Concavity of Mutual Information Rate for Input-Restricted Finite-State Memoryless Channels at High SNR
Information Theory
2010-07-28 v1 math.IT
Abstract
We consider a finite-state memoryless channel with i.i.d. channel state and the input Markov process supported on a mixing finite-type constraint. We discuss the asymptotic behavior of entropy rate of the output hidden Markov chain and deduce that the mutual information rate of such a channel is concave with respect to the parameters of the input Markov processes at high signal-to-noise ratio. In principle, the concavity result enables good numerical approximation of the maximum mutual information rate and capacity of such a channel.
Keywords
Cite
@article{arxiv.1007.4604,
title = {Concavity of Mutual Information Rate for Input-Restricted Finite-State Memoryless Channels at High SNR},
author = {Guangyue Han and Brian Marcus},
journal= {arXiv preprint arXiv:1007.4604},
year = {2010}
}
Comments
26 pages