A note on convergence rate of constrained capacity estimation algorithms over ISI channels

Tolga M. Duman, Junshan Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

It has recently become popular to use simulation-based algorithms to empirically estimate achievable information rates over intersymbol interference (ISI) channels with inputs from specific input constellations. Such algorithms are guaranteed to converge by invoking the Shannon-McMillan-Brieman theorem provided that the output sequence is stationary and ergodic. In this note, we establish a central limit theorem result on the rate of convergence, and show that the variance of the estimates decreases like 1/N (where N is the sequence length employed) as N goes to infinity. This result indicates that it is possible to achieve estimation accuracy with any desired level by simply increasing the number of samples appropriately.

Original languageEnglish (US)
Title of host publication2008 Information Theory and Applications Workshop - Conference Proceedings, ITA
Pages66-69
Number of pages4
DOIs
StatePublished - Oct 6 2008
Event2008 Information Theory and Applications Workshop - ITA - San Diego, CA, United States
Duration: Jan 27 2008Feb 1 2008

Publication series

Name2008 Information Theory and Applications Workshop - Conference Proceedings, ITA

Other

Other2008 Information Theory and Applications Workshop - ITA
CountryUnited States
CitySan Diego, CA
Period1/27/082/1/08

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

Fingerprint Dive into the research topics of 'A note on convergence rate of constrained capacity estimation algorithms over ISI channels'. Together they form a unique fingerprint.

  • Cite this

    Duman, T. M., & Zhang, J. (2008). A note on convergence rate of constrained capacity estimation algorithms over ISI channels. In 2008 Information Theory and Applications Workshop - Conference Proceedings, ITA (pp. 66-69). [4601026] (2008 Information Theory and Applications Workshop - Conference Proceedings, ITA). https://doi.org/10.1109/ITA.2008.4601026