Channel decoding of systematically encoded unknown redundant sources

Erik Ordentlich, Gadiel Seroussi, Sergio Verdú, Krishnamurthy Viswanathan, Marcelo J. Weinberger, Tsachy Weissman

Research output: Contribution to journalConference articlepeer-review

15 Scopus citations


Practical decoders that take advantage of the source redundancy without requiring prior knowledge of the source statistics are designed. Discrete universal denoiser (DUDE)-enhanced decoders including, hard-denoising and decoding, soft-denoising and decoding, and iterative denoising and decoding, are considered. The results indicate that these decoders can provide substantial reductions in bit-error rates over conventional decoders that ignore redundancy in the source. The results involving Markov sources and repeat accumulate (RA) codes show that the proposed DUDE-enhanced belief propagation (BP) decoders closely track the performance of various source distribution dependent BP decoder structures.

Original languageEnglish (US)
Pages (from-to)165
Number of pages1
JournalIEEE International Symposium on Information Theory - Proceedings
StatePublished - 2004
EventProceedings - 2004 IEEE International Symposium on Information Theory - Chicago, IL, United States
Duration: Jun 27 2004Jul 2 2004

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics


Dive into the research topics of 'Channel decoding of systematically encoded unknown redundant sources'. Together they form a unique fingerprint.

Cite this