Optimal Code Design for Lossless and Near Lossless Source Coding in Multiple Access Networks
DCC '01 Proceedings of the Data Compression Conference
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EURASIP Journal on Applied Signal Processing
Distributed arithmetic coding for the Slepian-Wolf problem
IEEE Transactions on Signal Processing
Distributed coding using punctured quasi-arithmetic codes for memory and memoryless sources
IEEE Transactions on Signal Processing
Distributed coding using punctured quasi-arithmetic codes for memory and memoryless sources
PCS'09 Proceedings of the 27th conference on Picture Coding Symposium
Functional compression through graph coloring
IEEE Transactions on Information Theory
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A multiple access source code (MASC) is a source code designed for the following network configuration: a pair of correlated information sequences {Xi}i=1∞ and {Yi}i=1∞ is drawn independent and identically distributed (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 of infinite coding dimension (n→∞) and asymptotically negligible error probabilities (Pe(n)→0). In this paper, we consider the properties of optimal instantaneous MASCs with finite coding dimension (ne(n)=0) and nearlossless (Pe(n)→0) performance. The interest in near-lossless codes is inspired by the discontinuity in the limiting rate region at Pe(n)=0 and the resulting performance benefits achievable by using near-lossless MASCs as entropy codes within lossy MASCs. Our central results include generalizations of Huffman and arithmetic codes to the MASC framework for arbitrary p(x,y), n, and Pe(n) and polynomial-time design algorithms that approximate these optimal solutions.