DNA Genetic Bat Algorithm Based Fractionally Spaced Multi-modulus Algorithm

doi:10.3969/j.issn.1000-1093.2015.08.018

Abstract

Abstract: For the low convergence speed and large mean square error (MSE) of the existing multi-modulus algorithms(MMAs), a DNA genetic bat algorithm based fractionally spaced multi-modulus algorithm(DNA-GBA-FS-MMA) is proposed. In this proposed algorithm, the fractionally spaced equalizer is used to get more detail channel information via oversampling signals. DNA genetic algorithm is introduced into bat algorithm to obtain a new intelligent optimization algorithm, called as DNA genetic bat algorithm (DNA-GBA), and DNA-GBA is used to find the global optimal position vector of the bat swarm serving as the real and imaginary parts of the initial weight vector of multi-modulus algorithm. Simulation results show that DNA-GBA-FS-MMA has the smallest MSE, the fastest convergence speed, and the clearest and most compact constellation points in comparison with the existing multi-modulus algorithms(MMAs).

Key words: information processing technology, fractionally spaced equalizer, multi-modulus algorithm, DNA genetic bat algorithm , global optimal position vector

CLC Number:

TN911.2

GUO Ye-cai, WU Hua-peng, WANG Hui, ZHANG Miao-qing. DNA Genetic Bat Algorithm Based Fractionally Spaced Multi-modulus Algorithm[J]. Acta Armamentarii, 2015, 36(8): 1502-1507.

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