Zero-Error Codes for Correlated Information Sources
Proceedings of the 6th IMA International Conference on Cryptography and Coding
Distributed Source Coding Using Syndromes (DISCUS): Design and Construction
DCC '99 Proceedings of the Conference on Data Compression
Lossless and near-lossless source coding for multiple access networks
IEEE Transactions on Information Theory
On the interdependence of routing and data compression in multi-hop sensor networks
Proceedings of the 8th annual international conference on Mobile computing and networking
Data Compression of Correlated Non-Binary Sources Using Punctured Turbo Codes
DCC '02 Proceedings of the Data Compression Conference
Distributed coding of three binary and Gaussian correlated sources using punctured turbo codes
Signal Processing - Special section: Distributed source coding
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Abstract: A multiple access source code (MASC) is a source code designed for the following network configuration: a pair of correlated information sequences \{X_I\}^\infty_{I=1} and \{Y_I\}^\infty_{I=1} is drawn i.i.d. according to joint probability mass function (p.m.f.) p(x; y); the encoder for each source operates without knowledge of the other source; the decoder jointly decodes the encoded bit streams from both sources. The work of Slepian and Wolf describes all rates achievable by MASCs with arbitrarily small but non-zero error probabilities but does not address truly lossless coding or code design. In this paper, we consider practical code design for lossless and near lossless MASCs. We generalize the Huffman and arithmetic code design algorithms to attain the corresponding optimal MASC codes for arbitrary p.m.f. p(x; y). Experimental results comparing the optimal achievable rate region to the Slepian-Wolf region are included.