A Framework for Adaptive Voice A Framework for Adaptive Voice Communications Over Wireless ChannelsCommunications Over Wireless Channels

Sandeep K. S. Gupta and Suhaib A. ObeidatSandeep K. S. Gupta and Suhaib A. Obeidat

OutlineOutline

Problem Statement Motivation and approach Results and discussion Conclusions

MotivationMotivation

Voice is the most natural way for human comm.

Taking advantage of silence periods. Varying error channel conditions of a

wireless link Solution:

Changing the modulation scheme. Changing the voice coding rate.

Motivation-ContMotivation-Cont

SNR vs. BER for several modulation schemes [4].

Motivation-ContMotivation-Cont

Good Channel Condition: compressed voice at a rate of 16 kbps, denser modulation (QAM16).

Bad Channel Condition: uncompressed voice (64 kbps), and BPSK.

Motivation-ContMotivation-Cont

Number of Sources (Bad

State)

Number of Sources (Good

State)

Total Supported

4 0 4

3 8 11

2 16 18

1 24 25

0 32 32NS That can be accommodated when using adaptive modulationLink capacity: 256ksymbol

Motivation-ContMotivation-Cont

Number of Sources (Bad

State)

Number of Sources (Good

State)

Total Supported

4 0 4

3 4 7

2 8 10

1 12 13

0 16 16NS That can be accommodated when using adaptive encodingLink capacity: 256kbps

GoalGoal

Measuring the performance of adaptive voice over

a wireless connection and proposinga methodology of adaptation.

QoS requirements of voiceQoS requirements of voice

Delay Propagation delay (negligible) Queuing delay

Losses Channel Losses Buffer Losses

Current WorkCurrent Work Shenker compared strict versus

adaptive applications.o Rate-adaptive reacts better to

network congestion than other classes of adaptation (e.g., delay-adaptive)

Meo studied rate-adaptive voice comm. over IP networkso Supporting more voice

communications.

Adaptive modulation: reacting to channel conditions by changing the modulation scheme and the symbol rateo Motivated newer wireless devices to

support different modulation schemes.

FrameworkFramework

Source ConfigurationSource Configuration

Mux

Module

64 Kbps 64 Kbps

Src1

.

.

.

Src2

Src3

SrcN

Dest1

.

.

.

Dest2

Dest3

DestN

DeMux

Module

1.544 Mbps

T1 link

Voice Traffic ModelVoice Traffic Model Brady 2-state Markov

Model

On-off times for silence and speech

Exponential dist. for speech and silence states.

Speech activity 35.1%

352 ms on, 650 ms off

Wireless Channel ModelWireless Channel Model

Elliot-Gilbert Model Represents a Good

(G) and Bad (B) states.

G: 16 kbps, QAM16 B: 64 kbps, BPSK Pe(G) = 10-6

Pe(B) = 10-2

4s in B, 10s in G.

Packet Loss Ratio for Packet Loss Ratio for Adaptive vs. Non-adaptive ModulationAdaptive vs. Non-adaptive Modulation

Packet Loss Ratio = SentrOfPacketsTotalNumbe

rOfLossesTotalNumbe

Loss Components for Loss Components for Adaptive vs. Non-adaptive ModulationAdaptive vs. Non-adaptive Modulation

Buffer Loss Ratio = SentrOfPacketsTotalNumbe

fferLossesNumberOfBu

Channel Loss Ratio = SentrOfPacketsTotalNumbe

sannelLosseNumberOfCh

Packet Loss Ratio for Packet Loss Ratio for Adaptive vs. Non-adaptive EncodingAdaptive vs. Non-adaptive Encoding

Packet Loss Ratio = SentrOfPacketsTotalNumbe

rOfLossesTotalNumbe

Loss components for Loss components for Adaptive vs. Non-adaptive EncodingAdaptive vs. Non-adaptive Encoding

Ratio of Packets Delayed (80-ms Threshold) Ratio of Packets Delayed (80-ms Threshold) for Adaptive vs. Non-adaptive Modulationfor Adaptive vs. Non-adaptive Modulation

Delayed Packets Ratio = SentrOfPacketsTotalNumbe

msedcketsDelayNumberOfPa 80

DVQ for Adaptive vs. Non-adaptive DVQ for Adaptive vs. Non-adaptive Modulation + EncodingModulation + Encoding

Degradation of Voice Quality = SentrOfPacketsTotalNumbe

mslayedNumberOfDessesNumberOfLo 80

Future Work-Analytic ModelFuture Work-Analytic Model

• More generic

• Get more confidence.

• Can be used to quantify error control effect

• Can be used in any analysis involving Rayleigh channel and/or adaptive modulation.

ConclusionsConclusions

Adaptive voice allows for greater flexibility and more savings

Can support more voice communications.

Trading quality for monetary