Abbasi, Muhammad Ali Babar, Ansari, Rafay, Machado, Gabriel G. and Fusco, Vincent F. (2021) Design and analysis of Maxwell fisheye lens based beamformer. Scientific Reports, 11 (1). p. 22739. ISSN 2045-2322
|
Text
s41598-021-02058-9.pdf - Published Version Available under License Creative Commons Attribution 4.0. Download (3MB) | Preview |
|
|
Text
Design_and_Analysis_of_Maxwell_Fisheye_Lens_based_Beamformer.pdf - Accepted Version Download (5MB) | Preview |
Abstract
Antenna arrays and multi-antenna systems are essential in beyond 5G wireless networks for providing wireless connectivity, especially in the context of Internet-of-Everything. To facilitate this requirement, beamforming technology is emerging as a key enabling solution for adaptive on-demand wireless coverage. Despite digital beamforming being the primary choice for adaptive wireless coverage, a set of applications rely on pure analogue beamforming approaches, e.g., in point-to-multi point and physical-layer secure communication links. In this work, we present a novel scalable analogue beamforming hardware architecture that is capable of adaptive 2.5-dimensional beam steering and beam shaping to fulfil the coverage requirements. Beamformer hardware comprises of a finite size Maxwell fisheye lens used as a scalable feed network solution for a semi-circular array of monopole antennas. This unique hardware architecture enables a flexibility of using 2 to 8 antenna elements. Beamformer development stages are presented while experimental beam steering and beam shaping results show good agreement with the estimated performance.
Item Type: | Article |
---|---|
Additional Information: | Funding information: This work was partially supported by the Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/P000673/1 and Grant EP/S007954/1. |
Subjects: | G400 Computer Science G500 Information Systems |
Department: | Faculties > Engineering and Environment > Computer and Information Sciences |
Depositing User: | Elena Carlaw |
Date Deposited: | 02 Dec 2021 15:13 |
Last Modified: | 23 May 2022 03:32 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/47887 |
Downloads
Downloads per month over past year