Resource Allocation Strategy of Power Communication Network Based on Enhanced Q-Learning

In order to improve the application efficiency of power communication network resources, improve communication service quality, reduce data transmission delay and improve the utilization of network resources. Firstly, the business and quality of service requirements of power communication network are analyzed. Based on multi-agent collaborative decision algorithm, a Markov decision model for power communication network resource allocation is constructed, and an enhanced Q-Learning algorithm for this model is proposed. Simulation results show that the proposed algorithm can effectively improve network data throughput and reduce network data transmission delay.