A Novel Alternative Optimization Method for Joint Power and Trajectory Design in UAV-Enabled Wireless Network

Hongying Tang, Qingqing Wu, Jing Xu, Wen Chen, Baoqing Li

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

This correspondence aims to maximize the average throughput via the joint design of the transmit power and trajectory for unmanned aerial vehicle (UAV)-enabled network. The conventional way to tackle this problem is based on the alternating optimization (AO) method by iteratively updating power and trajectory until convergence, resulting in a non-convex trajectory subproblem which is difficult to deal with. To develop more efficient methods, we propose a novel AO method by incorporating both power and trajectory into an intermediate variable, and then iteratively updating power and the newly introduced variable. This novel variable transformation makes it easier to decompose the original problem into two convex subproblems, namely a throughput maximization subproblem and a feasibility subproblem. Consequently, both of these subproblems can be solved in a globally optimal fashion. We further propose a low-complexity algorithm for the feasibility subproblem by exploiting the alternating directional method of multipliers (ADMM), whose updating step is performed in closed-form solutions. Simulation results demonstrate that our proposed method reduces the computation time by orders of magnitude, while achieving higher performance than the conventional methods.

Original languageEnglish
Article number8828093
Pages (from-to)11358-11362
Number of pages5
JournalIEEE Transactions on Vehicular Technology
Volume68
Issue number11
DOIs
StatePublished - Nov 2019

Keywords

  • ADMM
  • Alternative optimization
  • joint power and trajectory design
  • throughput maximization
  • unmanned aerial vehicle

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