An Orthogonal Wavelet Blind Equalization Method Based on DNA Genetic Optimization

Abstract

The invention discloses an orthogonal wavelet transform constant modulus blind equalization algorithm based on optimization of the DAN genetic algorithm (DNA-GA-WTCMA). According to the algorithm, the DNA genetic algorithm is combined with the WTCMA and the advantages of the WT-CMA and the advantages of the DNA genetic algorithm are thoroughly utilized. According to the orthogonal wavelet transform constant modulus blind equalization algorithm, a weight vector of the blind equalization algorithm is shown according to a coding method based on a DNA nucleotide chain and interlace operation and mutation operation are conducted on the coded DNA chain to find an optimal individual in a DAN group, the decoded optimal individual serves as an optimal initial weight vector of a blind equalization device, and the shortages that the WTCMA is low in convergence rate, large in mean square error and prone to getting into local minimum are overcome. Compared with the WTCMA and the GA-WTCMA, the DNA-GA-WTCMA is the highest in convergence rate, the smallest in mean square error, globally optimal in performance and high in practical value in the communication technical field.

Description

technical field [0001] The invention belongs to the technical field of communication, and relates to a blind equalization method, in particular to a DNA genetic optimization-based orthogonal wavelet blind equalization method. Background technique [0002] In wireless communication, the distortion caused by the complex and changeable communication channel and the inter-symbol interference (Inter-Symbol Interference, ISI) caused by the limited bandwidth are the main factors affecting the communication quality. In order to improve the communication quality, it is necessary to adopt effective Channel equalization technology to eliminate the impact of intersymbol interference. Compared with the traditional adaptive equalization algorithm, the constant modulus algorithm (Constant Modulus Algorithm, CMA) greatly improves the bandwidth utilization because it does not need to send training sequences. However, for the traditional normal-mode blind equalization algorithm, its converge...

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Problems solved by technology

[0015] If the DNA genetic algorithm can be applied to the equalizer weight vector optimization of the blind equalization algorithm, it will help to avoid the premature convergence of the traditional genetic algorithm, thereby obtaining faster convergence speed and lower steady-state error, but in the prior art There is still a lack of application models combining DNA genetic algorithm and blind equalization algorithm

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