Static and dynamic jamming games over wireless channels with mobile strategic players
For researchers in wireless security and game theory, this work extends jamming games to mobile players, but the contribution is incremental as it combines known game-theoretic and RL methods.
This paper studies a wireless jamming game where both the legitimate receiver and jammer can move along a linear geometry, extending prior work on stationary nodes. It solves the static game in closed form and uses reinforcement learning to find equilibrium strategies for dynamic games with varying information assumptions.
We study a wireless jamming problem consisting of the competition between a legitimate receiver and a jammer, as a zero-sum game where the value to maximize/minimize is the channel capacity at the receiver's side. Most of the approaches found in the literature consider the two players to be stationary nodes. Instead, we investigate what happens when they can change location, specifically moving along a linear geometry. We frame this at first as a static game, which can be solved in closed form, and subsequently we extend it to a dynamic game under three different versions for what concerns completeness/perfection of mutual information about the adversary's position, corresponding to different assumptions of concealment/sequentiality of the moves, respectively. We first provide some theoretical conditions that hold for the static game and also help identify good strategies valid under any setup, including dynamic games. Since dynamic games, although more realistic, are characterized by a significantly expanded strategy space, we exploit reinforcement learning to obtain efficient strategies that lead to equilibrium outcomes. We show how theoretical findings can be used to train smart agents to play the game and validate our approach in practical settings.