a framework for adaptive voice communications over wireless channels sandeep k. s. gupta and suhaib...
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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