改进狼群算法优化的小波常模盲均衡算法  

An Orthogonal Wavelet Transform Weighted Constant Modulus Blind Equalization Algorithm Based on Improved Wolf Pack Algorithm

作　　者：郑亚强[1] ZHENG Yaqiang(Electrical and Mechanical Department,Huainan Union University,Huainan 232001,China)

机构地区：[1]淮南联合大学机电系

出　　处：《安徽科技学院学报》2019年第5期65-70,共6页Journal of Anhui Science and Technology University

基　　金：安徽省教育厅自然科学研究重点项目(KJ2016A663)

摘　　要：针对常模盲均衡算法中因代价函数优化问题带来的收敛速度慢、稳态误差大等问题,本文提出一种新的盲均衡算法,即改进狼群算法优化的小波常模盲均衡算法。该算法改进了基本狼群算法的更新机制,提高狼群算法的全局寻优性能,将改进后的狼群算法代替传统的梯度思想最小化盲均衡算法中的代价函数,获取盲均衡器的最优初始权向量。仿真实验结果证明,新算法均衡效果更好,且收敛速度更快,稳态误差更小,星座图更加清晰。For the problem of slow convergence and large steady-state error caused by the cost function optimization problem in the wavelet norm blind equalization algorithm.In this paper,a new blind equalization algorithm,orthogonal wavelet transform weighted constant modulus blind equalization algorithm based on improved wolf pack algorithm is proposed.The new algorithm improves the update mechanism of the basic wolf group algorithm and improves the global optimization performance of the wolf group algorithm.The improved wolf group algorithm replaces the traditional gradient idea to minimize the cost function in the blind equalization algorithm,and obtains the optimal initial weight vector of the blind equalizer.As the simulation results have shown,the new algorithm has better equalization effect,faster convergence,smaller steady-state error,and clearer constellation map.

关 键 词：狼群算法 常模算法 盲均衡 小波变换 最优权向量 

分 类 号：TN911.5[电子电信—通信与信息系统]