|Title:||Symbol-based iterative decoding of convolutionally encoded multiple descriptions|
|Authors:||Wu, C. -F.|
Chang, W. -W.
Institute of Communication Studies
|Abstract:||Transmission of convolutionally encoded multiple descriptions over noisy channels can benefit from the use of iterative source-channel decoding. The authors first modified the BCJR algorithm in a way that symbol a posteriori probabilities can be derived and used as extrinsic information to improve the iterative decoding between the source and channel decoders. The authors also formulate a recursive implementation for the source decoder that processes reliability information received on different channels and combines them with inter-description correlation to estimate the transmitted quantiser index. Simulation results are presented for two-channel scalar quantisation of Gauss-Markov sources which demonstrate the error-resilience capabilities of symbol-based iterative decoding.|
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