Learning rate updating methods applied to adaptive fuzzy equalizers for broadband power line communications

Authors:
Moisés V. Ribeiro
Affiliations:
Department of Communications, State University of Campinas, São Paulo, Brazil
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2004

Citing 11
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Abstract

This paper introduces adaptive fuzzy equalizers with variable step size for broadband power line (PL) communications. Based on delta-bar-delta and local Lipschitz estimation updating rules, feedforward, and decision feedback approaches, we propose singleton and nonsingleton fuzzy equalizers with variable step size to cope with the intersymbol interference (ISI) effects of PL channels and the hardness of the impulse noises generated by appliances and nonlinear loads connected to low-voltage power grids. The computed results show that the convergence rates of the proposed equalizers are higher than the ones attained by the traditional adaptive fuzzy equalizers introduced by J. M. Mendel and his students. Additionally, some interesting BER curves reveal that the proposed techniques are efficient for mitigating the above-mentioned impairments.