Refined bounds on the empirical distribution of good channel codes via concentration inequalities

Maxim Raginsky, Igal Sason

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

Abstract

We derive sharpened inequalities on the empirical output distribution of good channel codes with deterministic encoders and with non-vanishing maximal probability of decoding error. These inequalities refine recent bounds of Polyanskiy and Verdú by identifying closed-form expressions for certain asymptotic terms, which facilitates their calculation for finite blocklengths. The analysis relies on concentration-of-measure inequalities, specifically on McDiarmid's method of bounded differences and its close ties to transportation inequalities for weighted Hamming metrics. An operational implication of the new bounds is addressed.

Original languageEnglish
Title of host publication2013 IEEE International Symposium on Information Theory, ISIT 2013
Pages221-225
Number of pages5
DOIs
StatePublished - 2013
Event2013 IEEE International Symposium on Information Theory, ISIT 2013 - Istanbul, Turkey
Duration: 7 Jul 201312 Jul 2013

Publication series

NameIEEE International Symposium on Information Theory - Proceedings

Conference

Conference2013 IEEE International Symposium on Information Theory, ISIT 2013
Country/TerritoryTurkey
CityIstanbul
Period7/07/1312/07/13

All Science Journal Classification (ASJC) codes

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

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