Modeling VoIP in Cognitive Radio Network  Students: Taly Sessler Ben Rubovitch Ben Rubovitch  Instructor: Boris Oklander  Semester: Winter 2010

Index 1.Introduction 1.1 VoIP 1.2 Cognitive Radio 1.2 Cognitive Radio 2.Project’s Goals 3. Model Description 4. Simulation design 5. Results 6.Conclusions 7.Summery

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

Introduction to VoIP Relevant 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.

clustering / dispersion → overflow / time-outs clustering / dispersion → overflow / time-outs Trade-offs management: Delay ↔ Loss 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 Sensing  Spectrum Analysis  Spectrum Decision Introduction to Cognitive Radio

Project Goals  Studying VoIP technology with emphasis on Oos aspects  Implementation of VoIP CRN Model using  Executing and Performance studying

E-model MOS Kλ Delay Loss T Delay Network conditions Delay Loss Codec characteristics Equipment impairment Loss robustness R-Factor jitter buffer codec jitter buffer controller Voice Quality Jitter Buffer Network & Codec System’s Model

E-model MOS R-Factor jitter buffer codec jitter buffer controller Voice Quality Jitter Buffer Network & Codec CRN System’s Model CRN

E-model MOS Kλ Delay Loss T Delay Network conditions Delay Loss Codec characteristics Equipment impairment Loss robustness R-Factor jitter buffer codec jitter buffer controller Voice Quality Jitter Buffer Network & Codec CRN 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 Design Inputs: M – number of channels C i (t) – state of i th channel i=1,2,…,M PU parameters α,β Simulation time Outputs: Channels(t) – state of channels

Channel State Simulator Design Change 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'); end End Change 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; end

Design Description using UML tools

Class Diagrams

Results

Results and Conclusions 1.Analytic - AJB 2.AR-1 – re-evaluation 3.AR-N – re-evaluation 4.Constant Delay Jitter Buffer Algorithm Types

C=0.1 MOS results (Network.type, participant.type, JBuffer.type) 4321 JBuffer participan t Networ k

C=2 MOS results (Network.type, participant.type, JBuffer.type) 4321 JBuffer participan t Network

C=5 MOS results (Network.type, participant.type, JBuffer.type) 4321 JBuffer participantNetwork

C=10 MOS results (Network.type, participant.type, JBuffer.type) 4321 JBuffer participan t Networ k

C=5, K=0.01, Network type=1 MOS results (Network.type, participant.type, JBuffer.type) 4321 JBuffer participa nt Networ k

C=50, K= MOS results (Network.type, participant.type, JBuffer.type) 4321 JBuffer participantNetwork

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