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Channel Equalization Using a Robust Recursive Least-Squares Adaptive-Filtering Algorithm

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1 Author(s)
Yang Wang ; Sch. of Aeronaut. & Astronaut., UESTC, Chengdu, China

Aimed at the existing shortcomings that robustness cannot be guaranteed for input-signals or desired-signals corrupted by impulsive noise and sudden system changes also cannot be successfully tracked in channel equalization using conventional algorithms, a new robust recursive least-squares (RLS) adaptive-filtering algorithm that uses a priori error-dependent weights is proposed. Robustness against impulsive noise is achieved by choosing the weights on the basis of the L1 norms of the cross-correlation vector and the input-signal autocorrelation matrix. Simulation results show that the proposed algorithm offers improved robustness as well as better tracking compared to the conventional RLS and the QN adaptation algorithms.

Published in:

Computer and Information Technology (CIT), 2012 IEEE 12th International Conference on

Date of Conference:

27-29 Oct. 2012

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