The Principle of Per-Survivor Processing (PPSP) constitutes a general framework for the approximation of Maximum Likelihood Sequence Estimation (MLSE) algorithms whenever the presence of unknown quantities prevents us from the realization of the classical Viterbi algorithm. The principle is based on the idea of embedding data-aided estimation techniques into the structure of the Viterbi algorithm itself. Several applications to adaptive MLSE and Reduced State Sequence Estimation (RSSE) are possible. Channel truncation techniques used in RSSE have a straightforward interpretation in terms of this principle. A number of algorithms for the simultaneous estimation of data sequence and unknown channel parameters are presented. Simulation results for these algorithms applied to certain InterSymbol Interference (ISI) channels indicate negligible performance degradation with respect to ideal MLSE.
The principle of per-survivor processing: a general approach to approximate and adaptive MLSE / Raheli, Riccardo; A., Polydoros; C. K., Tzou. - (1991), pp. 1170-1175. (Intervento presentato al convegno IEEE Global Commun. Conf. (GLOBECOM '91) tenutosi a Phoenix, Arizona, U.S.A. nel December 1991) [10.1109/GLOCOM.1991.188558].
The principle of per-survivor processing: a general approach to approximate and adaptive MLSE
RAHELI, Riccardo;
1991-01-01
Abstract
The Principle of Per-Survivor Processing (PPSP) constitutes a general framework for the approximation of Maximum Likelihood Sequence Estimation (MLSE) algorithms whenever the presence of unknown quantities prevents us from the realization of the classical Viterbi algorithm. The principle is based on the idea of embedding data-aided estimation techniques into the structure of the Viterbi algorithm itself. Several applications to adaptive MLSE and Reduced State Sequence Estimation (RSSE) are possible. Channel truncation techniques used in RSSE have a straightforward interpretation in terms of this principle. A number of algorithms for the simultaneous estimation of data sequence and unknown channel parameters are presented. Simulation results for these algorithms applied to certain InterSymbol Interference (ISI) channels indicate negligible performance degradation with respect to ideal MLSE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.