Modeling burst channels using partitioned Fritchman's Markov models

Abstract

Discrete models based on functions of Markov chains (also referred to as hidden Markov models or finite-state channel (FSC) models) have been used to characterize the error process in communication channels with memory. One important property of these models is that the probability of any observed sequence can be expressed as a linear combination of the probability of a finite set of sequences of finite length, the so-called basis sequences. In this paper, we express the parameters of a class of FSC models as a simple function of the probability of the basis sequences. Based on this approach, we propose a new method for the parameterization of the Fritchman (1967) channel with single-error state as well as the interesting cases of Fritchman channels with more than one error state and the Gilbert-Elliott channel ((GEC) nonrenewal models). To illustrate the method, FSC models for the nonfrequency-selective Rician fading channel are presented. The number of states and the probability of state transitions are estimated for a given set of fading parameters.