On Syndrome Decoding for Slepian-Wolf Coding Based on Convolutional and Turbo Codes

Details On Syndrome Decoding for Slepian-Wolf Coding Based on Convolutional and Turbo Codes On Syndrome Decoding for Slepian-Wolf Coding Based on Convolutional and Turbo Codes

2009-12-04

arxiv.org/abs/0912.0797v3

IEEE Comm. Letters, vol. 14, no. 6, pp. 554-556, Jun. 2010

Computer Science

Information Theory

3 pages, 1 figure (2 graphic files arranged with subfigure); a note was added; to appear on IEEE Comm. Letters

Scientific paper

10.1109/LCOMM.2010.06.100283

In source coding, either with or without side information at the decoder, the ultimate performance can be achieved by means of random binning. Structured binning into cosets of performing channel codes has been successfully employed in practical applications. In this letter it is formally shown that various convolutional- and turbo-syndrome decoding algorithms proposed in literature lead in fact to the same estimate. An equivalent implementation is also delineated by directly tackling syndrome decoding as a maximum a posteriori probability problem and solving it by means of iterative message-passing. This solution takes advantage of the exact same structures and algorithms used by the conventional channel decoder for the code according to which the syndrome is formed.

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