Scinovex
articleTop 1% cited

Throughput Maximization for UAV-Enabled Mobile Relaying Systems

IEEE Transactions on Communications · 2016 · Vol. 64(12) · pp. 4983–4996
Yong ZengRui ZhangTeng Joon Lim

Abstract

In this paper, we consider a novel mobile relaying technique, where the relay nodes are mounted on unmanned aerial vehicles (UAVs) and hence are capable of moving at high speed. Compared with conventional static relaying, mobile relaying offers a new degree of freedom for performance enhancement via careful relay trajectory design. We study the throughput maximization problem in mobile relaying systems by optimizing the source/relay transmit power along with the relay trajectory, subject to practical mobility constraints (on the UAV's speed and initial/final relay locations), as well as the information-causality constraint at the relay. It is shown that for the fixed relay trajectory, the throughput-optimal source/relay power allocations over time follow a “staircase” water filling structure, with non-increasing and non-decreasing water levels at the source and relay, respectively. On the other hand, with given power allocations, the throughput can be further improved by optimizing the UAV's trajectory via successive convex optimization. An iterative algorithm is thus proposed to optimize the power allocations and relay trajectory alternately. Furthermore, for the special case with free initial and final relay locations, the jointly optimal power allocation and relay trajectory are derived. Numerical results show that by optimizing the trajectory of the relay and power allocations adaptive to its induced channel variation, mobile relaying is able to achieve significant throughput gains over the conventional static relaying.

Cooperative Communication and Network CodingAdvanced Wireless Communication TechnologiesUAV Applications and OptimizationRelayThroughputComputer scienceTrajectoryTransmitter power outputTrajectory optimizationMaximizationPower (physics)Relay channelConstraint (computer-aided design)
Citations
1,341
FWCI
134.22
field-weighted impact
References
42
Percentile
100%
vs. same field & year
Citations per year
Cited by
Mobile Edge Computing via a UAV-Mounted Cloudlet: Optimization of Bit Allocation and Path Planning
IEEE Transactions on Vehicular Technology · 2017 · 801 citations
UAV-Enabled Wireless Power Transfer: Trajectory Design and Energy Optimization
IEEE Transactions on Wireless Communications · 2018 · 611 citations
Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks
IEEE Transactions on Wireless Communications · 2018 · 1,961 citations
Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond
Proceedings of the IEEE · 2019 · 1,491 citations
Joint Computation and Communication Design for UAV-Assisted Mobile Edge Computing in IoT
IEEE Transactions on Industrial Informatics · 2019 · 424 citations
Energy Minimization for Wireless Communication With Rotary-Wing UAV
IEEE Transactions on Wireless Communications · 2019 · 1,984 citations
References
User cooperation diversity-part II: implementation aspects and performance analysis
IEEE Transactions on Communications · 2003 · 2,796 citations
Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies
IEEE Journal on Selected Areas in Communications · 2011 · 1,126 citations
User cooperation diversity-part I: system description
IEEE Transactions on Communications · 2003 · 6,316 citations
Cooperative Diversity in Wireless Networks: Efficient Protocols and Outage Behavior
IEEE Transactions on Information Theory · 2004 · 12,284 citations
Capacity theorems for the relay channel
IEEE Transactions on Information Theory · 1979 · 4,178 citations
Citation Network

How this paper connects to the literature. Drag to explore, click any node to open that paper.