Concavity of Mutual Information Rate for Input-Restricted Finite-State Memoryless Channels at High SNR

Details Concavity of Mutual Information Rate for Input-Restricted Finite-State Memoryless Channels at High SNR Concavity of Mutual Information Rate for Input-Restricted Finite-State Memoryless Channels at High SNR

2010-07-27

arxiv.org/abs/1007.4604v1

Computer Science

Information Theory

26 pages

Scientific paper

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.

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