Sensor Network with Unmanned Aerial Vehicle-enabled Wireless Power Transfer: Optimal Clustering and Trajectory Designing

Abstract

In this work, we investigate the application of an unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) system in large-scale wireless sensor networks (WSNs). The specific research described in this paper can be divided into three parts. Firstly, it is well known that the energy consumption of WSNs and the limited-capacity battery of nodes lead to the limited lifetime of WSNs. To improve the lifetime of the WSNs, the UAV's optimal position and the optimal clustering scheme are determined using an improved differential evolution (DE) algorithm in multicluster scenarios. The corresponding energy consumption is determined by comparing different clustering schemes. Meanwhile, the shortest time for the UAV to charge nodes is determined by utilizing the proposed DE algorithm to search for the optimal charging location. Since the UAV usually acts as both a base station and an energy transmitter, the algorithm requires joint optimization of the clustering scheme and the UAV's charging location. Secondly, as the scale of WSNs increases, some areas will be in the "dead" state within the WSNs, which will greatly affect the performance. On the basis of the above studies, an improved local permutation algorithm is applied to plan an optimal path subject to the dormancy rate constraint in all regions. With the algorithm, the UAV needs to "rescue" the target region and charge regions along the path as much as possible. Finally, numerical results show that the optimized UAV trajectory can significantly improve the energy transmission efficiency, and the proposed optimal path planning improves the lifetime of WSNs.

Unmanned Aerial Vehicle 3D Trajectory Planning Based on Background of Complex Industrial Product Warehouse Inventory

“…At this stage, the algorithms to solve the UAV trajectory planning problem are mainly intelligent and accurate algorithms. (3,4) Taking the trajectory planning of UAVs as an example, Zhou et al (5) used Bezier curves to generate the trajectory of a quadrotor UAV, but they did not study the motion model. The establishment of the dynamic model has no practical application value, as mentioned by Cheng et al (6) Moreover, in related studies by Qian and Lei, (7) Gao et al, (8) Wang and Wang, (9) and Hu and Wu, (10) the traditional squid algorithm, fast-expanding random tree algorithm, traditional particle swarm optimization algorithm (PSO), and ant colony algorithm are not good enough for the convergence of the UAV trajectory planning problem, and the convergence speed is very low.…”

Application of Wireless Power Transfer Technologies for Soil Temperature Measurement System of Reinforced Soil Wall in Cold and Snowy Environments

“…(10) Studies are being conducted on the applicability of WPT systems to unmanned aerial vehicles (UAVs) in large-scale wireless sensor networks (WSNs) and as the power supply to railroad vehicles. (11) However, there has been little research on the application of WPT to the health monitoring of civil engineering structures such as those targeted in this study. (12,13) As an example of one such study, Shams and Ali reported an experiment where wireless power was transmitted to a rectenna buried in concrete or pavement materials.…”

WSN-Assisted UAV Trajectory Adjustment for Pesticide Drift Control

“… Assisting in locating the WSN nodes [ 25 , 26 , 27 ]. Performing wireless charging for the WSN nodes [ 28 , 29 , 30 ]. Dispersing the WSN nodes in large areas [ 31 ].…”