Close category search window
 

Markov Processes Asymptotically Achieve the Capacity of Finite-State Intersymbol Interference Channels

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jiangxin Chen ; Prediction Co., UBS, Santa Fe, NM ; Siegel, P.H.

Recent progress in capacity evaluation has made it possible to compute a sequence of lower bounds on the capacity of a finite-state intersymbol-interference (ISI) channel by finding a sequence of optimized Markov input processes with increasing order , for which the state of the process is the previous input symbols. In this correspondence, we prove that, as the order goes to infinity, the sequence of optimized Markov sources asymptotically achieves the capacity of the channel. The conclusion is extended to two-dimensional finite-state ISI channels, the binary symmetric channel (BSC) with constrained inputs, and general indecomposable finite-state channels with a mild constraint.

Published in:
Information Theory, IEEE Transactions on  (Volume:54 ,  Issue: 3 )

Date of Publication: March 2008

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.