Modeling VoIP in Cognitive Radio Network

Students: Taly Sessler 038741401 Ben Rubovitch 065631475

Instructor: Boris OklanderSemester: Winter 2010

Index1. Introduction

1.1 VoIP 1.2 Cognitive Radio2. Project’s Goals3. Model Description4. Simulation design5. Results6. Conclusions7. Summery

Introduction to VoIP Voice over Internet Protocol- VoIP

is a general term for a family of transmission technologies for delivery of voice communications over IP networks such as the Internet or other packet-switched networks.

Flexibility - VoIP can facilitate tasks and provide services that may be more difficult to implement using the PSTN.Many telephone calls over a single channel.Secure calls using standardized protocols. Location independence. Integration with other Internet services.

Introduction to VoIPRelevant challenges

Quality of Service – the network cannot ensure that the data packets are delivered in sequential order, or provide Quality of Service (QoS) guarantees, VoIP implementations may face problems mitigating latency and jitter.

Delay Jitter - in the context of computer networks, the term jitter is often used as a measure of the variability over time of the packet latency across a network.

Jitter Buffer - Some systems use sophisticated delay-optimal de-jitter buffers that are capable of adapting the buffering delay to changing network jitter characteristics.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 180

1

2

3

4

5

6

7

8

9

10

11se

nded

/rece

ived

pac

kets

time (in packet units)

XX

sended packetsreceived packetsplayout time (a)playout time (b)

• clustering / dispersion → overflow / time-outs • Trade-offs management: Delay ↔ Loss

Introduction to VoIP

Cognitive Radio (CR) is a new wireless communication paradigm.

CR characteristics:Based on Software Defined Radio (SDR).CR is aware of its environment and use case.Spectrum SensingSpectrum AnalysisSpectrum Decision

Introduction to Cognitive Radio

Project Goals Studying VoIP technology with emphasis on

Oos aspects Implementation of VoIP CRN Model using

MATLAB@

Executing and Performance studying

E-model MOS

Kλ

Delay Loss

TDelay

Network conditions •Delay•Loss

Codec characteristics•Equipment impairment•Loss robustness

R-Factor

jitter bufferjitter

buffercodec codeccodec codec

jitter buffer controller

Voice Quality

Jitter Buffer

Network & Codec

System’s Model

E-model MOSR-Factor

jitter bufferjitter

buffercodec codeccodec codec

jitter buffer controller

Voice Quality

Jitter Buffer

Network & Codec

CRN System’s Model

CRN

E-model MOS

Kλ

Delay Loss

TDelay

Network conditions •Delay•Loss

Codec characteristics•Equipment impairment•Loss robustness

R-Factor

jitter bufferjitter

buffercodec codeccodec codec

jitter buffer controller

Voice Quality

Jitter Buffer

Network & CodecCRN System’s Model

C(t)

Spectrum opportunities

Network Simulator

Performance Studying

Scenarios generator

MOS

Channel State

Simulator

Adaptive Jitter

Buffer

Network simulator

Channel State Simulator DesignInputs:M – number of channelsCi(t) – state of ith channel i=1,2,…,MPU parameters α,βSimulation timeOutputs:Channels(t) – state of channels

Channel State Simulator DesignChange 1:for i = 1:Network.channel_set.M nst = find(Network.channels(i).times > slot(n),1)-1; network_state = network_state + Network.channels(i).state(nst); if isempty(network_state) error('1'); endEndChange 2:

if network_state == 0 Stream.TOA(id) = -1; else Stream.TOA(id) = Stream.TOC(id)+Session.T_packet*50/network_state; if Stream.TOA(id) < Stream.TOA(id-1) Stream.TOA(id) = Stream.TOA(id-1)+ Session.T_packet/10000; endend

Design Description using UML tools

Class Diagrams

ResultsCRN activity vs. time for =0.1=0.1

time [sec]

chan

nel n

o.

100 200 300 400 500

5

10

15

20

25

CRN activity vs. time for =0.5=0.1

time [sec]

chan

nel n

o.

