Port Selection for Fluid Antenna Systems Via Conditional Generative Adversarial Networks

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.