The Capacity of Finite-State Markov Channels With Feedback

Abstract

We consider a class of finite-state Markov channels with feedback. We first introduce a simplified equivalent channel model, and then construct the optimal stationary and nonstationary input processes that maximize the long-term directed mutual information. Furthermore, we give a sufficient condition under which the channel's Shannon capacity can be achieved by a stationary input process. The corresponding converse coding theorem and direct coding theorem are proved.