混沌通信中时变信道的盲辨识  

Blind identification of time-varying channel in chaotic communication

作　　者：范永全[1,2] 张家树[2] 

机构地区：[1]西华大学数学与计算机学院,成都610039 [2]西南交通大学信号与信息处理重点实验室,成都610031

出　　处：《计算机工程与应用》2010年第23期151-153,158,共4页Computer Engineering and Applications

基　　金：国家自然科学基金No.60572027~~

摘　　要：利用混沌信号的有界性,集员广义LMS(SM-GLMS)算法成功用于混沌通信中的盲信道辨识。进一步将其应用于时变信道的盲辨识,分析了该算法的收敛性能,并提出了一种新的基于时变衰减因子的GLMS(VFF-GLMS)算法。结果表明VFF-GLMS和SM-GLMS算法性能相当,并且比常规的GLMS算法具有更好的稳态性能和时变参数跟踪能力。With the boundedness of chaotic signal the Set-Membership Generalized Least Mean Square（SM-GLMS） algorithm has been successfully used to blind channel equalization in chaotic communications.In this paper,the SM-GLMS is further applied to time-varying channel identification and its convergence property is also justified,finally a novel GLMS algorithm with Variable Forgetting Factor（VFF-GLMS） is proposed.Simulation results show that the performance of VFF-GLMS is comparable with that of SM-GLMS.In comparison with conventional GLMS algorithm both of them provide significant improvement in terms of steady state performance and tracking ability to the variation of channel parameters.

关 键 词：盲辨识 集员 最小均方(LMS) 混沌 时变信道 

分 类 号：TN911.7[电子电信—通信与信息系统]