Distributed Arithmetic Coding for the Slepian-Wolf Problem

• Published in: IEEE transactions on signal processing Vol. 57; no. 6; pp. 2245 - 2257
• Main Authors: Grangetto, M., Magli, E., Olmo, G.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.06.2009; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Arithmetic; Arithmetic coding; Codes; Coding, codes; compression; Context modeling; Decoding; distributed source coding; Encoding; Entropy; Exact sciences and technology; Image coding; Information, signal and communications theory; LDPC codes; Miscellaneous; Parity check codes; Signal and communications theory; Signal processing; Slepian-Wolf coding; Source coding; Telecommunications and information theory; Turbo codes; Video coding; Wyner-Ziv coding; Performance evaluation; Source coding; turbo codes, Wyner―Ziv coding; Distributed source signal; Turbo code; Channel coding; Sequential decoding; LDPC codes; Slepian―Wolf coding; distributed source coding; Statistical model; Arithmetic code; Signal processing; Parity check codes; Error correcting code; Wyner Ziv problem; Open market; Arithmetic coding; compression
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2009.2014280

Distributed source coding schemes are typically based on the use of channels codes as source codes. In this paper we propose a new paradigm, named ldquodistributed arithmetic coding,rdquo which extends arithmetic codes to the distributed case employing sequential decoding aided by the side information. In particular, we introduce a distributed binary arithmetic coder for the Slepian-Wolf coding problem, along with a joint decoder. The proposed scheme can be applied to two sources in both the asymmetric mode, wherein one source acts as side information, and the symmetric mode, wherein both sources are coded with ambiguity, at any combination of achievable rates. Distributed arithmetic coding provides several advantages over existing Slepian-Wolf coders, especially good performance at small block lengths, and the ability to incorporate arbitrary source models in the encoding process, e.g., context-based statistical models, in much the same way as a classical arithmetic coder. We have compared the performance of distributed arithmetic coding with turbo codes and low-density parity-check codes, and found that the proposed approach is very competitive.