Cores of cooperative games in information theory
EURASIP Journal on Wireless Communications and Networking - Theory and Applications in Multiuser/Multiterminal Communications
Asynchronous Slepian-Wolf code design
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2
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
Distributed joint source-channel coding for functions over a multiple access channel
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Information-theoretically secret key generation for fading wireless channels
IEEE Transactions on Information Forensics and Security
Functional compression through graph coloring
IEEE Transactions on Information Theory
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This paper discusses the Slepian-Wolf problem of distributed near-lossless compression of correlated sources. We introduce practical new tools for communicating at all rates in the achievable region. The technique employs a simple "source-splitting" strategy that does not require common sources of randomness at the encoders and decoders. This approach allows for pipelined encoding and decoding so that the system operates with the complexity of a single user encoder and decoder. Moreover, when this splitting approach is used in conjunction with iterative decoding methods, it produces a significant simplification of the decoding process. We demonstrate this approach for synthetically generated data. Finally, we consider the Slepian-Wolf problem when linear codes are used as syndrome-formers and consider a linear programming relaxation to maximum-likelihood (ML) sequence decoding. We note that the fractional vertices of the relaxed polytope compete with the optimal solution in a manner analogous to that observed when the "min-sum" iterative decoding algorithm is applied. This relaxation exhibits the ML-certificate property: if an integral solution is found, it is the ML solution. For symmetric binary joint distributions, we show that selecting easily constructable "expander"-style low-density parity check codes (LDPCs) as syndrome-formers admits a positive error exponent and therefore provably good performance