A Multi-modulus Blind Equalization Algorithm Based on Memetic Algorithm

Abstract

In view of slow convergence speed, large steady mean square error (MSE), and existing blind phase for the constant modulus blind equalization algorithm(CMA), a multi-modulus blind equalization algorithm based on memetic algorithm(MA-MMA) is proposed, which combines the basic idea of intelligent optimization algorithm and introduces the individual own evolution and social behavior among individuals to the blind equalization technology. In this proposed algorithm, the reciprocal of the cost function of multi-modulus blind equalization algorithm(MMA) is defined as the fitness function of the memetic algorithm(MA), the initial optimal weight vector of the MMA is optimized by using the global information sharing mechanism and local depth search ability of the MA. When the initial optimum weight vector of the MMA is obtained, the weight vector of the MMA may be updated. The simulation results with the higher-order APSK multi-modulus signals show that, compared with the CMA, the MMA, and the multi-modulus blind equalization algorithm based on genetic algorithm(GA-MMA), the proposed MA-MMA has the fastest convergence speed, smallest mean square error(MSE), and clearest output constellations.