Capacity, mutual information, and coding for finite-state Markov channels

  title={Capacity, mutual information, and coding for finite-state Markov channels},
  author={Andrea J. Goldsmith and Pravin Varaiya},
  journal={IEEE Trans. Information Theory},
The Finite-State Markov Channel (FSMC) is a discrete time-varying channel whose variation is determined by a finite-state Markov process. These channels have memory due to the Markov channel variation. We obtain the FSMC capacity as a function of the conditional channel state probability. We also show that for i.i.d. channel inputs, this conditional probability converges weakly, and the channel’s mutual information is then a closed-form continuous function of the input distribution. We next… CONTINUE READING
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