A Communication Game Confrontation Simulation System for MANET

Currently, game theory is wildly used in various fields such as gaming, military, and transportation, particularly focusing on Mobile Ad hoc Networks (MANETs) used in modern communication warfare scenarios. In military confrontations, both sides seek to disrupt the information transmission of the opponent and take countermeasures accordingly. Many related studies have proposed anti-jamming algorithms that intelligently avoid interference using spectral information. In this paper, a communication simulation system based on game theory adversarial strategies is proposed. It simulates the communication scenarios between opposing forces when using different interference and anti-jamming strategies. Deep reinforcement learning algorithms enable both sides to make intelligent decisions, and a comparison is made between the antijamming capabilities of communication in game scenarios and non-game scenarios. The results show that in situations where both sides engage in a game, the anti-jamming capability of the communication decreases.