A finite memory non stationary LMS algorithm for adaptive tracking Markovian time-varying channel

Author

Turki, M. ; Jaidane-Saidane, M.

Author_Institution

ENIT, LS Telecoms, Tunis, Tunisia

Volume

1

fYear

1998

fDate

1998

Firstpage

457

Abstract

This paper presents a new adaptive algorithm designed to track stochastic time-variations of channels that are characterized by P-order non stationarity Markov model. The proposed Finite Memory Non Stationary LMS (FM-NSLMS) algorithm, not only is able to identify the unknown order and parameters of the Markov model as the NSLMS but also takes into account the recursive nature induced by the non stationarity. The proposed FM-NSLMS performs better than the NSLMS since it has some memorization capability

Keywords

Markov processes; adaptive estimation; adaptive filters; filtering theory; least mean squares methods; parameter estimation; time-varying channels; tracking; Markovian time-varying channel; P-order non stationarity Markov model; adaptive algorithm; adaptive tracking; finite memory nonstationary LMS algorithm; memorization capability; stochastic time-variations; Adaptive algorithm; Algorithm design and analysis; Convergence; Filters; Least squares approximation; Recursive estimation; Statistics; Steady-state; Stochastic processes; Time-varying channels;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Circuits and Systems, 1998 IEEE International Conference on

Conference_Location

Lisboa

Print_ISBN

0-7803-5008-1

Type

conf

DOI

10.1109/ICECS.1998.813362

Filename

813362