Efficient distributed source coding for multiple receivers via matrix sparsification

Chen Avin, Michael Borokhovich, Asaf Cohen, Zvi Lotker

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Consider the problem of source coding with side information in large networks with multiple receivers. In this case, standard coding techniques are either prohibitively complex to decode, or require source-network coding separation, resulting in sub-optimal transmission schemes. To alleviate this problem, we offer a joint network-source coding scheme based on matrix sparsification at the code design phase, which allows the terminals to use an efficient decoding procedure (syndrome decoding using LDPC), despite the network coding throughout the network. Via a novel relation between matrix sparsification and rate-distortion theory, we give lower and upper bounds on the best achievable sparsification performance, and analyze our scheme in the limit of weak side information at the receivers. Simulation results motivate the use of this scheme at non-limiting rates as well.

Original languageEnglish
Title of host publication2011 IEEE International Symposium on Information Theory Proceedings, ISIT 2011
Pages2045-2049
Number of pages5
DOIs
StatePublished - 26 Oct 2011
Event2011 IEEE International Symposium on Information Theory Proceedings, ISIT 2011 - St. Petersburg, Russian Federation
Duration: 31 Jul 20115 Aug 2011

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8104

Conference

Conference2011 IEEE International Symposium on Information Theory Proceedings, ISIT 2011
Country/TerritoryRussian Federation
CitySt. Petersburg
Period31/07/115/08/11

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