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Evaluation of Low Complexity Massive MIMO Techniques Under Realistic Channel Conditions

Bashar, Manijeh, Burr, Alister G., Haneda, Katsuyuki, Cumanan, Kanapathippillai, Molu, Mehdi M., Khalily, Mohsen and Xiao, Pei (2019) Evaluation of Low Complexity Massive MIMO Techniques Under Realistic Channel Conditions IEEE Transactions on Vehicular Technology.

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Abstract

A low complexity massive multiple-input multipleoutput (MIMO) technique is studied with a geometry-based stochastic channel model, called COST 2100 model. We propose to exploit the discrete-time Fourier transform of the antenna correlation function to perform user scheduling. The proposed algorithm relies on a trade off between the number of occupied bins of the eigenvalue spectrum of the channel covariance matrix for each user and spectral overlap among the selected users. We next show that linear precoding design can be performed based only on the channel correlation matrix. The proposed scheme exploits the angular bins of the eigenvalue spectrum of the channel covariance matrix to build up an “approximate eigenchannels” for the users. We investigate the reduction of average system throughput with no channel state information at the transmitter (CSIT). Analysis and numerical results show that while the throughput slightly decreases due to the absence of CSIT, the complexity of the system is reduced significantly.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Bashar, Manijehm.bashar@surrey.ac.uk
Burr, Alister G.
Haneda, Katsuyuki
Cumanan, Kanapathippillai
Molu, Mehdi M.m.molu@surrey.ac.uk
Khalily, Mohsenm.khalily@surrey.ac.uk
Xiao, PeiP.Xiao@surrey.ac.uk
Date : 2019
Copyright Disclaimer : © 2019 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
Uncontrolled Keywords : COST 2100 channel model; Massive MIMO; MMSE estimation; Spatial correlation; User scheduling
Related URLs :
Depositing User : Clive Harris
Date Deposited : 03 Jul 2019 13:09
Last Modified : 03 Jul 2019 13:09
URI: http://epubs.surrey.ac.uk/id/eprint/852200

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