RIS assisted energy efficiency optimization mechanism in UAV edge computing system supporting wireless energy supply

YU Xueyong; SONG Jianing; ZHU Hongbo; ZHANG Ludan; WANG Dagang

doi:10.11959/j.issn.2096-3750.2025.00394

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RIS assisted energy efficiency optimization mechanism in UAV edge computing system supporting wireless energy supply

Theory and Technology | 更新时间：2026-01-26

- RIS assisted energy efficiency optimization mechanism in UAV edge computing system supporting wireless energy supply
- Chinese Journal on Internet of Things Vol. 9, Issue 3, Pages: 73-82(2025)
- 作者机构：
  
  1.江苏省无线通信与物联网省高校重点实验室，江苏南京 210003
  2.南京邮电大学教育部泛在网络健康服务系统工程研究中心，江苏南京 210003
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(92067201);The Jiangsu Provincial Key Research and Development Program(BE2020084-4)
- DOI：10.11959/j.issn.2096-3750.2025.00394
  CLC： TP929.5
- Received：19 December 2023，
  
  Revised：2025-04-23，
  
  Published：10 September 2025
- 稿件说明：
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余雪勇,宋家宁,朱洪波等.RIS辅助下支持无线供能的无人机边缘计算网络的能效优化机制[J].物联网学报,2025,09(03):73-82.

YU Xueyong,SONG Jianing,ZHU Hongbo,et al.RIS assisted energy efficiency optimization mechanism in UAV edge computing system supporting wireless energy supply[J].Chinese Journal on Internet of Things,2025,09(03):73-82.
余雪勇,宋家宁,朱洪波等.RIS辅助下支持无线供能的无人机边缘计算网络的能效优化机制[J].物联网学报,2025,09(03):73-82. DOI： 10.11959/j.issn.2096-3750.2025.00394.

YU Xueyong,SONG Jianing,ZHU Hongbo,et al.RIS assisted energy efficiency optimization mechanism in UAV edge computing system supporting wireless energy supply[J].Chinese Journal on Internet of Things,2025,09(03):73-82. DOI： 10.11959/j.issn.2096-3750.2025.00394.

摘要

在终端将任务卸载至无人机（UAV

unmanned aerial vehicle）的过程中，密集的建筑物可能导致信号衰减、多径传播和信号阻塞等问题，从而影响终端的卸载速率。为了应对这一挑战，引入智能反射面（RIS

reconfigurable intelligent surface）以改善信道质量并提高任务卸载速率。首先，考虑RIS是无源器件且终端能量有限，创新性地提出无人机基于射频（RF

radio frequency）信号的能量波束为终端和RIS充电；其次，通过联合优化上下行波束成形矩阵、UAV轨迹以及任务卸载速率，研究RIS辅助UAV无线供电的边缘计算网络的能效问题。在此基础上，基于半正定松弛法（SDR

semi-definite relaxation）和逐次凸逼近（SCA

successive convex approximation）的块坐标下降算法求解该优化问题。仿真结果表明，所提优化策略在满足地面终端卸载需求的同时，有效平衡了能耗供给与任务卸载能耗之间的关系，提高了终端设备的能量效率。

Abstract

During the process of offloading tasks from devices to the UAVs

tall buildings can cause issues such as signal attenuation

multipath propagation

and signal blockage

thereby impacting the task offloading rate of devices. To address this challenge

the RIS was introduced to improve channel quality and enhance task offloading rates. It is worth noting that RIS operates without its own energy source and user energy resources are limited. To overcome this energy constraint

UAV employing RF signal-based energy transmission beams to recharge both devices and RIS was proposed. Secondly

an energy-efficient optimization strategy for RIS-enhanced wireless powered MEC network was proposed by jointly optimizing downlink and uplink phase beamforming

UAV trajectories

and task offloading rates. Building upon this foundation

a block coordinate descent (BCD) algorithm that combines semi-definite relaxation (SDR) and successive convex approximation (SCA) techniques was introduced. The extensive simulation results validate the effectiveness of the proposed optimization strategy in achieving a great balance between energy supply and task offloading energy consumption while meeting the task offloading requirements of ground terminals

thus enhancing the overall energy efficiency of the network.

关键词

Keywords

references

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