To address the issue of limited computational power due to insufficient energy in mo-bile devices when handling complex tasks,a low-power unmanned aerial vehicle(UAV)back-scattering communication(BackCom)mobile edge computing(MEC)network optimization scheme is proposed.The scheme first establishes a non-convex problem based on the UAV and BackCom-assisted MEC system model,then decomposes the problem into multiple convex prob-lems using block coordinate descent(BCD).Dual solution,subgradient iteration and successive convex approximation(SCA)algorithm are adopted to optimize the UAV trajectory.Finally,the effectiveness of the proposed scheme is verified by simulation analysis for the resource allocation and UAV trajectory design.Simulation results show that the proposed scheme can maximize the user device storage and minimize the system energy consumption.
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