An Intelligent Anti-interference Communication Method Based on Game Learning

摘要

Wireless communication is vulnerable to malicious jamming due to its inherent broadcast characteristics. With the development of intelligent technology, the jammer can actively adjust the jamming strategy according to the feedback of the jamming effect, so as to achieve intelligent jamming with lower consumption and higher efficiency. The existence of intelligent jamming poses more serious challenges to the reliable transmission capacity of wireless communication system. In this paper, an intelligent anti-jamming communication method based on game learning is proposed. The communication confrontation between jammer and user is modeled as Stackelberg game, and intelligent anti-jamming decision-making in frequency domain is realized with the help of reinforcement learning algorithm, so as to improve the reliability of wireless transmission and realize intelligent anti-jamming communication in the jamming environment. The simulation results show that the proposed scheme can obtain stable policies, and the proposed anti-jamming communication method has higher anti-jamming performance than the conventional method.