Title :
Symmetric Characterization of Finite State Markov Channels
Author :
Rezaeian, Mohammad
Author_Institution :
Dept. of Electr. & Electron. Eng., Melbourne Univ., Vic.
Abstract :
In this paper the symmetry property for discrete memoryless channels is generalized to finite state Markov channels. We show that for symmetric Markov channels the noise process can be characterized as a hidden Markov process, and the capacity of channel is related to the entropy rate of this process. These results elaborate the characterization of symmetry for Markov channels in previous narrations and extend the capacity formulae for symmetric discrete memoryless channel to symmetric Markov channels. Using recent formulation of entropy rate of hidden Markov process, this capacity formula is shown to be equivalent to the previous formulations which have been obtained for special cases of symmetric Markov channels
Keywords :
channel capacity; entropy; hidden Markov models; matrix algebra; channel capacity; discrete memoryless channels; entropy rate; finite state Markov channels; hidden Markov process; symmetric characterization; Australia; Channel capacity; Distributed computing; Entropy; Hidden Markov models; Markov processes; Memoryless systems; Probability distribution; Random variables; Tin;
Conference_Titel :
Information Theory, 2006 IEEE International Symposium on
Conference_Location :
Seattle, WA
Print_ISBN :
1-4244-0505-X
Electronic_ISBN :
1-4244-0504-1
DOI :
10.1109/ISIT.2006.261559