A CHANNEL ESTIMATION METHOD BASED ON DISTRIBUTED COMPRESSED SENSING AND TIMEDOMAIN KALMAN FILTERING IN OFDM SYSTEMS
Channel estimation is important for coherent detection in orthogonal frequency-division multiplexing (OFDM) systems. Current time-domain Kalman filtering (TDKF) method has a good performance in estimating the channel responses, but is impractical since it requires the knowledge of multipath delays. In this paper, we propose a new scheme to relax such requirement by combining the recent methodology of distributed compressed sensing (DCS) and TDKF. By exploiting the sparse attribute of OFDM channels, the number of pilots could be reduced greatly. Furthermore, to reduce the complexity, a threshold on the change of channel responses is designed to avoid unnecessary DCS execution. Simulations indicate the proposed method achieves better performance than conventional least square method.
channel estimation distributed compressed sensing kalman filtering
Wenbo Xu Donghao Wang Kai Niu Zhiqiang He Jiaru Lin
Key Lab of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications, Beijing, 100876, China
国际会议
深圳
英文
157-161
2011-10-28（万方平台首次上网日期，不代表论文的发表时间）