DCC '03 Proceedings of the Conference on Data Compression
Compression with Side Information Using Turbo Codes
DCC '02 Proceedings of the Data Compression Conference
Design of Slepian-Wolf Codes by Channel Code Partitioning
DCC '04 Proceedings of the Conference on Data Compression
DCC '04 Proceedings of the Conference on Data Compression
Slepian-Wolf Coding for Nonuniform Sources Using Turbo Codes
DCC '04 Proceedings of the Conference on Data Compression
Serial concatenation of interleaved codes: performance analysis, design, and iterative decoding
IEEE Transactions on Information Theory
Nested linear/lattice codes for structured multiterminal binning
IEEE Transactions on Information Theory
Distributed source coding using syndromes (DISCUS): design and construction
IEEE Transactions on Information Theory
A general and optimal framework to achieve the entire rate region for Slepian-Wolf coding
Signal Processing - Special section: Distributed source coding
Distributed source coding using raptor codes for hidden Markov sources
IEEE Transactions on Signal Processing
Error resilient non-asymmetric Slepian-Wolf coding
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
On syndrome decoding for Slepian-Wolf coding based on convolutional and turbo codes
IEEE Communications Letters
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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 appears 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.