基于李雅普诺夫的RIS辅助无人机边缘计算网络中任务卸载与资源分配研究

邝祝芳; 郭宇敬; 邓晓衡

doi:10.11959/j.issn.1000-436x.2024155

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基于李雅普诺夫的RIS辅助无人机边缘计算网络中任务卸载与资源分配研究

学术通信 | 更新时间：2024-10-10

- 基于李雅普诺夫的RIS辅助无人机边缘计算网络中任务卸载与资源分配研究
- Research on task offloading and resource allocation in edge computing network of RIS assisted UAV based on Lyapunov
- 通信学报 2024年45卷第9期页码：258-273
- 作者机构：
  
  1.中南林业科技大学计算机与数学学院，湖南长沙 410004
  2.中南大学电子信息学院，湖南长沙 410083
- 作者简介：
  
  [ "邝祝芳（1982- ），男，湖南耒阳人，博士，中南林业科技大学教授、博士生导师，主要研究方向为物联网、边缘计算、大数据分析、人工智能。" ]
  [ "郭宇敬（1998- ），男，湖南邵阳人，中南林业科技大学硕士生，主要研究方向为物联网、边缘计算。" ]
  [ "邓晓衡（1974- ），男，湖南衡阳人，博士，中南大学教授、博士生导师，主要研究方向为物联网、边缘计算。" ]
- 基金信息：
  
  国家自然科学基金资助项目(62072477);国家重点研发计划基金资助项目(2023YFD2201703);湖南省自然科学基金资助项目(2024JJ5648);湖南省教育厅优秀青年基金资助项目(22C0132)
- DOI：10.11959/j.issn.1000-436x.2024155
  中图分类号： TP391
- 收稿日期：2024-04-16，
  
  修回日期：2024-07-01，
  
  纸质出版日期：2024-09-25
- 稿件说明：
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邝祝芳,郭宇敬,邓晓衡.基于李雅普诺夫的RIS辅助无人机边缘计算网络中任务卸载与资源分配研究[J].通信学报,2024,45(09):258-273.

KUANG Zhufang,GUO Yujing,DENG Xiaoheng.Research on task offloading and resource allocation in edge computing network of RIS assisted UAV based on Lyapunov[J].Journal on Communications,2024,45(09):258-273.
邝祝芳,郭宇敬,邓晓衡.基于李雅普诺夫的RIS辅助无人机边缘计算网络中任务卸载与资源分配研究[J].通信学报,2024,45(09):258-273. DOI： 10.11959/j.issn.1000-436x.2024155.

KUANG Zhufang,GUO Yujing,DENG Xiaoheng.Research on task offloading and resource allocation in edge computing network of RIS assisted UAV based on Lyapunov[J].Journal on Communications,2024,45(09):258-273. DOI： 10.11959/j.issn.1000-436x.2024155.

摘要

针对无人机（UAV）面对复杂时变的衰落信道对无线传输造成不利影响这一问题，构建了可重构智能表面（RIS）辅助UAV边缘计算网络中UAV轨迹、RIS相移、卸载时隙分配、CPU频率分配和用户设备（UE）传输功率的联合优化问题。为了求解构建的问题，对UE和UAV的任务队列稳定性约束进行转化，将多时隙随机性优化问题转化为每个时隙的确定性优化问题，提出了基于李雅普诺夫优化和块坐标下降（BCD）法的任务卸载与资源分配（JORL）方法。首先基于三角不等式求解RIS相移并求得闭合表达式；然后使用非凸转凸问题的技术求解卸载时隙分配、CPU频率分配和UE传输功率；最后基于连续凸近似方法求解UAV轨迹。仿真结果表明，JORL在保证任务队列稳定性和降低能耗方面有较优越的性能。

Abstract

To address the problem that unmanned aerial vehicle (UAV) face complex time-varying fading channels

which could affect wireless transmission

a joint optimization problem of UAV's trajectory

reconfigurable intelligent surface (RIS) phase shift

offloading slot allocation

CPU frequency allocation

and user equipment transmission power was constructed. In order to solve the constructed problem

the stability constraints of UE and UAV task queues were transformed

and the multi-timeslot stochastic optimization problem was transformed into a deterministic optimization problem for each time slot. A JORL optimization method based on Lyapunov optimization and block coordinate descent (BCD) method was proposed. Firstly

the phase shift of RIS was solved based on the triangle inequality and the closure expression was obtained. Then the technology of transforming the non-convex into the convex problem was used to solve the offloading slot allocation

CPU frequency allocation and user equipment transmission power. Finally

the trajectory of UAV was solved based on successive convex approximation (SCA) method. Simulation results show that JORL has better performance in ensuring queue stability and reducing energy consumption.

关键词

Keywords

references

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