EFFICIENT VARIANTS OF SQUARE CONTOUR ALGORITHM FOR BLIND EQUALIZATION

Abstract

Adaptive equalizers remove signal distortion causing Inter-symbol Interference in bandlimited channels. The tap coefficients of these equalizers are time-varying and can be updated using several methods. When these do not include the transmission of a training sequence, it is referred to as blind equalization. Motivated by the radius-adjusted approach which is a method to achieve blind equalizer tap adaptation based on the equalizer output distance for Quadrature Amplitude Modulated (QAM) signals, static square contours are defined around an estimated symbol in a QAM constellation, which create regions that correspond to fixed step sizes and weighting factors. As a result, the equalizer tap adjustment consists of a linearly weighted sum of adaptation criteria that is scaled by a variable step size. This approach is the basis of two new algorithms: the Variable step size Square Contour Algorithm (VSCA) and the Variable step size Square Contour Decision-Directed Algorithm (VSDA). The proposed schemes are compared with existing blind equalization algorithms in the SCA family in terms of convergence speed, constellation eye opening and residual ISI suppression. Simulation results for 64-QAM signaling over empiricallyderived microwave radio channels confirm the efficacy of the proposed algorithms. A custom implementation of a blind adaptive equalizer based on the proposed schemes is presented. The system can be configured to operate in one error signal mode, VSCA, for square QAM signals up to 64-QAM. The simulations were carried out using the ModelSim 6.1f.