100 200 300 400 500

5

10

15

20

25

1 log 1

1 log 1

on

off

rand

rand

1 log 1

1 log 1

on

off

rand

rand

1 log 1

1 log 1

on

off

rand

rand

Results and Conclusions

1. Analytic - AJB2. AR-1 – re-evaluation3. AR-N – re-evaluation4. Constant Delay

Jitter Buffer Algorithm Types

C=0.1MOS results (Network.type, participant.type, JBuffer.type)

4 3 2 1 JBuffer

4 3 2 1 4 3 2 1 4 3 2 1 4 3 2 1participan

tNetwor

k

1 0.8394

1 1 0.6791

0.9966

0.8764

0.6974

1 0.1156

1 1 0.7368

0.9966

0.9336

0.7741

1 0.9297

1 1 0.5441

1 0.8461

0.7289

1 0.1220

1 1 0.8547

0.9966

0.9217

0.8882

1 0.9397

1 1 0.6016

0.9966

0.8676

0.7378

1 0.1258

1 1 0.9262

0.9966

0.9371

0.91943

0.9685

0.9030

1 1 0.6480

0.9966

0.8395

0.6603

1 0.3177

1 0.9962

0.5041

0.9866

0.8170

0.57624

1 0.8762

1 1 0.5785

0.9966

0.8762

0.7173

0.9911

0.1224

1 0.9963

0.5793

0.9966

0.8795

0.66795

1 0.8561

1 1 0.5396

0.9966

0.8846

0.6104

1 0.1118

1 1 0.7433

1 0.900 0.72556

C=2MOS results (Network.type, participant.type, JBuffer.type)

4 3 2 1 JBuffer

4 3 2 1 4 3 2 1 4 3 2 1 4 3 2 1 participant Network

0.8250 0.9665 1 1 0.6484 0.9966 0.8815 0.7180 0.9919 0.1122 1 0.9961 0.6379 0.9933 0.8212 0.6752

1

0.9921 0.8762 1 1 0.5727 0.9966 0.9285 0.6902 1 0.1190 1 1 0.5801 0.9966 0.7668 0.6455

2

1 0.9163 1 1 0.5851 0.9966 0.8932 0.6792 1 0.1224 1 1 0.5212 0.9966 0.8367 0.6121

3

0.5052 0.9163 0.9907 0.6007 0.6218 0.7023 0.8562 0.6888 0.9557 0.1088 0.9890 0.9440 0.5840 0.9765 0.8407 0.6148

4

0.7247 0.9130 1 0.9589 0.4909 0.9966 0.8344 0.6628 1 0.1394 1 0.9925 0.4107 1 0.8325 0.5148

5

0.9193 0.9464 1 0.9962 0.5944 0.9966 0.8255 0.6703 1 0.1088 1 0.9925 0.3461 0.9966 0.7824 0.4794

6

C=5MOS results (Network.type, participant.type, JBuffer.type)

4 3 2 1 JBuffer

4 3 2 1 4 3 2 1 4 3 2 1 4 3 2 1 participant Network

0.7096 0.9832 1 0.7228 0.6969 0.9966 0.8516 0.7546 0.9842 0.1258 1 0.9890 0.6339 0.9933 0.8134 0.6194 1

0.8014 0.9397 1 0.9516 0.6260 0.9966 0.9203 0.6766 1 0.1190 1 0.9927 0.5619 0.9966 0.7934 0.6383 2

0.9401 0.9297 1 1 0.5833 0.9966 0.8857 0.6853 0.9922 0.1190 1 1 0.5579 0.9966 0.8711 0.6292 3

0.5740 0.4046 0.9411 0.6666 0.6771 0.1939 0.8791 0.6691 0.9015 0.1190 0.9611 0.9259 0.4818 0.9632 0.7951 0.6379 4

0.5785 0.7892 1 0.5677 0.6492 0.5819 0.8531 0.6259 0.9590 0.1224 1 0.9741 0.3851 0.9966 0.7583 0.5387 5

