Low-complexity pareto-optimal 3D beamforming for the full-dimensional multi-user massive MIMO downlink
Low-complexity pareto-optimal 3D beamforming for the full-dimensional multi-user massive MIMO downlink
Full-dimensional (FD) multi-user massive multiple-input multiple output (m-MIMO) systems employ large two-dimensional (2D) rectangular antenna arrays to control both the azimuth and elevation angles of signal transmission. We introduce the sum of two outer products of the azimuth and elevation beamforming vectors having moderate dimensions as a new class of FD beamforming. We show that this low-complexity class is capable of outperforming 2D beamforming relying on the single outer product of the azimuth and elevation beamforming vectors. It is also capable of performing close to its FD counterpart of massive dimensions in terms of either the users' minimum rate or their geometric mean rate (GM-rate), or sum rate (SR). Furthermore, we also show that even FD beamforming may be outperformed by our outer product-based improper Gaussian signaling solution. Explicitly, our design is based on low-complexity algorithms relying on convex problems of moderate dimensions for max-min rate optimization or on closed-form expressions for GM-rate and SR maximization.
Zhu, W.
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Tuan, H.D.
5bcfb405-e76a-4cb1-bc66-19eb4b9fe2a5
Dutkiewicz, E.
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Fang, Y.
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Hanzo, Lajos
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Zhu, W.
253a3e2d-5dc5-4c44-b1c2-1ff418a9b0ed
Tuan, H.D.
5bcfb405-e76a-4cb1-bc66-19eb4b9fe2a5
Dutkiewicz, E.
6f53b251-772f-4474-a9cc-c1f53b1370af
Fang, Y.
7536ee40-9593-4ebf-9180-acc53dadcff4
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Zhu, W., Tuan, H.D., Dutkiewicz, E., Fang, Y. and Hanzo, Lajos
(2023)
Low-complexity pareto-optimal 3D beamforming for the full-dimensional multi-user massive MIMO downlink.
IEEE Transactions on Vehicular Technology.
Abstract
Full-dimensional (FD) multi-user massive multiple-input multiple output (m-MIMO) systems employ large two-dimensional (2D) rectangular antenna arrays to control both the azimuth and elevation angles of signal transmission. We introduce the sum of two outer products of the azimuth and elevation beamforming vectors having moderate dimensions as a new class of FD beamforming. We show that this low-complexity class is capable of outperforming 2D beamforming relying on the single outer product of the azimuth and elevation beamforming vectors. It is also capable of performing close to its FD counterpart of massive dimensions in terms of either the users' minimum rate or their geometric mean rate (GM-rate), or sum rate (SR). Furthermore, we also show that even FD beamforming may be outperformed by our outer product-based improper Gaussian signaling solution. Explicitly, our design is based on low-complexity algorithms relying on convex problems of moderate dimensions for max-min rate optimization or on closed-form expressions for GM-rate and SR maximization.
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Low Complexity Pareto optimal 3D Beamforming for the Full Dimensional multi user massive MIMO Downlink
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Low-Complexity_Pareto-Optimal_3D_Beamforming_for_the_Full-Dimensional_Multi-User_Massive_MIMO_Downlink
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Accepted/In Press date: 13 February 2022
e-pub ahead of print date: 16 February 2023
Identifiers
Local EPrints ID: 476742
URI: http://eprints.soton.ac.uk/id/eprint/476742
ISSN: 0018-9545
PURE UUID: 98cb36f0-8060-40ec-bdb7-29f1a6d5cae0
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Date deposited: 12 May 2023 17:00
Last modified: 18 Mar 2024 02:36
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Contributors
Author:
W. Zhu
Author:
H.D. Tuan
Author:
E. Dutkiewicz
Author:
Y. Fang
Author:
Lajos Hanzo
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