Journal
IEEE SYSTEMS JOURNAL
Volume 17, Issue 3, Pages 4070-4077Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSYST.2023.3269095
Keywords
Data collection; Data communication; Schedules; Navigation; Autonomous aerial vehicles; Indexes; Data models; Collision avoidance; data collection; path planning; reconfigurable intelligent surface (RIS); sensor networks; uneven terrain; unmanned aerial vehicles (UAVs)
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This article discusses a time-constrained data collection problem from a network of ground sensors mounted on a nonflat terrain by several unmanned aerial vehicles (UAVs). Ground-based reconfigurable intelligent surfaces (RISs) are used to make data collection more effective. A model-predictive-control-based algorithm for UAVs navigation and data transmission is developed to maximize the amount of data sent to the UAVs within short times and minimize the energy expenditure.
This article considers a time-constrained data collection problem from a network of ground sensors mounted on a nonflat terrain by several unmanned aerial vehicles (UAVs). On an uneven terrain, the line-of-sight (LoS) from the sensors to the UAVs is often occluded. Ground-based reconfigurable intelligent surfaces (RISs) are used to make data collection more effective. Data are transmitted to the UAVs either directly or through the RISs. A model-predictive-control-based algorithm for UAVs navigation and data transmission is developed. The algorithm fully addresses the issue of an uneven terrain. It maximizes the amount of data sent to the UAVs within relatively short times and minimizes the energy expenditure of all the UAVs by establishing LoS connection directly or via RISs as often as possible. We present a mathematically rigorous proof of the optimality of the proposed method.
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