The principle of per-survivor processing: a general approach to approximate and adaptive MLSE

A class of algorithms for maximum likelihood sequence estimation (MLSE) is introduced. These algorithms are based on the principle of performing signal processing (PPSP) operations, necessary for the estimation of unknown parameters, in a per-survivor fashion. Introduced by several authors for state complexity reduction in an ISI (intersymbol interference) environment, DDFSE (delayed decision feedback sequence estimation) and RSSE (reduced state sequence estimation) make use of this principle. A number of algorithms which apply the PPSP to combined sequence estimation and channel identification are presented. The results of the simulation analysis are given