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Virtual FAS by Learning-Based Imaginary Antennas

Wong, KK; Wang, C; Zhang, H; Li, G; Wang, CC; Chae, CB; Murch, R; (2024) Virtual FAS by Learning-Based Imaginary Antennas. IEEE Wireless Communications Letters p. 1. 10.1109/LWC.2024.3382220. (In press). Green open access

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Abstract

Fluid antenna system (FAS) represents a new technology able to flexibly and instantaneously change the antenna position for optimizing wireless communication performance. The high-resolution adjustment of the antenna position is what makes FAS powerful in taking full advantage of the fading variation in space. To obtain the benefits of FAS but without the complication of implementing FAS, this letter considers a mobile receiver with several fixed-position antennas and employs a transformer-based signal prediction network to deduce the received signals at other positions. This is possible since the received signals are correlated in space. The outcome is an increased dimension multiple-input multiple-output (MIMO) receiver which can be interpreted as a virtual FAS with imaginary antennas. We evaluate the proposed system in multiuser channels and adopt regularized zeroforcing (RZF) in the virtual FAS to deal with the interference. Simulation results demonstrate that the proposed virtual FAS outperforms significantly the original fixed-position MIMO system.

Type: Article
Title: Virtual FAS by Learning-Based Imaginary Antennas
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/LWC.2024.3382220
Publisher version: http://dx.doi.org/10.1109/lwc.2024.3382220
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10191112
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