Orthogonal Wavelet Transform Dynamic Weighted Multi-Modulus Blind Equalization Algorithm Based on Dynamic Particle Swarm

For improving the equalization performance of higher-order QAM signals, orthogonal Wavelet transform dynamic Weighted Multi-Modulus blind equalization Algorithm based on the Dynamic Particle Swarm Optimization(DPSO-WWMMA) is proposed. In this proposed algorithm, dynamic particle swarm optimization algorithm and orthogonal wavelet transform are introduced into dynamic Weighted Multi-Modulus blind equalization Algorithm(WMMA). Accordingly, the equalizer weight vector can be optimized by Dynamic Particle Swarm Optimization(DPSO) algorithm, the autocorrelation of the input signals can be reduced via using orthogonal wavelet transform, and the WMMA is used to choose appropriate error model to match QAM constellations. The theoretical analyses and computer simulations in underwater acoustic channels indicate that the proposed algorithm can obtain the fastest convergence rate and the smallest steady mean square error in equalizing high-order QAM signals. So, the proposed algorithm has important reference value in the underwater acoustic communications.