Adaptive pseudo-maximum likelihood data estimation algorithm

Abstract

A pseudo-maximum likelihood data estimator (PML) algorithm for discrete channels with finite memory in an additive white Gaussian noise environment is described. Unlike the traditional methods which utilizes Viterbi algorithm (VA) for data sequence estimation, the PML algorithm offers an alternative solution to the problem. The adaptive PML (APML) algorithm is then introduced which is suitable for time-variant channels. The performance of the APML-based algorithms are compared to that of the VA-based approaches for Rayleigh fading channels.