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Energy Minimization for Wireless Communication With Rotary-Wing UAV

IEEE Transactions on Wireless Communications · 2019 · Vol. 18(4) · pp. 2329–2345
Yong ZengJie XuRui Zhang

Abstract

This paper studies unmanned aerial vehicle (UAV)-enabled wireless communication, where a rotary-wing UAV is dispatched to communicate with multiple ground nodes (GNs). We aim to minimize the total UAV energy consumption, including both propulsion energy and communication related energy, while satisfying the communication throughput requirement of each GN. To this end, we first derive a closed-form propulsion power consumption model for rotary-wing UAVs, and then formulate the energy minimization problem by jointly optimizing the UAV trajectory and communication time allocation among GNs, as well as the total mission completion time. The problem is difficult to be optimally solved, as it is non-convex and involves infinitely many variables over time. To tackle this problem, we first consider the simple fly-hover-communicate design, where the UAV successively visits a set of hovering locations and communicates with one corresponding GN while hovering at each location. For this design, we propose an efficient algorithm to optimize the hovering locations and durations, as well as the flying trajectory connecting these hovering locations, by leveraging the travelling salesman problem with neighborhood and convex optimization techniques. Next, we consider the general case, where the UAV also communicates while flying. We propose a new path discretization method to transform the original problem into a discretized equivalent with a finite number of optimization variables, for which we obtain a high-quality suboptimal solution by applying the successive convex approximation technique. The numerical results show that the proposed designs significantly outperform the benchmark schemes.

UAV Applications and OptimizationDistributed Control Multi-Agent SystemsMobile Ad Hoc NetworksComputer scienceBenchmark (surveying)Energy consumptionMathematical optimizationWirelessDiscretizationPropulsionTrajectoryThroughputConvex optimization

Funding

  • National Natural Science Foundation of China
  • Southeast University
  • Australian Research Council
Citations
1,984
FWCI
1556.54
field-weighted impact
References
42
Percentile
100%
vs. same field & year
Citations per year
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References
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Unmanned Aerial Vehicle With Underlaid Device-to-Device Communications: Performance and Tradeoffs
IEEE Transactions on Wireless Communications · 2016 · 1,111 citations
Throughput Maximization for UAV-Enabled Mobile Relaying Systems
IEEE Transactions on Communications · 2016 · 1,341 citations
Energy-Efficient UAV Communication With Trajectory Optimization
IEEE Transactions on Wireless Communications · 2017 · 2,091 citations
Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks
IEEE Transactions on Wireless Communications · 2018 · 1,961 citations
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IEEE Transactions on Wireless Communications · 2018 · 611 citations
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