Subverting Flexible Multiuser Communications via Movable Antenna-Enabled Jammer

TL;DR

This work introduces a movable-antenna jammer (MAJ) to subvert suspicious multiuser downlink communications by jointly optimizing jamming beamforming and antenna positions, under two reliability metrics: the sum-rate and the minimum-rate. By assuming a ZF-based ST and LoS channels, the authors formulate a non-convex AO framework that alternates between updating the MAJ’s beamforming and antenna placements, using SCA and log-sum-exp approximations to handle the non-differentiable max terms. A key theoretical result for the special case with $K=2$ shows that optimal MAJ deployment decouples antenna placement from beamforming and relies on maximizing jamming-channel correlation, providing intuitive deployment rules and performance bounds. Simulation results demonstrate that the proposed AO schemes outperform fixed-position baselines and benchmarks across multiple metrics, channel conditions, and MA movement extents, highlighting the practical viability of MA-enabled jamming and its robustness to CSI imperfections.

Abstract

Movable antenna (MA) is an emerging technology which can reconfigure wireless channels via adaptive antenna position adjustments at transceivers, thereby bringing additional spatial degrees of freedom for improving system performance. In this paper, from a security perspective, we exploit the MAenabled legitimate jammer (MAJ) to subvert suspicious multiuser downlink communications consisting of one suspicious transmitter (ST) and multiple suspicious receivers (SRs). Specifically, our objective is to minimize the benefit (the sum rate of all SRs or the minimum rate among all SRs) of such suspicious communications, by jointly optimizing antenna positions and the jamming beamforming at the MAJ. However, the key challenge lies in that given the MAJ's actions, the ST can reactively adjust its power allocations to instead maximize its benefit for mitigating the unfavorable interference. Such flexible behavior of the ST confuses the optimization design of the MAJ to a certain extent. Facing this difficulty, corresponding to the above two different benefits: i) we respectively determine the optimal behavior of the ST given the MAJ's actions; ii) armed with these, we arrive at two simplified problems and then develop effective alternating optimization based algorithms to iteratively solve them. In addition to these, we also focus on the special case of two SRs, and reveal insightful conclusions about the deployment rule of antenna positions at the MAJ. Furthermore, we analyze the ideal antenna deployment scheme at the MAJ for achieving the globally performance lower bound. Numerical results demonstrate the effectiveness of our proposed schemes compared to conventional fixed-position antenna (FPA) and other competitive benchmarks.

Figures (10)

• Figure 1: Illustration of the considered system model.
• Figure 2: Simulation setups.
• Figure 3: Convergence behaviors of Algorithm 1. The inner iteration: (a) given ${\bf{x}}$ and optimize ${{\bf{w}}_J}$; (b) given ${{\bf{w}}_J}$ and optimize ${\bf{x}}$. The outer iteration: (c) alternatively optimize ${{\bf{w}}_J}$ and ${\bf{x}}$.
• Figure 4: Convergence behaviors of Algorithm 2. The inner iteration: (a) given ${\bf{x}}$ and optimize ${\bf{y}}$; (b) given ${\bf{y}}$ and optimize ${\bf{x}}$. The outer iteration: (c) alternatively optimize ${\bf{y}}$ and ${\bf{x}}$.
• Figure 5: Suspicious sum rate w.r.t. the total antenna span ($L$) at the MAJ, where ${P_{{\rm{sum}}}} = {Q_J} = 10$ dBm.