Comparison of Convergence and BER Performance on LMS, RLS and NLMS in BPLC Systems

Adaptive equalization techniques compensate for time dispersion introduced by band limited or frequency selective communication channel and combat the resulting inter-symbol interference (ISI) effect. When signals are transmitted on broadband power-line (BPL) channel, they undergo severe distortions. Typically, adaptive equalizers used in digital communication systems like BPL systems require an initial training period, during which a known data sequence is transmitted. A replica of this sequence is made available at the receiver in proper synchronization with the transmitter, making it possible for adjustments to be made to the equalizer coefficients in accordance with the adaptive filtering algorithm. However, in this paper, three algorithms for adapting transversal filter coefficient were studied, to compare their adaptation rate and BER performance on BPL channel. It has been shown that normalized least mean square (NLMS) algorithm performs better with a rate of convergence of about 150 iterations with an approximate MSE value of 25dB and with an Eb/No of 13dB NLMS algorithm achieve a BER of 10-5 compared to least mean square (LMS) and recursive least square (RLS) having a BER of 510-5 and 10-2 respectively.