DocumentCode :
3850662
Title :
Feedback Capacity of a Class of Symmetric Finite-State Markov Channels
Author :
Nevroz Sen;Fady Alajaji;Serdar Yuksel
Author_Institution :
Department of Mathematics and Statistics, Queen´s University, Kingston, Canada
Volume :
57
Issue :
7
fYear :
2011
Firstpage :
4110
Lastpage :
4122
Abstract :
We consider the feedback capacity of a class of symmetric finite-state Markov channels. Here, symmetry (termed “quasi-symmetry”) is defined as a generalized version of the symmetry defined for discrete memoryless channels. The symmetry yields the existence of a hidden Markov noise process that depends on the channel´s state process and facilitates the channel description as a function of input and noise, where the function satisfies a desirable invertibility property. We show that feedback does not increase capacity for such class of finite-state channels and that both their nonfeedback and feedback capacities are achieved by an independent and uniformly distributed (i.u.d.) input. As a result, the channel capacity is explicitly given as a difference of output and noise entropy rates, where the output is driven by the i.u.d. input.
Keywords :
"Markov processes","Noise","Entropy","Symmetric matrices","Channel capacity","Hidden Markov models","Dynamic programming"
Journal_Title :
IEEE Transactions on Information Theory
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.2011.2146350
Filename :
5895050
Link To Document :
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