Optimization strategies in NOMA-based vehicle edge computing network

Jianbo DU; Nana XUE; Yan SUN; Jing JIANG; Shulei LI; Guangyue LU

doi:10.11959/j.issn.2096-3750.2021.00207

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Optimization strategies in NOMA-based vehicle edge computing network

Topic: Edge Intelligence and Fog Computing in IoT | 更新时间：2024-06-05

- Optimization strategies in NOMA-based vehicle edge computing network
- Chinese Journal on Internet of Things Vol. 5, Issue 1, Pages: 19-26(2021)
- 作者机构：
  
  1. 西安邮电大学陕西省信息通信网络及安全重点实验室，陕西西安 710071
  2. 天元瑞信通信技术股份有限公司，陕西西安 710121
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-3750.2021.00207
  CLC： TN92
- Published：30 March 2021，
  
  Published Online：2021-03，
- 稿件说明：
移动端阅览
JIANBO DU, NANA XUE, YAN SUN, et al. Optimization strategies in NOMA-based vehicle edge computing network. [J]. Chinese journal on internet of things, 2021, 5(1): 19-26.
DOI：

JIANBO DU, NANA XUE, YAN SUN, et al. Optimization strategies in NOMA-based vehicle edge computing network. [J]. Chinese journal on internet of things, 2021, 5(1): 19-26. DOI： 10.11959/j.issn.2096-3750.2021.00207.

摘要

目前，车载网络正面临着为车辆提供无处不在的连接和大量计算密集型、时延敏感型智能服务的挑战。为了应对这些挑战，非正交多址接入（NOMA

non-orthogonal multiple access）和移动边缘计算（MEC

mobile edge computing）被认为是两种较有前景的技术，它们分别允许多个车辆共享相同的无线资源以及在车辆边缘使用强大的边缘计算资源。在基于 NOMA 的车辆边缘计算网络中，在保证任务处理时延的情况下，提出了任务卸载、用户分簇、计算资源分配和发射功率控制的联合优化问题，使得任务处理成本最小化。由于所提出的问题难以解决，因此将其分解为子问题，并提出了低复杂度和易于实现的方法来解决。仿真结果表明，与其他基准算法相比，该算法在最小化成本方面表现良好。

Abstract

Nowadays

vehicular network is confronting the challenges to support ubiquitous connections and vast computation-intensive and delay-sensitive smart service for numerous vehicles.To address these issues

non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) are considered as two promising technologies by letting multiple vehicles to share the same wireless resources

and the powerful edge computing resources were adopted at the edge of vehicular wireless access network respectively.A NOMA-based vehicular edge computing network was studied.Under the condition of guaranteeing task processing delay

the joint optimization problem of task offloading

user clustering

computing resource allocation and transmission power control was proposed to minimize the task processing cost.Since the proposed problem was difficult to solve

it was divided into sub-problems

and a low-complexity and easy-to-implement method was proposed to solve it.The simulation results show that compared with other benchmark algorithms

the proposed algorithm performs well in minimizing costs.

关键词

边缘计算非正交多址接入车联网

Keywords

edge computingnon-orthogonal multiple accessvehicular network

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