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Article

Multi-UAV Enabled Data Collection with Efficient Joint Adaptive Interference Management and Trajectory Design

School of Electronic and Information, Beijing Institute of Technology, Beijing 100081, China
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Academic Editor: Sang-Woon Jeon
Electronics 2021, 10(5), 547; https://doi.org/10.3390/electronics10050547
Received: 13 January 2021 / Revised: 17 February 2021 / Accepted: 22 February 2021 / Published: 26 February 2021
(This article belongs to the Special Issue Advanced Communication Techniques for 5G and Internet of Things)
This paper studies interference in a data collection scenario in which multiple unmanned aerial vehicles (UAVs) are dispatched to wirelessly collect data from a set of distributed sensors. To improve the communication throughput and minimize the completion time, we design a joint resource allocation and trajectory optimization framework that not only is compatible with the traditional time-division scheme and interference coordination scheme but also combines their advantages. First, we analyse a basic quasi-stationary scenario with two UAVs and four devices, in which the two UAVs hover at optimal displacements to execute the data collection mission, and it is proven that the proposed optimal resource allocation and trajectory solution is adaptively adjustable according to the severity of the interference and that the common throughput of the network is non-decreasing. Second, for the general mobile case, we design an efficient algorithm to jointly address resource allocation and trajectory optimization, in which we first apply the block coordinate descent method to decompose the original non-convex problem into three non-convex sub-problems and then employ a dedicated genetic algorithm, a penalty function and the sequential convex approximation (SCA) technique to efficiently solve the individual sub-problems and obtain a satisfactory locally optimal solution with an adaptive initialization scheme. Subsequently, numerical experiments are presented to demonstrate that the completion time of the data collection task with our proposed method is at least 25% shorter than those with several baseline dynamic orthogonal schemes when 4 UAVs are deployed. Finally, we provide a practical application principle concerning the maximum suitable number of UAVs to avoid the inherent deficiencies of the proposed algorithm. View Full-Text
Keywords: multiple UAV; data collection; joint resource and trajectory design; interference management multiple UAV; data collection; joint resource and trajectory design; interference management
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MDPI and ACS Style

Pi, W.; Zhou, J. Multi-UAV Enabled Data Collection with Efficient Joint Adaptive Interference Management and Trajectory Design. Electronics 2021, 10, 547. https://doi.org/10.3390/electronics10050547

AMA Style

Pi W, Zhou J. Multi-UAV Enabled Data Collection with Efficient Joint Adaptive Interference Management and Trajectory Design. Electronics. 2021; 10(5):547. https://doi.org/10.3390/electronics10050547

Chicago/Turabian Style

Pi, Weichao, and Jianming Zhou. 2021. "Multi-UAV Enabled Data Collection with Efficient Joint Adaptive Interference Management and Trajectory Design" Electronics 10, no. 5: 547. https://doi.org/10.3390/electronics10050547

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