胡晗^{1, 2,,},
鲍楠¹,
凌章²,
沈乐²
1.南京邮电大学物联网学院 南京 210003
2.江苏省无线通信重点实验室 南京 210003
基金项目:国家自然科学基金(61871446, 61801244)，江苏省科技厅自然科学基金项目(BK20191378)，江苏省高等学校自然科学研究面上项目(18KJB510034)

详细信息

作者简介:胡晗：女，1985年生，副教授，研究方向为无线通信网络资源管理及优化等
鲍楠：女，1985年生，讲师，研究方向为异构网络资源优化及干扰抑制等
凌章：男，1993年生，硕士，研究方向为边缘计算及动态资源分配等
沈乐：男，1997年生，硕士生，研究方向为边缘计算及动态资源分配等

通讯作者:胡晗　han_h@njupt.edu.cn

中图分类号:TN929.5

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被引次数:0

出版历程

收稿日期:2020-10-20
修回日期:2021-04-29
网络出版日期:2021-11-10
刊出日期:2021-12-21

Fair Energy Efficiency Scheduling in NOMA-Based Mobile Edge Computing

Han HU^{1, 2,,},
Nan BAO¹,
Zhang LING²,
Le SHEN²
1. College of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
2. Jiangsu Key Laboratory of Wireless Communications, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
Funds:The National Natural Science Foundation of China (61871446, 61801244), The National Science Foundation Program of Jiangsu Province (BK20191378), The National Science Research Project of Jiangsu Higher Education Institutions (18KJB510034)


摘要
摘要:将移动边缘计算技术(MEC)与非正交多址技术(NOMA)结合，同时考虑公平性，该文研究了采用NOMA上行部分卸载的MEC系统公平能效问题。首先将基于公平函数的用户速率与功耗比值定义为公平能效函数，随后提出了两种公平能效调度准则下的能效调度算法，即最大化最小速率准则下DK-SCA算法及最大化系统能效准则下DK-SCALE算法，通过算法实现分别得到两种公平能效调度准则下用户最佳本地CPU处理频率及最佳传输功率。最后通过仿真表明，与基准方案相比，所提基于NOMA的部分卸载方案能够有效地将本地计算和基于NOMA的边缘卸载结合，达到最佳的公平能效性能。
关键词:边缘计算/
计算卸载/
NOMA/
能效/
公平
Abstract:Combing Mobile Edge Computing (MEC) and Non-Orthogonal Multiple Access (NOMA) technologies while considering fairness, this paper studies the fair energy efficiency of the MEC system using NOMA partial offloading. First, the ratio of user rate to power consumption based on the fair function is defined as the fair energy efficiency function. Then, two energy efficiency scheduling algorithms under the fair energy efficiency scheduling criteria are proposed, namely the DK-SCA algorithm under the maximum-minimum rate criterion and the DK-SCALE algorithm under the maximum system energy efficiency criterion. The optimal CPU-frequency cycle and optimal transmit power under these two fair energy efficiency scheduling criteria are obtained, respectively. Finally, simulations show that compared with the benchmark schemes, the proposed NOMA -based partial offloading scheme can effectively combine local computing with edge offloading based on NOMA, which can achieve the best fair energy efficiency performance.
Key words:Edge computing/
Computing offloading/
Non-Orthogonal Multiple Access (NOMA)/
Energy efficiency/
Fair



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