摘要
Abstract
This study focused on the efficiency optimization of unmanned aerial vehicle(UAV)communication systems in low altitude economies.By integrating big data and artificial intelligence technologies,a comprehensive solution based on trajectory planning,energy management,and communication protocol optimization was proposed.The experiment used high-performance computing devices,combined with multi environment data collection and deep reinforcement learning algorithms,to optimize the drone flight trajectory and communication strategy.The results showed that the optimized system performed significantly in terms of communication coverage,signal stability,and energy efficiency:communication delay was reduced by more than 15%,energy savings were increased by 15%compared to traditional methods,and the peak communication rate in fully autonomous mode reached 85 kb/s.Further research had proposed a method that combines dynamic demand forecasting and network strategy optimization by comparing and analyzing the average method and the modified queuing theory method.This provided theoretical support and practical guidance for the deployment of unmanned aerial vehicle communication in complex scenarios,and had high application value and social significance.关键词
人工智能技术/低空经济/无人机/通信系统效率优化Key words
artificial intelligence technology/low-altitude economy/UAV/optimization of communication system efficiency分类
信息技术与安全科学
