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空时MIMO-OFDM系统中基于扩展Kalman滤波的信道估计

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Extended Kalman filtering-based channel estimation for space-time coded MIMO-OFDM systems
A space-time coded multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) system is considered as a solution to the future wideband wireless communication system. This paper proposes an extended Kalman filtering-based (EKF-based) channel estimation method for space-time coded MIMO-OFDM systems. The proposed method can exploit pilot symbols and an extended Kalman filter to estimate channel without any prior knowledge of channel statistics. In comparison with the least square (LS) and the least mean square (LMS) methods, the EKF-based approach has a better performance in theory. Computer simulations demonstrate the proposed method outperforms the LS and LMS methods. Therefore it can offer dramatic system performance improvement at a modest cost of computational complexity.

multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM), channel estimation,extended Kalman filtering (EKF), least mean square (LMS).

梁永明、罗汉文、黄建国

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Department of Electronic Engineering, Shanghai Jiaotong University, Shanghai 200240, P. R. China

College of Marine Engineering, Northwestern Polytechnical University, Xi'an 710072, P. R. China

multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM), channel estimation,extended Kalman filtering (EKF), least mean square (LMS).

国家自然科学基金国家高技术研究发展计划(863计划)

605721572003AA123310

2007

上海大学学报(英文版)
上海大学

上海大学学报(英文版)

影响因子：0.196
ISSN：1007-6417
年,卷(期)：2007.11(5)
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