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 efficient SF-ISF approach for the Slepian-wolf source coding problem
EURASIP Journal on Applied Signal Processing
Asynchronous Slepian-Wolf code design
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2
On the redundancy of Slepian--Wolf coding
IEEE Transactions on Information Theory
The equivalence between Slepian-Wolf coding and channel coding under density evolution
IEEE Transactions on Communications
LDPC code design for asynchronous Slepian-Wolf coding
IEEE Transactions on Communications
Adaptive Slepian-Wolf decoding using particle filtering based belief propagation
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Error resilient non-asymmetric Slepian-Wolf coding
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Distributed source coding with cyclic codes and their duals
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
Joint distributed compression and encryption of correlated data in sensor networks
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
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Slepian-Wolf coding tackles the problem of distributed encoding of correlateddiscrete-alphabet sources for decoding at a common receiver.In thiswork, we propose a distributed linear block code construction for attainingany point on the Slepian-Wolf achievable rate region for arbitrarily correlatedsources using only a single code.Specifically, our prescription allows for anyarbitrary memoryless joint probability distribution over any arbitrary numberof distributed sources, and allows for any arbitrary rate combination thatlies in the Slepian-Wolf achievable region.Special cases of our framework includethe single source case (wherein our construction reduces to an entropycoder), source coding with side-information at the receiver (so-called cornerpoints of the Slepian-Wolf region), and specific source correlation models (suchas induced by a virtual Binary Symmetric Channel model).In this work, wedescribe how to use Low Density Parity Check (LDPC) codes in the proposedframework to solve the general Slepian-Wolf problem constructively.