LMS-RLS Joint adaptive equalization in wireless communication

Abstract

Equalization is a most widely used optimization scheme to reduce inter-symbol interference (ISI). Inter symbol interfering environment is a case of misrepresentation of the sent signal at the receiver. Different symbols can hinder with one another which results in noise and less relevant, reliable signal. Multipath propagation means a wireless signal from a spreader reaches the receiver through numerous paths. If inter symbol interfering occurs within an arrangement, it must be reduced to the most minimal quantity conceivable. The inter symbol interference is reduced through the use of adaptive algorithms; LMS (Least Mean Square Error) and RLS (Recursive Least Square) equalization procedures being the most prominent ones. In this work, a joint adaptive algorithm is proposed and simulated. A novel method involving both LMS and RLS is used for suppression of Inter symbol interference. The LMS has the benefit of a fast convergence rate but has a significant value of mean square error (MSE).However, the RLS complements it with low value of MSE and a slow convergence rate . Thus, a joint RLS and LMS is proposed The proposed method results in improved BER performance, lesser mean square error and a faster convergence.