Energy Efficient Resource Allocation in UAV-Enabled Mobile Edge Computing Networks

Research output: Contribution to journalArticle

DOI

Authors

  • Zhaohui Yang
  • Cunhua Pan
  • Kezhi Wang
  • Mohammad Shikh-Bahaei

External departments

  • King's College London
  • Queen Mary University of London

Details

Original languageEnglish
Pages (from-to)4576-4589
Number of pages14
JournalIEEE Transactions on Wireless Communications
Volume18
Issue number9
Early online date16 Jul 2019
DOIs
Publication statusPublished - 1 Sep 2019
Publication type

Research output: Contribution to journalArticle

Abstract

In this paper, we consider the sum power minimization problem via jointly optimizing user association, power control, computation capacity allocation, and location planning in a mobile edge computing (MEC) network with multiple unmanned aerial vehicles (UAVs). To solve the nonconvex problem, we propose a low-complexity algorithm with solving three subproblems iteratively. For the user association subproblem, the compressive sensing-based algorithm is accordingly proposed. For the computation capacity allocation subproblem, the optimal solution is obtained in closed form. For the location planning subproblem, the optimal solution is effectively obtained via one-dimensional search method. To obtain a feasible solution for this iterative algorithm, a fuzzy c-means clustering-based algorithm is proposed. The numerical results show that the proposed algorithm achieves better performance than the conventional approaches.

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