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3D Beamforming for 5G Millimeter Wave Systems Using Singular Value Decomposition and Particle Swarm Optimization Approaches

Alluhaibi, Osama, Nair, Manish, Hazzaa, Amjed, Mihbarey, Aza, Wang, Jiangzhou (2018) 3D Beamforming for 5G Millimeter Wave Systems Using Singular Value Decomposition and Particle Swarm Optimization Approaches. In: 2018 International Conference on Information and Communication Technology Convergence (ICTC). . pp. 15-19. IEEE, USA ISBN 978-1-5386-5042-4. E-ISBN 978-1-5386-5041-7. (doi:10.1109/ICTC.2018.8539578) (KAR id:71373)

Abstract

Millimeter wave (mmWave) systems are one of the

proposed solutions for the fifth generation (5G) mobile network.

However, mmWave system experiences strong path loss due to

higher frequencies. To solve this problem, such a system demands

a narrow beampattern to reduce the loss of the mmWave signal

energy due to the high path loss. One of the significant challenges

to be addressed before their deployment is designing three dimensional

(3D) beamforming algorithms, which are required to be

directional. In this paper, we first propose two 3D beamforming

algorithms with aim of tracking users in both the azimuth and

elevation planes. Our proposed beamforming algorithms operates

based on the principles of singular value decomposition (SVD) and

particle swarm optimization (PSO). Furthermore, these beamforming

algorithms are designed to have limited or negligible side

lobes, which cause less interference to the other users operating

in the same cell. In order to achieve this objective, Kaiser Bessel

(KB) filter is adopted which helps in mitigating side lobes in the

synthesized beampattern. Based on our analysis, we gain some

valuable insights. The proposed algorithms are shown to perform

well in achieving considerable capacity and lower side lobs.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/ICTC.2018.8539578
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: M. Nair
Date Deposited: 20 Dec 2018 11:40 UTC
Last Modified: 04 Mar 2024 15:17 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/71373 (The current URI for this page, for reference purposes)

University of Kent Author Information

Alluhaibi, Osama.

Creator's ORCID:
CReDIT Contributor Roles:

Nair, Manish.

Creator's ORCID: https://orcid.org/0000-0001-7151-8913
CReDIT Contributor Roles:

Wang, Jiangzhou.

Creator's ORCID: https://orcid.org/0000-0003-0881-3594
CReDIT Contributor Roles:
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