Joint MIMO Channel Estimation and Equalization in Doubly-selective Fading Environments
A improved algorithm to perform channel estimation and equalization for multiple input multiple output(MIMO) systems in frequency and time-selective fading environments is put forward.It contains two steps:training and tracking.In training phase,improved kalman filtering,namly robust kalman filtering(RKF), is exploited to estimate channel impulse response(CIR). After that,in tracking stage,the RKF and minimum mean-square error feedback decision equalizer (MMSE-DFE) cooperate to track the time-varying channel.The RKF recursions is presented and a closed-form solution for baud rate MIMO MMSE-DFE under perfect knowledge of CIR and correct past decisions conditions is derived. In addition, it regards unknown dc-offset due to zero intermediate frequency(IF) at the receiver as the mean of measurement noise, which is estimated as a byproduct through robust Kalman filters.Finally,it is compared with well-known ones,such as least mean-square (LMS),recursive least square (RLS),kalman filtering (KF).All these show that the proposal exhibits better performance.
MIMO channele stimation equaliazation robust kalman filtering DFE dc-offset..
Mengxing Li Longyang Huang Zemin Liu Weimin Zuo
School of Telecommunication Engineering Beijing University of Posts and Telecommunications Beijing,C Department of computer science & technology Hunan City University Yiyang,China
国际会议
上海
英文
2007-09-21（万方平台首次上网日期，不代表论文的发表时间）