UAV-Aided Low Latency Multi-Access Edge Computing

Ye Yu, Xiangyuan Bu, Kai Yang, Hongyuan Yang*, Xiaozheng Gao, Zhu Han

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)

Abstract

As an emerging technique, unmanned aerial vehicle (UAV) aided multi-access edge computing (MEC) network has been improving the performance of the communication network. The novel architecture is beneficial for coverage, flexibility, and reliability. However, reducing network latency is a critical issue. In this paper, we design a UAV-aided network with a millimeter wave (mmWave) backhaul to achieve the multi-access edge computing. The routing problem is formulated and solved first to obtain the optimal routes through the ad hoc link for all users. Then, we formulate the joint trajectory design and resource allocation problem, which is a mixed-integer nonconvex programming, to minimize the network latency. Furthermore, we design a novel iterative algorithm framework to handle this challenging problem. In the outer loop, the proposed problem is separated into the primal problems and master problems by adopting generalized benders decomposition (GBD). In the inner loop, we design the algorithm to solve the continuous nonconvex primal problem by combining the alternating direction method of multipliers (ADMM), Dinkelbach algorithm, and successive convex approximation (SCA) algorithm. The simulation results demonstrate that our proposed algorithm framework is effective and feasible.

Original languageEnglish
Article number9399826
Pages (from-to)4955-4967
Number of pages13
JournalIEEE Transactions on Vehicular Technology
Volume70
Issue number5
DOIs
Publication statusPublished - May 2021

Keywords

  • UAV
  • generalized benders decomposition
  • mmWave
  • multi-access edge computing

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