An Augmented Blind Channel Equalization Algorithm Reliant on Logarithmic Cost for M-QAM/M-PSK Signals

Abstract

The enhanced blind equalization technique for QAM/M-PSK signals, which are frequently employed in digital communication systems, is presented in this study. It is in accordance with the logarithmic cost function. In contrast to the two commonly used blind equalization techniques for QAM/M-PSK systems, the CMA (Constant Modulus Algorithm) and MCMA (Modified Constant Modulus Algorithm), The suggested approach can reduce steady state error and converge more quickly. When used in traditional equalization systems, CMA and MCMA show a significant steady-state mean square error and a very poor convergence speed. The proposed scheme uses a improved resilient back propagation with/ without weight backtracking based modeling which allows a simplification in weight adaption technique of the equalizer. Improved Logarithmic cost function based weight adaption has been incorporated which enhanced the suggested algorithm’s effectiveness. The simulation findings, the suggested approach outperforms the CMA and MCMA algorithms in terms of convergence rates and steady state error.