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Port Selection for Fluid Antenna Systems Via Conditional Generative Adversarial Networks

Eskandari, Mahdi; Burr, Alister G; Cumanan, Kanapathippillai; Wong, Kai-Kit; (2025) Port Selection for Fluid Antenna Systems Via Conditional Generative Adversarial Networks. In: 2025 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit). (pp. pp. 25-30). IEEE: Poznan, Poland. Green open access

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Abstract

Fluid antenna systems (FAS) present an innovative solution to enhance diversity in compact mobile devices. They dynamically adjust the position of radiating elements (known as ports), optimizing their placement to mitigate signal fades effectively. Despite their potential to enhance the signal-to-noise ratio (SNR), practical implementation faces challenges in port selection due to the vast volume of required channel estimation for all of the ports. In this letter, we propose a novel approach employing conditional generative adversarial networks (cGANs) to streamline port selection processes. This is done by leveraging the correlation among the ports due to their close proximity to generate unobserved channels for unobserved ports. Through extensive simulations, our findings demonstrate significant reductions in outage probability with minimal observed ports, showcasing the efficacy of our proposed algorithm.

Type: Proceedings paper
Title: Port Selection for Fluid Antenna Systems Via Conditional Generative Adversarial Networks
Event: 2025 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit): AI/ML Solutions for Communications (AI4C)
Dates: 3 Jun 2025 - 6 Jun 2025
ISBN-13: 979-8-3503-9180-0
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/eucnc/6gsummit63408.2025.11037200
Publisher version: https://doi.org/10.1109/eucnc/6gsummit63408.2025.1...
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.
Keywords: Antenna position selection, fluid antenna systems, machine learning, port selection, conditional generative adversarial networks, outage
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
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/10212709
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