Adaptive blind equalization for multi‐level QAM signals in impulsive noise environment

Abstract

A maximum correntropy criterion-blind clustering multi-modulus algorithm (MCC-BCMMA) is proposed to equalize multi-level quadrature amplitude modulation (QAM) channels in impulsive noise environment. The novel cost function is based on the maximum correntropy criterion (MCC), theoretical analysis shows that this criterion is useful when the noise is impulsive. Moreover, this cost function is decomposed into in-phase term and orthogonal term to eliminate the phase ambiguity, treats high-order QAM signal to classical QAM4 signal to reduce the error, and calculates the weight coefficients by a simple way. Simulation results show that the newly proposed algorithm MCC-BCMMA can be used to equalize multi-level QAM signals in both Gaussian and impulsive noise environments, and it shows better equalization performance under impulsive noise. The relationship between the kernel size of MCC, the convergence speed and accuracy is also analysed.

A Wireless Channel Equalization Method Based on Hybrid Whale Optimization: For Constant Modulus Blind Equalization System

“…It is still affected by the shortcomings of classical methods. Zhang et al [21] proposed a MMA based on the maximum correlation criterion. It proposed a method to calculate the weight coefficient, which reduces the computational complexity while maintaining the equalization effect.…”