0.6718 0.9632 1 0.5413 0.5985 0.9966 0.8888 0.6642 0.9920 0.1190 0.9880 0.9962 0.4310 0.9966 0.7185 0.5613 6

C=10MOS results (Network.type, participant.type, JBuffer.type)

4 3 2 1 JBuffer

4 3 2 1 4 3 2 1 4 3 2 1 4 3 2 1 participant

Network

0.5862 0.8795

0.9954

0.9588

0.7142

0.3779

0.9219

0.7088

0.9568

0.1156

0.9786

0.9698

0.5934

0.9966

0.7151

0.6133 1

0.6750 0.9264

0.9945

0.7063

0.5714

0.9966

0.8914

0.6958

0.9770

0.1054

0.9717

0.9924

0.5121

0.9966

0.8494

0.6067 2

0.7457 0.7892

0.9941

0.9963

0.5752

0.9966

0.8911

0.6618

0.9918

0.1360

0.9940

0.9854

0.5087

0.9966

0.7951

0.5724 3

0.5615 0.2876

0.8325

0.6240

0.6511

0.0802

0.8487

0.6742

0.7460

0.0986

0.8571

0.8333

0.5630

0.9698

0.8405

0.6298 4

0.4062 0.7625

0.9953

0.5018

0.5169

0.2508

0.8826

0.6703

0.9473

0.1190

0.9664

0.9673

0.3984

0.9799

0.7337

0.4943 5

0.4112 0.9197

0.9611

0.5114

0.5804

0.3846

0.8971

0.6370

0.9606

0.1156

0.9942

0.9742

0.3529

0.9966

0.7751

0.4644 6

C=5, K=0.01, Network type=1

MOS results (Network.type, participant.type, JBuffer.type)

4 3 2 1 JBuffer

4 3 2 1 4 3 2 1 4 3 2 1 4 3 2 1 participant

Network

0.9285

0.800

0.8846

0.800

0.4230

0.7906

0.5263

0.5161

0.4250

0.4029

0.3230

0.4821

0.3252

0.3993

0.4193

0.2741 1

C=50, K=10-150MOS results (Network.type, participant.type, JBuffer.type)

4 3 2 1 JBuffer

4 3 2 1 4 3 2 1 4 3 2 1 4 3 2 1 participant Network

0.3307

0.0668

0.9004 0.5055 0.5238 0 0.8511 0.5858 0.6086 0.0307 0.6666 0.7397 0.2857 0.9832 0.7806 0.4963

1

0.3421

0.301 0.9766 0.5703 0.635 0 0.8232 0.6828 0.8018 0.0612 0.9651 0.8913 0.3423 0.9966 0.8391 0.4626

2

0.2941

0.2508

0.9759 0.7472 0.5658 0 0.8372 0.6629 0.7795 0.034 0.9681 0.854 0.2252 0.9966 0.8113 0.4501

3

0.32 0.2408

0.9521 0.5505 0.735 0 0.8723 0.7333 0.8449 0.0374 0.9605 0.8523 0.3875 0.9966 0.6982 0.4833

4

0.807 0.8695

0.9955 0.989 0.5913 0 0.7248 0.5526 0.9545 0.1084 0.9782 0.9779 0.8888 0.9966 0.895 0.8228

5

0.8217

0.9698

0.9951 0.9962 0.5203 0 0.7978 0.6397 0.9923 0.1224 0.9951 0.9923 0.7723 0.9966 0.9109 0.8339

6

Conclusions

- We can see that for each situation there is an algorithm that fits it, but there is no good algorithm for all Network and Participant types.

- The use of Algorithm will be done by the state of known factors in the Network and Participant with the use of the tables above

Summery

1. In this project we integrated a network simulation that fits better with realistic Network.

2. Upgraded the Jitter Buffer’s algorithm by dumping packets that came later then their successors and simulated a more realistic Time Of Arrival.

3. Generated a table that covers a vast variety of situations which the Jitter Buffer can choose an algorithm from