RLS channel estimation with adaptive forgetting factor in space-time coded MIMO-OFDM systems  

作　　者：LIANG Yong-ming LUO Han-wen HUANG Jian-guo 

机构地区：[1]Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200030, China [2]College of Marine Engineering, Northwestern Polytechnical University. Xi＇an 710072, China

出　　处：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》2006年第4期507-515,共9页浙江大学学报（英文版）A辑（应用物理与工程）

基　　金：Project supported by the National Natural Science Foundation of China (No. 60272079), and the Hi-Tech Research and Development Program (863) of China (No. 2003AA123310)

摘　　要：Considering that channel estimation plays a crucial role in coherent detection, this paper addresses a method of Recursive-least-squares (RLS) channel estimation with adaptive forgetting factor in wireless space-time coded multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Because there are three different forgetting factor scenarios including adaptive, two-step and conventional ones applied to RLS channel estimation, this paper describes the principle of RLS channel estimation and analyzes the impact of different forgetting factor scenarios on the performances of RLS channel estimation. Simulation results proved that the RLS algorithm with adaptive forgetting factor (RLS-A) outperformed that with two-step forgetting factor (RLS-T) or with conventional forgetting factor (RLS-C) in both estimation accuracy and robustness over the multiple-input multiple-output (MIMO) channel, i.e., a wide-sense stationary uncorrelated scattering (WSSUS) and frequency-selective slowly fading channel. Hence, we can employ the RLS-A method by adjusting forgetting factor adaptively to track and estimate channel state parameters successfully in space-time coded MIMO-OFDM systems.Considering that channel estimation plays a crucial role in coherent detection, this paper addresses a method of Recursive-least-squares （RLS） channel estimation with adaptive forgetting factor in wireless space-time coded multiple-input and multiple-output orthogonal frequency division multiplexing （MIMO-OFDM） systems. Because there are three different forgetting factor scenarios including adaptive, two-step and conventional ones applied to RLS channel estimation, this paper describes the principle of RLS channel estimation and analyzes the impact of different forgetting factor scenarios on the performances of RLS channel estimation. Simulation results proved that the RLS algorithm with adaptive forgetting factor （RLS-A） outperformed that with two-step forgetting factor （RLS-T） or with conventional forgetting factor （RLS-C） in both estimation accuracy and robustness over the multiple-input multiple-output （MIMO） channel, i.e., a wide-sense stationary uncorrelated scattering （WSSUS） and frequency-selective slowly fading channel. Hence, we can employ the RLS-A method by adjusting forgetting factor adaptively to track and estimate channel state parameters successfully in space-time coded MIMO-OFDM systems.

关 键 词：MIMO-OFDM Channel estimation RLS algorithm Adaptive forgetting factor 

分 类 号：TN911.23[电子电信—通信与信息系统] TN929.5[电子电信—信息与通信工程]