Optimal 3D Directional WPT Charging via UAV for 3D Wireless Rechargeable Sensor Networks

TL;DR

This paper addresses the complex problem of scheduling UAV-based directional wireless charging in 3D sensor networks, proposing a novel framework that guarantees optimality and outperforms existing algorithms.

Contribution

It introduces a systematic three-step framework, FELKH-3D, for 3D UAV charging scheduling, including a novel direction set generation method and an application of the Lin-Kernighan heuristic.

Findings

FELKH-3D outperforms classical algorithms in simulations.

The direction set generation guarantees minimal size and equivalence.

The framework effectively handles the complexity of 3D spatial distribution.

Abstract

The high mobility and flexible deployment capability of UAVs make them an impressive option for charging nodes in Wireless Rechargeable Sensor Networks (WRSNs) using Directional Wireless Power Transfer (WPT) technology. However, existing studies largely focus on 2D-WRSNs, lacking designs catering to real 3D-WRSNs. The spatial distribution characteristics of nodes in a 3D-WRSN further increase the complexity of the charging scheduling task, thus requiring a systematic framework to solve this problem. In this paper, we investigated the Directional UAV Charging Scheduling problem for 3D-WRSNs (DCS-3D) and established its NP-hard property, and then proposed a three-step framework named as directional charging scheduling algorithm using Functional Equivalent (FuncEqv) direction set and Lin-Kernighan heuristic (LKH) for 3D-WRSNs (FELKH-3D) to solve it. In FELKH-3D, the challenge of infinite charging direction space is solved by designing an algorithm generating a minimum-size direction set guaranteed to be FuncEqv to the infinite set of whole sphere surface, and the optimaility of the method was proved.To determine the optimal charging tour for the UAV, the LKH algorithm is employed.Simulation experiments demonstrated the superiority of FELKH-3D over other classical algorithms.