Abstract:

A medium access control protocol using dueling-deep double Q-network (dueling-DDQN) algorithm is proposed to maximize the system throughput in the rapidly changing wireless communication networks. The proposed protocol applies the q value calculation method of the dueling deep Q-network to calculate the q value of the deep double Q-network,which combines the advantages of dueling deep Q-network and deep double Q-network. Thus, it cannot only increase the calculation accuracy of the q value and the convergence performance, but also solve the problem of overestimation, that improves the overall performance and robustness of the system. The simulation results demonstrate that the proposed protocol coexisting with time division multiple access protocol and ALOHA protocol in wireless communication systems, is effective to reduce the convergence time and increase the total system throughput when comparing to the traditional deep Q-network medium access control(MAC) protocol.

Key words: deep reinforcement learning, dueling deep Q-network, deep double Q-network, medium access control protocols, throughput