Static and Dynamic Jamming Games Over Wireless Channels With Mobile Strategic Players
This paper investigates a zero-sum game between a mobile legitimate receiver and an interferer in wireless communications, using channel capacity as the payoff function—departing from prior works that assume static nodes. It introduces one-dimensional linear mobility as a core dynamic variable in the game formulation, establishing two scenario classes: static position configurations and dynamic position evolution, under three information structures—complete, incomplete, and delayed information. Theoretically, it derives closed-form solutions for static Nash equilibria and proposes a general design principle: “static solutions guide dynamic strategies.” Methodologically, it integrates game-theoretic analysis with reinforcement learning (RL) to efficiently approximate equilibria in high-dimensional dynamic strategy spaces. Experimental results demonstrate that the proposed RL-based policies exhibit robustness and practicality across diverse mobility patterns and information constraints.