Symbol-based iterative decoding of convolutionally encoded multiple descriptions

C. F. Wu*, Wen-Whei Chang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)1868-1875
Number of pages8
JournalIET Communications
Volume6
Issue number13
DOIs
StatePublished - 5 Sep 2012

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