NDLI: Statistical channel state information acquisition for massive MIMO communications

Content Provider	IEEE Xplore Digital Library
Author	Zhitan Zheng Chengzhi Zhu Bin Jiang Wen Zhong Xiqi Gao
Copyright Year	2015
Description	Author affiliation: Nat. Mobile Commun. Res. Lab., Southeast Univ., Nanjing, China (Zhitan Zheng; Chengzhi Zhu; Bin Jiang; Wen Zhong; Xiqi Gao)
Abstract	This paper studies the statistical channel state information (CSI) acquisition in single-cell for massive multiuser multiple-input multiple-output (MIMO) system in the beam domain. Compared with the Bayesian channel estimation which models the channels by an independent and identically Gaussian-mixture (GM) distribution, we model the channels by an independent and non-identically Gaussian distribution exploiting the statistical channel characteristics, and provide the acquired statistical CSI for the approximate message passing (AMP) channel estimation that can reduce computational complexity. Meanwhile, we show that the statistical CSI for the user scheduling in the beam division multiple access (BDMA) transmission is the same as that of the AMP channel estimation. Due to the heavy orthogonal pilot overhead when serving a large number of user terminals (UTs) in massive MIMO system, the Bayesian channel estimation that don't need the orthogonal pilots is used to estimate the channel parameters in the statistical CSI acquisition. Simulation results show that the mean square error (MSE) of the AMP channel estimation using the estimated statistical CSI is better than that of the Bayesian channel estimation and the iteration number has a significant reduction. Besides, the user scheduling using the estimated statistical CSI can reach a good sum rate of the scheduled UTs.
Starting Page	1
Ending Page	5
File Size	750764
Page Count	5
File Format	PDF
e-ISBN	9781467376877
DOI	10.1109/WCSP.2015.7341263
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Simulation Channel estimation MIMO Bayes methods Covariance matrices Antennas
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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