MODIFICATION OF THE REFERENCE SIGNAL FOR FAST CONVERGENCE IN LMS-BASED ADAPTIVE EQUALIZERS

Abstract

In adaptive equalizers based on least mean squares (LMS) algorithms, the convergence rate is determined by the correlation matrix of an input signal. When the eigenvalue spread of the correlation matrix is close to unity, the convergence rate is quite fast. In this paper, or fast convergence of LMS-based adaptive equalizers we propose a modified reference signal pertinent to the given statistical channel. From the theoretical analysis and computer simulations, it is shown that the proposed modification method is quite effective for fast convergence of LMS-based adaptive equalizers.