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

doi:10.3969/j.issn.1000-1093.2013.12.009

Abstract

Abstract: In order to improve the equalization performance of high-order quadrature amplitude modulation（QAM）signals, an orthogonal wavelet transform dynamic weighted multi-modulus blind equalization algorithm based on the dynamic particle swarm optimization (DPSO-WTDWMMA) is proposed. In the proposed algorithm, dynamic particle swarm optimization algorithm and orthogonal wavelet transform are applied to dynamic weighted multi-modulus blind equalization algorithm (DWMMA). Accordingly, the equalizer weight vector can be optimized by DPSO algorithm, the autocorrelation of the input signals can be reduced using orthogonal wavelet transform, and DWMMA is used to choose appropriate error models to match QAM signals. The theoretical analyses and computational simulations of underwater acoustic channels indicate that the proposed algorithm can be used to obtain the highest convergence rate and the smallest steady mean square error in the equalization of high-order QAM signals.

Key words: information processing, dynamic particle swarm optimization algorithm, orthogonal wavelet transform, weighted multi-modulus blind equalization, underwater acoustic communication

CLC Number:

TN911.2

HU Ling-ling， GUO Ye-cai. Orthogonal Wavelet Transform Dynamic Weighted Multi-modulus Blind Equalization Algorithm Based on Dynamic Particle Swarm[J]. Acta Armamentarii, 2013, 34(12): 1547-1554.

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