxM such that

ak,m =

{1, if channel m is assigned to eNBk ,

0, otherwise.

Mode Allocation Matrix (B): B = {bk,m|bk,m ∈ {0, 1}}KxM is aK by M binary matrix.

bk,m =

{1, if allocated channel ak,m is to be shared ,

0, otherwise.

Jain Fairness Index (F):

F =

(K∑

k=1

Tk(A,B)

)2

K ×K∑

k=1

Tk(A,B)2.



Spectrum Sharing ProblemProblem Formulation

Maximize system throughput subject to fairness constraint

(A?,B?) = arg maxA,B

(K∑

k=1

Tk(A,B)

),

subject to F > δ

where A = Channel Allocation Matrix,

B = Mode Allocation Matrix,

F = Fairness Index,

δ = Constrained value of fairness.

* This is a combinatorial problem which is known to be NP-complete.



Outline

1 Introduction




5 Conclusion



Graphical Model of Network

1 System can be modeled as graph, G (V ,E )V := Set of all the vertices i.e. eNBs deployed in the given areaE := Set of edges between eNBs i.e. an edge between any twovertices implies that vertices are interfering with each other

2 Protocol Interference ModeleNBs interfere with each other if distance between them is less thandthreshold

1

2

4

3

5



Fairness Constrained Channel Allocation

1 Input : Graph, G

2 Sub-Algorithms :1 Multiple Dedicated Channel Allocation (MDCA):

Multiple dedicated channels are assigned to an eNB

2 One Dedicated Rest Shared Channel Allocation (ODRS-CA):

Single dedicated channel is assigned to each eNBChannels which are not assigned to the neighbors are assigned asshared channel

3 Pick that output for which fairness is greater than δ

4 If fairness is greater than δ for both sub-algorithm, then select theoutput which has better throughput

5 Output : Allocation matrices (A,B)



Illustrative example of FCCA

Figure: MDCA

1{1 4}

2 {2}

3 {3}

Figure: ODRS-CA

1{1 4}

2 {2 4}

3 {3 4}

Better system fairness in ODRS-CA than in MDCA



Illustrative example of FCCA

Figure: MDCA

1{1 3}

2 {2 4}

3 {1 3}

Figure: ODRS-CA

1{1 3 4}

2 {2 3 4}

3 {1 3 4}

Better system throughput in MDCA than in ODRS-CA



Outline

1 Introduction




5 Conclusion



Performance AnalysisScenario Description

1 eNBs deployeduniformly at random

2 10 CPEs distributeduniformly within eachcell

3 Saturated downlinktraffic for each CPE

4 Divide bandwidth into4 orthogonal channels

Figure: Network topology in100 km2 area

0

2000

4000

6000

8000

10000

0 2000 4000 6000 8000 10000

Y C

oord

inate

s

X Coordinates

eNB

1

2

3

4

CPE



Performance AnalysisSimulation Parameters

Parameters Values

Frequency Band 500-520 MHzTransmit Power (Pt) 18 dBmReceiver Sensitivity (RS) −101 dBmCable Loss (CL) 2 dBReceiver Noise Figure (NF ) 7 dBTransmitter Antenna Gain (Gt) 10 dBReceiver Antenna Gain (Gr ) 0 dBTransmitter Antenna Height (ht) 30 mReceiver Antenna Height (hr ) 5 mSlot Time 9 µsTransmit Opportunity (TxOp) 10 msDetection Threshold −62 dBmSimulation Time 1 s



Performance AnalysisSimulation Results

Figure: (a) Spectral EfficiencyFigure: (b) Average SystemThroughput

Comparative analysis of spectral efficiency and system throughput vs.number of eNBs deployed in 100 km2 area



Performance AnalysisSimulation Results

Figure: (c) Jain’s Fairness Index

Variation of fairness index with increasing number of eNBs deployed in100 km2 area



Outline

1 Introduction




5 Conclusion



Conclusions

1 Conclusions

FCCA performs better than other coexistence mechanismsAchieves fairness index of 0.75 even in case of dense deployment(10 eNBs/100 km2)

2 Future Work

Different throughput requirement at different eNBsDifferent weights to different operatorsNon co-operative spectrum sharing among operators
