Optimization of UAV Communication Network Efficiency Based on Deep Reinforcement Learning
With the widespread application of UAVs in various applications,the security,spectrum and energy efficiency of their communication networks have gradually become prominent.In this study,a joint optimization strategy based on deep reinforce-ment learning is proposed for UAV swarm communication networks.First,this paper builds a model that takes into account security threats,spectrum sharing,and energy consumption.Then,through deep reinforcement learning,this paper trains intelligent agents to dynamically select the best spectrum allocation and energy strategies to improve spectrum and energy efficiency while main-taining cybersecurity.Through a large number of simulation experiments,it shows that this method performs well in improving com-munication security,spectrum utilization and energy efficiency,and has obvious advantages over the traditional baseline and aver-age allocation DQN-wopa[15]method.
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