FAS-aided Robust Anti-Jamming Communications: Continuous and Discrete Positioning Designs

TL;DR

This paper explores joint beamforming and antenna positioning in fluid antenna systems for anti-jamming, proposing continuous and discrete optimization methods that outperform traditional continuous approaches.

Contribution

It introduces a novel discrete joint design using sparse recovery, demonstrating superior performance over continuous optimization in FAS anti-jamming scenarios.

Findings

Discrete joint design outperforms continuous optimization in sum-rate.

Sparse recovery effectively avoids local optima in antenna positioning.

Discretization with sparse recovery enhances spatial degrees-of-freedom utilization.

Abstract

This paper investigates the joint optimization of beamforming and antenna positions in fluid antenna system (FAS)-aided anti-jamming communications. We consider a multi-user multiple-input multiple-output downlink scenario where multiple malicious jammers exist and the jammer channel state information is imperfect. The goal is to maximize the worst-case sum-rate under quality-of-service and transmit power constraints. To achieve this, we develop two distinct optimization frameworks for continuous and discrete antenna position designs, respectively. For continuous design, we propose an alternating optimization (AO) framework that integrates successive convex approximation and majorization minimization (MM) to handle the highly non-convex problem. For discrete design, based on the minimum mean squared error criterion and MM, we reformulate the problem as a sparse recovery task and propose a low-complexity block coordinate descent and simultaneous orthogonal matching pursuit, which enables joint design rather than AO. Through systematic comparison, we uncover a practical phenomenon: the discrete joint design yields superior sum-rate performance compared to the AO-based continuous counterpart under identical conditions. This superiority stems from the sparse recovery formulation which effectively circumvents the severe local optima. Our findings challenge the conventional view that continuous optimization is inherently superior, and reveal that discretization combined with sparse recovery can offer a more effective paradigm for exploiting spatial degrees-of-freedom in FAS-aided anti-jamming communications.