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Frontiers of Electrical and Electronic Engineering

ISSN 2095-2732

ISSN 2095-2740(Online)

CN 10-1028/TM

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Front Elect Electr Eng Chin    2009, Vol. 4 Issue (2) : 161-165    https://doi.org/10.1007/s11460-009-0027-9
RESEARCH ARTICLE
Parameter estimation for MIMO system based on MUSIC and ML methods
Wei DONG(), Jiandong LI, Zhuo LU, Linjing ZHAO
Information Science Institute, State Key Laboratory of Integrated Service Networks, Xidian University, Xi’an 710071, China
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Abstract

The frequency offset and channel gain estimation problem for multiple-input multiple-output (MIMO) systems in the case of flat-fading channels is addressed. Based on the multiple signal classification (MUSIC) and the maximum likelihood (ML) methods, a new joint estimation algorithm of frequency offsets and channel gains is proposed. The new algorithm has three steps. A subset of frequency offsets is first estimated with the MUSIC algorithm. All frequency offsets in the subset are then identified with the ML method. Finally, channel gains are calculated with the ML estimator. The algorithm is a one-dimensional search scheme and therefore greatly decreases the complexity of joint ML estimation, which is essentially a multi-dimensional search scheme.
Keywords multiple-input multiple-output (MIMO)      multiple signal classification (MUSIC)      frequency offsets      channel estimation      maximum likelihood (ML) estimation     
Corresponding Author(s): DONG Wei,Email:wdong_piao@163.com   
Issue Date: 05 June 2009
 Cite this article:   
Wei DONG,Jiandong LI,Zhuo LU, et al. Parameter estimation for MIMO system based on MUSIC and ML methods[J]. Front Elect Electr Eng Chin, 2009, 4(2): 161-165.
 URL:  
https://academic.hep.com.cn/fee/EN/10.1007/s11460-009-0027-9
https://academic.hep.com.cn/fee/EN/Y2009/V4/I2/161
Fig.1  Structure of training sequence
methodrangecomplexityperformancerequirement for TS
ML[-π,π]T-dimensional searchasymptotic optimalno requirement
Besson’s[-π,π]T 1-dimensional searchasymptotic optimalno overlapping in time domain
Yao’s[-π/P,π/P]close-form solutionhave error floorallow overlapping (Walsh sequence)
MUSIC+ML[-π,π]1-dimensional searchsuboptimalallow overlapping
Tab.1  Comparison of four estimators
Fig.2  MSE of frequency offset estimation versus SNR for different estimators
Fig.3  MSE of channel estimation versus SNR for different estimators
Fig.4  MSE of frequency offset estimation with different lengths of
Fig.5  MSE of channel estimation with different lengths of
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