Collecting correlated information from a sensor network
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Lower bounds for asymmetric communication channels and distributed source coding
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Approaching the Slepian-Wolf boundary using practical channel codes
Signal Processing - Special section: Distributed source coding
A general and optimal framework to achieve the entire rate region for Slepian-Wolf coding
Signal Processing - Special section: Distributed source coding
An energy-efficient adaptive DSC scheme for wireless sensor networks
Signal Processing
An efficient SF-ISF approach for the Slepian-wolf source coding problem
EURASIP Journal on Applied Signal Processing
Symmetric distributed coding of stereo omnidirectional images
Image Communication
IEEE Transactions on Image Processing
Error resilient non-asymmetric Slepian-Wolf coding
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Heegard-Berger video coding using LMMSE estimator
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
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A Slepian-Wolf coding scheme that can achieve arbitrary rate allocation amongtwo encoders was outlined in the work of Pradhan and Ramchandran. Inspired by thiswork, we start with a detailed solution for general (asymmetric or symmetric) Slepian-Wolfcoding based on partitioning a single systematic channel code, and continuewith practical code designs using advanced channel codes. By using systematic IRAand turbo codes, we devise a powerful scheme that is capable of approaching any pointon the Slepian-Wolf bound. We further study an extension of the technique to multiplesources, and show that for a particular correlation model among the sources, a singlepractical channel code can be designed for coding all the sources in symmetric andasymmetric scenarios. If the code approaches the capacity of the channel that modelsthe correlation between the sources, then the system will approach the Slepian-Wolflimit. Using systematic IRA and punctured turbo codes for coding two binary sources,each being independent identically distributed, with correlation modeled by a binarysymmetric channel, we obtain results which are 0.04 bits away from the theoreticallimit in both symmetric and asymmetric Slepian-Wolf settings.