IRS和WPT辅助的UAV边缘计算网络性能优化OA

To address the issues of degraded communication quality,reduced task offloading performance,and constrained computational efficiency in unmanned aerial vehicle(UAV)edge computing networks caused by poor communication conditions and limited wireless device energy when terrestrial wireless infrastructure fails,supported by intelligent reflecting surface(IRS)and wireless power transfer(WPT)technologies,UAV edge computing networks were studied,and corresponding optimization schemes were proposed.On the one hand,by adopting IRS technology,the communication quality of wireless links was optimized through real-time adjustment of the reflected signal phase to direct signals toward the target,thereby improving the task offloading capability.On the other hand,WPT technology was used to supply temporary energy to wireless devices,providing power support for them to execute computation tasks.Under this network,through an iterative optimization method,the spectrum resources,CPU frequencies and transmitting power of wireless devices,time allocation between WPT and task offloading,IRS coefficients,and UAV flying trajectory were analyzed and derived,and the network's computation rate was optimized.The simulation results verify that the proposed scheme effectively improves the overall computing performance of the network.In terms of computation rate,the proposed scheme outperforms various UAV flying schemes by at least 34.3%,various task processing mechanisms by at least 15.3%,and different optimization schemes by at least 15.9%.The above results demonstrate that the proposed scheme can significantly improve the edge computing performance in UAV scenarios and can provide an efficient and reliable solution for wireless device energy supply and collaborative computation task processing in UAV edge computing network.