Blind equalization technique for cross correlation constant modulus algorithm (CC-CMA)

Abstract

Equalization plays an important role for the communication system receiver to correctly recover the symbol send by the transmitter, where the received signals may contain additive noise and intersymbol interference (ISI). Blind equalization is a technique of many equalization techniques at which the transmitted symbols over a communication channel can be recovered without the aid of training sequences, recently blind equalizers have a wide range of research interest since they do not require training sequence and extra bandwidth, but the main weaknesses of these approaches are their high computational complexity and slow adaptation, so different algorithms are presented to avoid this nature. The conventional Cross Correlation Constant Modulus Algorithm (CC-CMA) suffers from slow convergence rate corresponds to various transmission delays especially in wireless communication systems, which require higher speed and lower bandwidth. To overcome that, several adaptive algorithms with rapid convergence property are proposed based upon the cross-correlation and constant modulus (CC-CM) criterion, namely the recursive least squares (RLS) version of the CC-CMA (RLS-CC-CMA). This paper proposes a new blind equalization technique, the Exponential Weighted Step-size Recursive Cross Correlation CMA (EXP-RCC-CMA), which is based upon the Exponentially Weighted Step-size Recursive Least Squares (EXP-RLS) and the Recursive Cross Correlation CMA (RCC-CMA) methods, by introducing several assumptions to obtain higher convergence rate, minimum Mean Squared Error (MSE), and hence better receiver performance in digital system. Simulations studies show the rate of convergence, the mean square error (MSE), and the average error versus different signal-to-noise ratios (SNRs) with the other related blind algorithms.