An Intelligent Access Channel Algorithm Based on Distributed Double Q Learning

Aiming at the problem of mutual interference between nodes and external malicious jamming in wireless communication networks, this paper proposes an intelligent anti-jamming algorithm based on distributed double Q-learning. First all, proposed is modeled as a time-frequency two-dimensional optimization problem. The decoupled relationship subframe channel used. Each node uses two According to automatically received feedback signal, users choose their avoid users. It maximizes sum all user throughput. Simulation results show that can effectively shorten convergence time improve performance system.