Optimizing Information Rate Bounds for Channels with Memory

Abstract

We consider the problem of optimizing information rate upper and lower bounds for communication channels with (possibly large) memory. A recently proposed auxiliary-channel-based technique allows one to efficiently compute upper and lower bounds on the information rate of such channels. Towards tightening these bounds, we propose iterative expectation-maximization (EM) type algorithms to optimize the parameters of the auxiliary finite-state machine channel (FSMC). From a channel coding perspective, optimizing the lower bound is related to increasing the achievable mismatched information rate, i.e. the information rate of a communication system where the maximum-likelihood decoder at the receiver is matched to the auxiliary channel and not to the true channel. We provide explicit solutions for optimizing the upper bound and the difference between the upper and the lower bound and we discuss a method for the optimization of the lower bound for data-controllable channels with memory. We discuss examples of channels with memory, for which application of the developed theory results in noticeably tighter information rate bounds. Show more