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Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks

IEEE Transactions on Wireless Communications · 2018 · Vol. 17(3) · pp. 2109–2121
Qingqing WuYong ZengRui Zhang

Abstract

Due to the high maneuverability, flexible deployment, and low cost, unmanned aerial vehicles (UAVs) have attracted significant interest recently in assisting wireless communication. This paper considers a multi-UAV enabled wireless communication system, where multiple UAV-mounted aerial base stations are employed to serve a group of users on the ground. To achieve fair performance among users, we maximize the minimum throughput over all ground users in the downlink communication by optimizing the multiuser communication scheduling and association jointly with the UAV's trajectory and power control. The formulated problem is a mixed integer nonconvex optimization problem that is challenging to solve. As such, we propose an efficient iterative algorithm for solving it by applying the block coordinate descent and successive convex optimization techniques. Specifically, the user scheduling and association, UAV trajectory, and transmit power are alternately optimized in each iteration. In particular, for the nonconvex UAV trajectory and transmit power optimization problems, two approximate convex optimization problems are solved, respectively. We further show that the proposed algorithm is guaranteed to converge. To speed up the algorithm convergence and achieve good throughput, a low-complexity and systematic initialization scheme is also proposed for the UAV trajectory design based on the simple circular trajectory and the circle packing scheme. Extensive simulation results are provided to demonstrate the significant throughput gains of the proposed design as compared to other benchmark schemes.

UAV Applications and OptimizationAdvanced Wireless Communication TechnologiesDistributed Control Multi-Agent SystemsComputer scienceCoordinate descentTrajectory optimizationScheduling (production processes)Transmitter power outputOptimization problemInitializationWirelessBenchmark (surveying)Telecommunications link

Funding

  • National University of Singapore
Citations
1,961
FWCI
2060.72
field-weighted impact
References
33
Percentile
100%
vs. same field & year
Citations per year
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References
Unmanned Aerial Vehicle With Underlaid Device-to-Device Communications: Performance and Tradeoffs
IEEE Transactions on Wireless Communications · 2016 · 1,111 citations
Mobile Edge Computing via a UAV-Mounted Cloudlet: Optimization of Bit Allocation and Path Planning
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