Generalized Multi-modulus Blind Equalization Algorithm Based on Chaotic Artificial Fish Swarm Optimization

For improving the equalization performance of higher-order QAM signals, a generalized multi-modulus blind equalization algorithm based on chaos artificial fish swarm optimization is proposed. In this proposed algorithm, according to the prior information of higher-order QAM signal constellations, chaotic artificial fish swarm algorithm is fused to generalized multi-modulus blind equalization algorithm. Accordingly, the proposed algorithm uses rapid global optimum searching ability of chaotic artificial fish swarm algorithm (CAFSA) to initialize equalizer weight vector and adjusts adaptively modulus value of objective function in the equalizer vector iterations. The theoretical analyses and computer simulations indicate that the proposed algorithm outperforms generalized multi-modulus algorithm (GMMA) and artificial fish swarm algorithm based GMMA (AFSA-GMMA) in mean square error and convergence rate, which is more efficient for high-order QAM signals.