Blind adaptive identification and equalization using bias-compensated NLMS methods  

作　　者：Zhen ZHANG Lijuan JIA Ran TAO Yue WANG 

机构地区：[1]School of Information and Electronics,Beijing Institute of Technology,Beijing 100081,China

出　　处：《Science China(Information Sciences)》2022年第5期180-191,共12页中国科学（信息科学）（英文版）

基　　金：supported in part by National Natural Science Foundation of China(Grant No.41927801)。

摘　　要：In this paper,two new blind adaptive identification and equalization algorithms based on second-order statistics are proposed.We consider a practical case where the noise statistics of each transmission channel is unknown.Resorting to the technique of antennas array,a single-input double-output channel can be obtained.We further convert the problem of blind identification into an errors-in-variables(EIV)parameter estimation problem,then we apply the normalized least-mean squares(NLMS)algorithms to tackle the problem.To improve the performance of the NLMS algorithms,we also develop a variable stepsize NLMS(VSS-NLMS)algorithm that ensures the stability of the algorithm and faster convergence speed at the beginning of the iterations process.Under various practical scenarios,noise affects transmission channels;it is necessary to estimate the variance and remove the bias.By modifying the cost function,we present a bias-compensated NLMS(BC-NLMS)algorithm and a bias-compensated NLMS algorithm with variable step-size(BC-VSS-NLMS)to eliminate the bias.The proposed algorithms estimate the variances of the noise online,and therefore,the noise-induced bias can be removed.The estimate of the channel characteristics is available for equalization.Simulation results are presented to demonstrate the performance of the proposed algorithms.

关 键 词：blind adaptive identification EQUALIZATION normalized least mean squares algorithm bias compensation ERRORS-IN-VARIABLES 

分 类 号：TN911.5[电子电信—通信与信息系统]