基于NOMA的超密集MEC网络任务卸载和资源分配方案

绳韵; 许晨; 郑光远

doi:10.11959/j.issn.1000-0801.2022033

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基于NOMA的超密集MEC网络任务卸载和资源分配方案

研究与开发 | 更新时间：2024-06-05

- 基于NOMA的超密集MEC网络任务卸载和资源分配方案
- Task offloading and resource allocation in NOMA-based ultra-dense MEC networks
- 电信科学 2022年38卷第2期页码：35-46
- 作者机构：
  
  1. 华北电力大学电气与电子工程学院，北京 102206
  2. 北京邮电大学人工智能学院，北京 100876
  3. 华南理工大学电子与信息学院，广东广州 510641
- 作者简介：
  
  [ "绳韵（1998- ），女，华北电力大学电气与电子工程学院硕士生，主要研究方向为移动边缘计算网络中的资源管理" ]
  [ "许晨（1988- ），女，博士，北京邮电大学人工智能学院副研究员、博士生导师，主要研究方向为智能网络优化、协作通信与计算、未来移动通信系统" ]
  [ "郑光远（1996- ），男，华南理工大学电子与信息学院博士生，主要研究方向为移动边缘计算网络中的资源分配、能量管理和干扰管理" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(62071179);北京市科技新星计划项目;The Beijing Nova Program of Science and Technology(Z191100001119124);中央高校基本科研业务费专项资金资助项目;The Fundamental Research Funds for the Central Universities(2019MS009)
- DOI：10.11959/j.issn.1000-0801.2022033
  中图分类号： TN929.5
- 网络出版日期：2022-02，
  
  纸质出版日期：2022-02-20
- 稿件说明：
移动端阅览
绳韵, 许晨, 郑光远. 基于NOMA的超密集MEC网络任务卸载和资源分配方案[J]. 电信科学, 2022,38(2):35-46.

Yun SHENG, Chen XU, Guangyuan ZHENG. Task offloading and resource allocation in NOMA-based ultra-dense MEC networks[J]. Telecommunications science, 2022, 38(2): 35-46.
绳韵, 许晨, 郑光远. 基于NOMA的超密集MEC网络任务卸载和资源分配方案[J]. 电信科学, 2022,38(2):35-46. DOI： 10.11959/j.issn.1000-0801.2022033.

Yun SHENG, Chen XU, Guangyuan ZHENG. Task offloading and resource allocation in NOMA-based ultra-dense MEC networks[J]. Telecommunications science, 2022, 38(2): 35-46. DOI： 10.11959/j.issn.1000-0801.2022033.

摘要

为了提高移动边缘计算（mobile edge computing，MEC）网络的频谱效率，满足大量用户的服务需求，建立了基于非正交多址接入（non-orthogonal multiple access，NOMA）的超密集MEC系统模型。为了解决多个用户同时卸载带来的严重通信干扰等问题，以高效利用边缘服务器资源，提出了一种联合任务卸载和资源分配的优化方案，在满足用户服务质量的前提下最小化系统总能耗。该方案联合考虑了卸载决策、功率控制、计算资源和子信道资源分配。仿真结果表明，与其他卸载方案相比，所提方案可以在满足用户服务质量的前提下有效降低系统能耗。

Abstract

In order to improve spectrum efficiency and meet the service demands of massive users

a non-orthogonal multiple access (NOMA)-based ultra-dense mobile edge computing (MEC) system was considered.In order to solve the serious communication interference caused by simultaneous offloading of multiple users and make efficient use of edge server resources

a joint task offloading and resource allocation scheme was proposed to minimize the system energy consumption while meeting the quality of service (QoS) of all users.Offloading decision

power control

computation resource and subchannel resource allocation were jointly considered in the proposed scheme.Simulations results show that the proposed scheme can efficiently lower system energy consumption compared to the other offloading schemes.

关键词

Keywords

references

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