A unified MLSE detection technique for TDMA digital cellular radio

Abstract

A unified maximum-likelihood sequence estimation (MLSE) detection technique is proposed for time division multiple access (TDMA) digital cellular radio. In this technique, the probabilistic likelihood metrics are calculated from the joint conditional probabilities of all received sample sequences, including complex-valued, oversampled, and/or multichannel diversity sequences, provided that the sample statistics are independent. Based on the calculated metrics, the Viterbi algorithm is used to decide on the maximum-likelihood sequence. The same unified approach can be used to analyze the probability of error for MLSE detection. As an application, a receiver employing the proposed detection technique is constructed and its performance is analyzed and simulated according to the North American digital cellular standard. Simulation results verify the effectiveness of the proposed technique.