Evaluation of Low Complexity Massive MIMO Techniques Under Realistic Channel Conditions

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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; Xiao, Pei.

In: IEEE Transactions on Vehicular Technology, Vol. 68, No. 9, 09.2019, p. 9297-9302.

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Bashar, Manijeh ; Burr, Alister G. ; Haneda, Katsuyuki ; Cumanan, Kanapathippillai ; Molu, Mehdi M. ; Khalily, Mohsen ; Xiao, Pei. / Evaluation of Low Complexity Massive MIMO Techniques Under Realistic Channel Conditions. In: IEEE Transactions on Vehicular Technology. 2019 ; Vol. 68, No. 9. pp. 9297-9302.

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@article{45d0dd30f09a4bf596e515c68d38237c,
title = "Evaluation of Low Complexity Massive MIMO Techniques Under Realistic Channel Conditions",
abstract = "In this paper, a low complexity massive multiple-input multiple-output technique is studied with a geometry-based stochastic channelmodel, calledCOST2100 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 tradeoff 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.",
keywords = "COST 2100 channel model, massive MIMO, MMSE estimation, spatial correlation, user scheduling",
author = "Manijeh Bashar and Burr, {Alister G.} and Katsuyuki Haneda and Kanapathippillai Cumanan and Molu, {Mehdi M.} and Mohsen Khalily and Pei Xiao",
year = "2019",
month = "9",
doi = "10.1109/TVT.2019.2927095",
language = "English",
volume = "68",
pages = "9297--9302",
journal = "IEEE Transactions on Vehicular Technology",
issn = "0018-9545",
number = "9",

}

RIS - Download

TY - JOUR

T1 - Evaluation of Low Complexity Massive MIMO Techniques Under Realistic Channel Conditions

AU - Bashar, Manijeh

AU - Burr, Alister G.

AU - Haneda, Katsuyuki

AU - Cumanan, Kanapathippillai

AU - Molu, Mehdi M.

AU - Khalily, Mohsen

AU - Xiao, Pei

PY - 2019/9

Y1 - 2019/9

N2 - In this paper, a low complexity massive multiple-input multiple-output technique is studied with a geometry-based stochastic channelmodel, calledCOST2100 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 tradeoff 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.

AB - In this paper, a low complexity massive multiple-input multiple-output technique is studied with a geometry-based stochastic channelmodel, calledCOST2100 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 tradeoff 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.

KW - COST 2100 channel model

KW - massive MIMO

KW - MMSE estimation

KW - spatial correlation

KW - user scheduling

U2 - 10.1109/TVT.2019.2927095

DO - 10.1109/TVT.2019.2927095

M3 - Article

VL - 68

SP - 9297

EP - 9302

JO - IEEE Transactions on Vehicular Technology

JF - IEEE Transactions on Vehicular Technology

SN - 0018-9545

IS - 9

ER -

ID: 37758991