Adaptive Beamforming for mmWave 5G MIMO Antennas

Enahoro, Sunday, Ekpo, Sunday ORCID: https://orcid.org/0000-0001-9219-3759, Uko, Mfonobong, Ansari,, Umm-E-Haya, Altaf, Arslan and Zafar, Muazzam (2021) Adaptive Beamforming for mmWave 5G MIMO Antennas. In: 2021 IEEE 21st Annual Wireless and Microwave Technology Conference, 28 April 2021 - 29 April 2021, Sand Key, Forida, USA.

Preview

Accepted Version
Download (1MB) | Preview

Official URL: https://ieeexplore.ieee.org/document/9443616

Abstract

The direction of arrival (DOA) estimation and beamforming are effective methods for spatial diversity realization. Various algorithm already exists for implementing these methods. This paper explore the performance of least mean square algorithm (LMS) beamforming algorithm. This adaptive beamforming algorithm investigates receiver signal processing method that continuously monitor, calculate and update the weights in a continuously changing electromagnetic environment. Several optimization algorithms are studied, and a comparison of the least mean-squared algorithm and the minimum variance distortionless response is investigated with varying parameters (i.e. number of antenna element, element spacing etc.) using analytical method and Matlab simulation. It would be demonstrated through simulation that LMS algorithm increases signal quality by elimination interfering signals and noise by nulling them, while sending maximum signal (beams) to the desired direction.

Item Type:	Conference or Workshop Item (Paper)
Published Proceedings:	2021 IEEE 21st Annual Wireless and Microwave Technology Conference (WAMICON)
Peer-reviewed:	Yes
Date Deposited:	22 Sep 2022 10:37
Publisher:	IEEE
Additional Information:	© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Divisions:	Faculties > Science and Engineering
URI:	https://e-space.mmu.ac.uk/id/eprint/630104
DOI:	https://doi.org/10.1109/WAMICON47156.2021.9443616

Impact and Reach

Statistics

DownloadsShow export options

Activity Overview

6 month trend

247Downloads

6 month trend

38Hits

Additional statistics for this dataset are available via IRStats2.

Altmetric

Repository staff only

Edit record