用于非线性均衡的一种遗传算法  

Genetic algorithm for nonlinear equalization

作　　者：姜波[1] 李爱红[1] 朱江[1] 张尔扬[1] 

机构地区：[1]国防科技大学电子科学与工程学院,湖南长沙410073

出　　处：《西安电子科技大学学报》2007年第6期1001-1006,共6页Journal of Xidian University

基　　金：国家部委预研基金资助(113030401)

摘　　要：提出了一种改进的遗传算法,用它搜索稀疏Volterra滤波器的最佳形式.与经典遗传算法不同,本算法定义可能解的元素为染色体,对染色体采用整数编码,效率高.遗传进化过程从低阶、短记忆非线性模型开始,通过进化发现合适的参数设置,从而不需要预先确定模型的阶数和记忆深度,避免了高阶长记忆非线性带来的搜索空间的急速膨胀.通过LMS算法估计核矢量,避免了相同核的重复估计,节省了运算.将本算法用于中继卫星信道的非线性均衡,并进行性能仿真,仿真结果表明,种群规模大幅减小,进化速度明显加快.This paper proposes an improved genetic algorithm for determining the optimal structure of the sparse Volterra filter. The algorithm defines chromosomes as the components of possible solutions instead of possible solutions in the classic genetic algorithm. The chromosomes are encoded with integer, which results in high efficiency. The genetic evolution process starts from the lower-order and short memory nonlinear model, and optimal setting is obtained at the end of the evolution process. Thus, the order and memory length of the nonlinear model needn＇t be determined in advance, which avoids the booming expansion of the searching space for the high-order and long memory nonlinear model. The algorithm estimates the sparse kernel vector by the LMS algorithm, and therefore avoids repetitive estimation of the same vector and reduces computation. The simulation is finally carried out by applying the algorithm to nonlinear equalization for the data relay satellite channel, and the results show that the size of seeds group is largely reduced and that the genetic evolution converges faster.

关 键 词：自适应Volterra滤波 遗传算法 稀疏滤波器 信道均衡 

分 类 号：TN911.5[电子电信—通信与信息系统]