Abstract
Due to their maneuverability, unmanned aerial vehicles (UAVs) have grown into a promising enabler of the Internet of Things (IoTs). In addition to the benefits of the bandwidth and communication quality of millimeter-wave (mmWave) systems, a UAV-aided mmWave multiple-input and multiple-output (MIMO) communication system is investigated in this paper for the data collection of IoT systems, in which single-antenna IoT devices are divided into several clusters, and the UAV aided mmWave base station (UAV-BS) collects data from each cluster using the time division scheme. The joint optimization of the beam selection, UAV trajectory, user clustering, power allocation and transmission duration is studied in this paper to improve the data collection efficiency. The solution of the problem is then given in three steps. Firstly, the incremental K-means clustering and ant colony optimization algorithm are utilized to handle the UAV trajectory planning and user clustering problem. Secondly, an incremental beam selection scheme is employed to ensure that all the devices in each cluster can communicate with the UAV. Thirdly, an iterative algorithm is proposed by alternately optimizing the power allocation and transmission duration of the IoT devices. Finally, the simulation results demonstrate the effectiveness of the proposed solution for the UAV-aided mmWave communication system.
Highlights
Unmanned aerial vehicles (UAVs) have been investigated in a wide range of applications, such as security monitoring, smart agriculture, aerial photography and cargo delivery [1]
The distances between the UAV and the ground devices could be adjusted by employing user clustering, which was mainly dependent on the coverage of the UAV and improved the performance of the wireless communication system
Taking the limitation of scattering in mmWave frequency into account [17], we assume that the air-to-ground links between the UAV aided mmWave base station (UAV-base station (BS)) and the devices are dominated by line-of-sight (LoS) channels
Summary
Unmanned aerial vehicles (UAVs) have been investigated in a wide range of applications, such as security monitoring, smart agriculture, aerial photography and cargo delivery [1]. Aiming to improve the efficiency of UAV-assisted data collection, several works have been proposed to optimize the UAV trajectory and the communication systems. We formulate a joint optimization problem of UAV trajectory planning, user clustering, beam selection, power allocation and transmission duration to maximize the data collection efficiency, subject to the practical energy constraints of IoT devices. With the UAV trajectory obtained by the incremental K-means clustering and ACO algorithm, an incremental beam selection algorithm for the UAV-BS is proposed to maximize the sum rate of the IoT devices. Based on the obtained UAV trajectory, user clusters and the selected beams, the allocations of the transmitting power and transmission duration of the UAV-BS are optimized by alternately optimizing the power allocation and transmission duration, aiming to maximize the data collection efficiency of the UAV-aided mmWave communication systems.
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