Wyner's common information in Gaussian channels

Pengfei Yang, Biao Chen

Research output: Chapter in Book/Entry/PoemConference contribution

8 Scopus citations


This paper considers the computation of Wyner's common information between outputs of additive Gaussian channels with a common input. The work is motivated by recent generalization of Wyner's common information to continuous random variables and the associated lossy source coding interpretation, as well as its application to statistical inference. It is shown that with independent and identically distributed Gaussian noises, Wyner's common information between channel outputs is precisely the same as the mutual information between the source input and the channel outputs regardless of the source distribution. The result extends the previous result when the source distribution is Gaussian. Generalization to additive channels with correlated noises and its application to statistical estimation are also presented.

Original languageEnglish (US)
Title of host publication2014 IEEE International Symposium on Information Theory, ISIT 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Print)9781479951864
StatePublished - Jan 1 2014
Event2014 IEEE International Symposium on Information Theory, ISIT 2014 - Honolulu, HI, United States
Duration: Jun 29 2014Jul 4 2014

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095


Other2014 IEEE International Symposium on Information Theory, ISIT 2014
Country/TerritoryUnited States
CityHonolulu, HI

ASJC Scopus subject areas

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


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