基于NOMA的车辆边缘计算网络优化策略

doi:10.11959/j.issn.2096-3750.2021.00207

Abstract

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.

Key words: edge computing, non-orthogonal multiple access, vehicular network

CLC Number:

TN92

Jianbo DU, Nana XUE, Yan SUN, Jing JIANG, Shulei LI, Guangyue LU. Optimization strategies in NOMA-based vehicle edge computing network[J]. Chinese Journal on Internet of Things, 2021, 5(1): 19-26.

Figures/Tables 6

References 25

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