Uncertainty-Aware Jamming Mitigation with Active RIS: A Robust Stackelberg Game Approach

TL;DR

The paper tackles secure wireless communication under adaptive jamming by deploying an active RIS (ARIS) and modeling the interaction as a robust Stackelberg game between a legitimate system (leader) and a reactive jammer (follower) under channel uncertainty. It proves equilibrium existence and derives the jammer’s best response in closed form, then solves the leader’s robust optimization using a BSUM framework with SCA-based surrogates to jointly optimize transmit power, beamforming, and ARIS reflection. The uncertainty-aware reformulations rely on bounded error sets and auxiliary variables to capture worst-case interference, ensuring resilience against imperfect CSI. Simulation results show that ARIS with robust BSUM/SCA optimization significantly improves legitimate SINR/utility and reduces the jammer’s effectiveness across different power budgets, ARIS sizes, and jammer locations, demonstrating practical impact for robust anti-jamming deployments.

Abstract

Malicious jamming presents a pervasive threat to the secure communications, where the challenge becomes increasingly severe due to the growing capability of the jammer allowing the adaptation to legitimate transmissions. This paper investigates the jamming mitigation by leveraging an active reconfigurable intelligent surface (ARIS), where the channel uncertainties are particularly addressed for robust anti-jamming design. Towards this issue, we adopt the Stackelberg game formulation to model the strategic interaction between the legitimate side and the adversary, acting as the leader and follower, respectively. We prove the existence of the game equilibrium and adopt the backward induction method for equilibrium analysis. We first derive the optimal jamming policy as the follower's best response, which is then incorporated into the legitimate-side optimization for robust anti-jamming design. We address the uncertainty issue and reformulate the legitimate-side problem by exploiting the error bounds to combat the worst-case jamming attacks. The problem is decomposed within a block successive upper bound minimization (BSUM) framework to tackle the power allocation, transceiving beamforming, and active reflection, respectively, which are iterated towards the robust jamming mitigation scheme. Simulation results are provided to demonstrate the effectiveness of the proposed scheme in protecting the legitimate transmissions under uncertainties, and the superior performance in terms of jamming mitigation as compared with the baselines.

Figures (9)

• Figure 1: System model of an ARIS-assisted communications against a jammer. The legitimate signals and jamming attacks reach the destination through the direct links (shown as arrows) and reflection-based links (shown as tapered ribbons).
• Figure 2: The utility of the legitimate user versus jamming power price.
• Figure 3: The utility of the jammer versus jamming power price.
• Figure 4: The utility of the legitimate user versus legitimate power price.
• Figure 5: The utility of the jammer versus legitimate power price.