Coordination Graph-Based Deep Reinforcement Learning for Cooperative Spectrum Sensing Under Correlated Fading

In this letter, cooperative spectrum sensing (CSS) under correlated fading in cognitive radio networks is modeled, and the distributed deep reinforcement learning method is adopted to learn the optimal CSS strategy. To reduce the dimension of the solution space in large networks, this letter takes advantage of the coordination graph to decompose the problem into a max-plus problem and employs the message passing to obtain the optimal strategy sequentially. The simulation results verify the superior performance of the proposed algorithm by comparison with the conventional reinforcement learning implementations.