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An Efficient SF-ISF Approach for the Slepian-Wolf Source Coding Problem

Abstract

A simple but powerful scheme exploiting the binning concept for asymmetric lossless distributed source coding is proposed. The novelty in the proposed scheme is the introduction of a syndrome former (SF) in the source encoder and an inverse syndrome former (ISF) in the source decoder to efficiently exploit an existing linear channel code without the need to modify the code structure or the decoding strategy. For most channel codes, the construction of SF-ISF pairs is a light task. For parallelly and serially concatenated codes and particularly parallel and serial turbo codes where this appear less obvious, an efficient way for constructing linear complexity SF-ISF pairs is demonstrated. It is shown that the proposed SF-ISF approach is simple, provenly optimal, and generally applicable to any linear channel code. Simulation using conventional and asymmetric turbo codes demonstrates a compression rate that is only 0.06 bit/symbol from the theoretical limit, which is among the best results reported so far.

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Correspondence to Zhenyu Tu.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Tu, Z., Li (Tiffany), J. & Blum, R.S. An Efficient SF-ISF Approach for the Slepian-Wolf Source Coding Problem. EURASIP J. Adv. Signal Process. 2005, 542757 (2005). https://doi.org/10.1155/ASP.2005.961

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Keywords and phrases

  • distributed source coding
  • compression with side information at the decoder
  • Slepian-Wolf coding
  • code binning
  • serially concatenated convolutional codes
  • parallelly concatenated convolutional codes