无线供能智能反射面辅助移动边缘计算系统设计与优化

唐冬; 黄栩蔚; 罗至威; 赵赛; 黄高飞

doi:10.11959/j.issn.1000-436x.2023165

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无线供能智能反射面辅助移动边缘计算系统设计与优化

学术论文 | 更新时间：2024-06-06

- 无线供能智能反射面辅助移动边缘计算系统设计与优化
- Design and optimization for wireless-powered IRS-aided mobile edge computing system
- 通信学报 2023年44卷第9期页码：79-92
- 作者机构：
  
  广州大学电子与通信工程学院，广东广州 510006
- 作者简介：
  
  [ "唐冬（1967- ），男，辽宁大连人，博士，广州大学教授，主要研究方向为中继通信与信号能量同传、移动边缘计算、环境散射与智能反射面通信等" ]
  [ "黄栩蔚（1998- ），男，广东汕头人，广州大学硕士生，主要研究方向为无线边缘计算和智能反射面辅助通信技术" ]
  [ "罗至威（1997- ），男，广东梅州人，广州大学硕士生，主要研究方向为无线边缘计算和NOMA无线通信" ]
  [ "赵赛（1981- ），女，湖南衡阳人，博士，广州大学副教授、硕士生导师，主要研究方向为无线协作通信、非正交多址接入技术、智能反射面通信技术等" ]
  [ "黄高飞（1978- ），男，广东信宜人，博士，广州大学教授，主要研究方向为无线边缘计算、无线能量与信息同传、无人机通信技术等" ]
- 基金信息：
  
  国家重点研发计划基金资助项目(2021YFB2012403);国家自然科学基金资助项目(61872098);国家自然科学基金资助项目(61902084)
- DOI：10.11959/j.issn.1000-436x.2023165
  中图分类号： TN92
- 网络首发：2023-09，
  
  纸质出版：2023-09-25
- 稿件说明：
移动端阅览
唐冬, 黄栩蔚, 罗至威, 等. 无线供能智能反射面辅助移动边缘计算系统设计与优化[J]. 通信学报, 2023,44(9):79-92.

Dong TANG, Xuwei HUANG, Zhiwei LUO, et al. Design and optimization for wireless-powered IRS-aided mobile edge computing system[J]. Journal on Communications, 2023, 44(9): 79-92.
唐冬, 黄栩蔚, 罗至威, 等. 无线供能智能反射面辅助移动边缘计算系统设计与优化[J]. 通信学报, 2023,44(9):79-92. DOI： 10.11959/j.issn.1000-436x.2023165.

Dong TANG, Xuwei HUANG, Zhiwei LUO, et al. Design and optimization for wireless-powered IRS-aided mobile edge computing system[J]. Journal on Communications, 2023, 44(9): 79-92. DOI： 10.11959/j.issn.1000-436x.2023165.

摘要

研究了一种智能反射面（IRS）辅助移动边缘计算系统的新设计方案，该系统由一个配备边缘计算服务器的混合接入点（HAP）、一个配备射频能量收集电路的 IRS 和一个具有随机任务到达的用户端组成。为节省用户端能耗，首先提出了一种新颖的协议，使系统可以根据信道状态信息、IRS电池的能量状态与用户任务队列状态，自适应地在能量收集模式、IRS辅助任务卸载模式和IRS待机任务卸载模式中选择一种合适的工作模式。然后，基于该协议，建立了系统的优化问题，在给定IRS电池的能量状态与用户任务队列的稳定性约束条件下，通过优化系统工作模式和每种模式下的资源分配，最小化用户端的任务卸载与计算能耗。通过利用李雅普诺夫（Lyapunov）优化方法，对该问题进行了求解，从而得到了一种高效的低复杂度优化算法。仿真结果表明，所提方案比已有的基准方案可节省50%～90%的能耗。

Abstract

A new design of intelligent reflecting surface (IRS)-aided mobile edge computing (MEC) system was studied

which consisted of a hybrid access point (HAP) connected with an MEC server

an IRS equipped with radio-frequency (RF) energy harvesting (EH) circuits

and a user side with random task arrival.To reduce energy consumption at the user

a novel protocol was proposed first

in which the system was enabled to select a proper operation mode among an EH mode

an IRS-aided task offloading mode

and an IRS-inactive task offloading mode.Then

based on the proposed protocol

an optimization problem was formulated

which aimed at minimizing the amount of consumed energy at the user by optimizing the selection of system operation mode and the resource allocation in each mode.Lyapunov optimization framework was employed to solve the problem to achieve a low-complexity and efficient optimization algorithm.Simulation results show that the proposed scheme can save 50% to 90% of energy consumption for the MEC system as compared with the existing baseline schemes.

关键词

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references

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