基于SA-GSO的小波加权多模盲均衡算法

为解决传统多模盲均衡算法（MMA）在均衡高阶QAM信号时存在的收敛速度慢、稳态误差大等问题,提出了一种基于模拟退火萤火虫优化的小波加权多模盲均衡算法（SA-GSO-WT-WMMA）。该算法在MMA的基础上增加了加权项,并引入了模拟退火萤火虫优化（SA-GSO）算法和正交小波变换（WT）,利用加权项自适应地调整算法中代价函数的模值,利用SA-GSO算法极强的全局寻优能力来优化均衡器的初始权向量,利用正交小波变换降低信号的自相关性,有效提高了均衡效果。水声信道仿真实验表明,该算法在降低稳态均方误差和加速收敛速度两方面表现卓越。

An Orthogonal Wavelet Transform Weighted Multi - Modulus Blind Equalization Algorithm Based on SA- GSO

When MMA （ Multi - modulus Algorithm） is used to equalize high - order QAM, it has many disadvan- tages, such as slow convergence rate, large mean square error, and so on. In order to overcome the problems, an orthogonal wavelet transform weighted muhi -modulus blind equalization algorithm based on simulated annea- ling optimization glowworm swarm algorithm （SA -GSO -WT- MMA） was proposed. In the proposed algo- rithm, the weighted item was increased to the traditional multi- modulus blind equalization algorithm （MMA）, and the simulated annealing glowwolan swarm optimization algorithm and the wavelet transform were also intro- duced in. The proposed algorithm can adjust the modulus value of the cost function value by using the weighted item, it can optimize the initial weight vector of the equalizer by using the strong global optimization ability of SA - GSO , and reduce the signal autocorrelation by using the de - correlation ability of WT. The results from com- puter simulation show that the proposed algorithm was excellence in improving the convergence rate and reducing the steady- state error.