NDLI: Subspace-Based Semi-Blind Channel Estimation for Large-Scale Multi-Cell Multiuser MIMO Systems

Content Provider	IEEE Xplore Digital Library
Author	Anzhong Hu Tiejun Lv Yueming Lu
Copyright Year	2013
Description	Author affiliation: Key Lab. of Trustworthy Distrib. Comput. & Service, Beijing Univ. of Posts & Telecommun., Beijing, China (Anzhong Hu; Tiejun Lv; Yueming Lu)
Abstract	Large-scale multi-cell multiuser multiple-input multiple-output (LS-MIMO) systems have received much attention recently. But the performance of these systems is deteriorated by imperfect channel state information (CSI). Hence, in this paper, a subspace-based semi-blind channel estimator is proposed. Based on the approximate orthogonality of the channel vectors of LS-MIMO systems, singular value decomposition (SVD) is employed on the received signals to determine the channel matrix up to an ambiguity matrix. Then matrix inversion is avoided in resolving the ambiguity matrix, which is essential to traditional subspace-based estimators and loses the partial CSI. The properties of the estimators are analyzed, and the analysis shows that the estimation accuracy of the proposed estimator is improved. Simulations comparing the proposed approach with others illustrate improvement of the performance of the proposed approach.
Sponsorship	IEEE Vehicular Technol. Soc.
Starting Page	1
Ending Page	5
File Size	219760
Page Count	5
File Format	PDF
ISBN	9781467363372
ISSN	15502252
DOI	10.1109/VTCSpring.2013.6692772
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-02
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Channel estimation Vectors Matrix decomposition MIMO Antennas Covariance matrices Fading
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering Computer Science Applications

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