Antenna selection based on matching theory for uplink cell-free millimetre wave massive multiple input multiple output systems

Al Ayidh, A., Sambo, Y. , Olaosebikan, S. , Ansari, S. and Imran, M. A. (2022) Antenna selection based on matching theory for uplink cell-free millimetre wave massive multiple input multiple output systems. Telecom, 3(3), pp. 448-466. (doi: 10.3390/telecom3030024)

Abstract

In this paper, we propose a hybrid beamforming architecture with constant phase shifters (CPSs) for uplink cell-free millimetre-wave (mm-Wave) massive multiple-input multiple-output (MIMO) systems based on exploiting antenna selection to reduce power consumption. However, current antenna selection techniques are applied for conventional massive MIMO, not cell-free massive MIMO systems. Therefore, the enormous computational complexity of these techniques to optimally select antennas for cell-free massive MIMO networks is caused by numerous randomly distributed access points (APs) in the service area and their large antennas. The architecture proposed in this work solves this issue by employing a low-complexity matching technique to obtain the optimal number of antennas, chosen based on channel magnitude and by switching off antennas that contribute more to interference power than to desired signal power for each radio frequency (RF) chain at each AP, instead of assuming all RF chains at each AP have the same number of selected antennas. Therefore, an assignment optimization problem based on a bipartite graph is formulated for cell-free mm-Wave massive MIMO system uplinks. Then, the Hungarian method is proposed to solve this problem due to its ability to solve this assignment problem in a polynomial time. Simulated results show that, despite several APs and antennas, the proposed matching approach is more energy-efficient and has lower computational complexity than state-of-the-art schemes.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Ansari, Dr Shuja and Al Ayidh, Abdulrahman and Imran, Professor Muhammad and Sambo, Dr Yusuf and Olaosebikan, Dr Sofiat
• Authors: Al Ayidh, A., Sambo, Y., Olaosebikan, S., Ansari, S., and Imran, M. A.
• College/School: College of Science and Engineering; College of Science and Engineering > School of Computing Science; College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Journal Name: Telecom
• Publisher: MDPI
• ISSN: 2673-4001
• ISSN (Online): 2673-4001
• Published Online: 07 July 2022
• Copyright Holders: Copyright © 2022 by the authors
• First Published: First published in Telecom 3(3): 448-466
• Publisher Policy: Reproduced under a Creative Commons licence