Analysis of relay decision-making in wireless heterogeneous networks supported by deep learning
In wireless heterogeneous networks,the intelligent decision-making for relay nodes directly affects the spectrum efficiency,energy efficiency,and service quality of the network.A reinforcement learning method based on deep Q-network(DQN)is proposed for the relay decision-making problem in wireless heterogeneous networks.The composition of wireless heterogeneous networks and the role of relay nodes are summarized,the advantages and network structure of DQN algorithm are introduced,the state space,action space,and reward function of wireless network environment are defined,and an end-to-end DQN decision model is constructed.Finally,the effectiveness of the proposed method was verified through simulation experiments.
万方数据
维普
