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Joint source-channel decoding for variable-length encoded data by exact and approximate MAP sequence estimation
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DOI：10.1109/26.818865.png)
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Abstract
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Joint source-channel decoding based on residual source redundancy is an effective paradigm for error-resilient data compression. While previous work only considered fixed-rate systems, the extension of these techniques for variable-length encoded data was recently independently proposed by the authors and by Demir and Sayood. In this letter, we describe and compare the performance of a computationally complex exact maximum a posteriori (MAP) decoder, its efficient approximation, an alternative approximate decoder, and an improved version of this decoder suggested here. Moreover, we evaluate several source and channel coding configurations. The results show that our approximate MAP technique outperforms other approximate methods and provides substantial error protection to variable-length encoded data.
Keywords:
hidden Markov models
joint source-channel decoding
MAP estimation
residual redundancy
variable length codes
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