对称α稳定分布噪声下基于Kalman滤波迭代信道估计  

Kalman filter-based iterative channel estimation in symmetric α-stable noise environments

作　　者：罗康生[1] 赵明生[1] 

机构地区：[1]清华大学电子工程系,北京100084

出　　处：《清华大学学报（自然科学版）》2011年第2期145-149,共5页Journal of Tsinghua University(Science and Technology)

基　　金：国家"八六三"高技术项目(2007AA01Z292)

摘　　要：为了提高加性脉冲噪声衰落信道环境下的通信传输性能,提出了一种适用于对称稳定分布噪声的基于Kalman滤波的迭代信道估计方法。该方法利用时变信道的先验统计信息将信道建模为一阶自回归模型,并将最小分散系数准则应用于Kalman滤波信道估计方法中,从而更充分地利用了时变信道和非高斯噪声的先验信息。在较为严重的时变脉冲信道下,该方法比最小平均p范数估计方法性能要优约2 dB。仿真结果表明:该方法能消除脉冲噪声和稳定分布二阶矩不存在等不利因素的影响,能快速准确地跟踪并预测时变信道的变化,且性能显著地优于传统的最小均方误差和最小平均p范数信道估计方法。A Kalman filter-based channel estimation method was developed for symmetric α-stable（SαS） noise to improve transmission performance in time-varying additive impulsive noise channels.The channel is modeled as a first-order autoregressive process using a statistical property for the time-varying channel,with the minimum dispersion criterion then applied to the Kalman filter-based channel estimation.In a severely time-varying impulsive channel,the method gives 2 dB better performance than the least mean p-norm method.Simulations show this Kalman method overcomes the adverse impact of the impulse and the infinite second-order moment.The time-varying channel can be predicted accurately and quickly,and the method is more effective than the traditional least mean square（LMS） algorithm and the least mean p-norm（LMP） algorithm.

关 键 词：时变衰落信道 迭代信道估计 TURBO均衡 Α稳定分布噪声 KALMAN滤波 

分 类 号：TN911.5[电子电信—通信与信息系统]