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A Semi-blind Method for MIMO Channel Identification

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4 Author(s)
Mengxing Li ; School of Telecommunication Engineering, Beijing University of Posts and Communications, Beijing, China. ; Longyang Huang ; Zemin Liu ; Weimin Zuo

A semi-blind algorithm to perform channel identification for multiple input multiple output(MIMO) systems in frequency and time-selective fading environments is proposed. It contains two steps:training and tracking.In training phase, improved Kalman filtering,namely robust Kalman filtering (RKF), is exploited to identify channel impulse response(CIR). After 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.

Published in:

2007 IEEE International Conference on Automation and Logistics

Date of Conference:

18-21 Aug. 2007