Location-Aware Anti-Jamming Game: An Intelligent Approach for Reliable Wireless Communications

Advances in wireless communication technologies have led to increasing dynamic jamming attacks. Enabling the receiver to make real-time decisions that enhance the communication quality from the transmitter and to defend against the interference from the jammer becomes a key challenge, which can be modeled as a game. In such a game, the receiver aims to optimize communication performance by adjusting its geographical location and negotiating frequency band. Meanwhile, the jammer tries to launch more effective attacks based on the receiver's decisions. Nevertheless, the complex electromagnetic environment, combined with the vast decision possibilities thereby induced, poses significant challenges in accurately quantifying payoff matrices within such games. Specifically, two-dimensional geographical location and one-dimensional frequency band form a three-dimensional strategy space, further introducing difficulties for intelligent and efficient decision-making. To address these challenges, we first develop a location-aware anti-jamming game (LAJ game) to characterize the simultaneous decision-making and non-cooperative relationship between the receiver and the jammer, with Nash Equilibrium (NE) being the optimal strategy for both game players. Through appropriate discretization, we then compute two payoff matrices based on geographical locations and frequency bands. Finally, we propose ResBiNet, a continuous series-parallel architecture that utilizes inverted residual blocks to construct a deep cascade residual network, specifically designed to effectively solve large-scale LAJ games. Extensive experiments using real-world and synthesized datasets demonstrate that our proposed method can exponentially reduce running time while achieving an approximation error of less than 5%, offering an intelligent and efficient solution to address location-aware anti-jamming communication challenges.