Suboptimal MMSE Channel Estimation with Subspace Tracking for MIMO-OFDM Transmission  

作　　者：张静 罗汉文 金荣洪 

机构地区：[1]Department of Electronic Engineering,Shanghai Jiaotong University [2]Department of Communication Engineering,Shanghai Normal University

出　　处：《Journal of Donghua University(English Edition)》2010年第1期14-18,共5页东华大学学报（英文版）

基　　金：National Natural Science Foundation of China (No.60572157);International Cooperation Foundation of Shanghai Jiaotong University,China (No.2008DFA11950)

摘　　要：A suboptimal minimum mean-squared error estimation （MMSE） is proposed for a dispersive wireless channel in the absence of its .orrelation matrix for multipleinput multiple-output ort,ogonal frequency division multiplexing （MIMO - OFDM） transmission. It utilizes a fast subspace approximation tracking to separate signal subspace with a limited set of channel estimates. The subspace rank is adjusted by pre-set thresholds in different signal-to-noise ratios （SNRs）. The performance comparison among the proposed algorithm, least square based, and the optimal MMSE estimation is shown by numerical simulation under a spatially correlated multi-tap channel scenario. It demonstrates that the approach has better normalized mean square error than recursive least square estimation and yields 3 dB gain over the latter.A suboptimal minimum mean-squared error estimation (MMSE) is proposed for a dispersive wireless channel in the absence of its correlation matrix for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) transmission.It utilizes a fast subspace approximation tracking to separate signal subspace with a limited set of channel estimates.The subspace rank is adjusted by pre-set thresholds in different signal-to-noise ratios (SNRs).The performance comparison among the proposed algorithm,least square based,and the optimal MMSE estimation is shown by numerical simulation under a spatially correlated multi-tap channel scenario.It demonstrates that the approach has better normalized mean square error than recursive least square estimation and yields 3 dB gain over the latter.

关 键 词：multiple-input multiple-output （ MIMO ） orthogonal frequency division multiplexing （OFDM） channel estimation adaotive estimation spatial-correlation 

分 类 号：TN914[电子电信—通信与信息系统] TP183[电子电信—信息与通信工程]