Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Wireless Laser Power Transfer for Low-altitude Uncrewed Aerial Vehicle-assisted Internet of Things: Paradigms, Challenges, and Solutions

Chengzhen Li, Likun Zhang, Chuang Zhang, Jiahui Li, Changyuan Zhao, Ruichen Zhang, Geng Sun

TL;DR

The paper addresses the energy bottlenecks in low-altitude UAV-assisted IoT networks and proposes wireless laser power transfer (WLPT) as a scalable energy provisioning solution. It provides a principled analysis of WLPT, introduces three integration paradigms for UAV-IoT systems, and presents a MAPPO-TM multi-agent framework to coordinate charging and data collection. The key contributions include a detailed WLPT principles-and-advantages discussion, a paradigm taxonomy with practical application insights, and a MAPPO-TM case study demonstrating improvements in energy sustainability and data freshness. This work highlights the potential of WLPT to enable autonomous, resilient UAV-IoT operations and outlines directions for hardware, control, network integration, and safety in future deployments.

Abstract

Low-altitude uncrewed aerial vehicles (UAVs) have become integral enablers for the Internet of Things (IoT) by offering enhanced coverage, improved connectivity and access to remote areas. A critical challenge limiting their operational capacity lies in the energy constraints of both aerial platforms and ground-based sensors. This paper explores WLPT as a transformative solution for sustainable energy provisioning in UAV-assisted IoT networks. We first systematically investigate the fundamental principles of WLPT and analysis the comparative advantages. Then, we introduce three operational paradigms for system integration, identify key challenges, and discuss corresponding potential solutions. In case study, we propose a multi-agent reinforcement learning framework to address the coordination and optimization challenges in WLPT-enabled UAV-assisted IoT data collection. Simulation results demonstrate that our framework significantly improves energy sustainability and data freshness. Finally, we discuss some future directions.

Wireless Laser Power Transfer for Low-altitude Uncrewed Aerial Vehicle-assisted Internet of Things: Paradigms, Challenges, and Solutions

TL;DR

The paper addresses the energy bottlenecks in low-altitude UAV-assisted IoT networks and proposes wireless laser power transfer (WLPT) as a scalable energy provisioning solution. It provides a principled analysis of WLPT, introduces three integration paradigms for UAV-IoT systems, and presents a MAPPO-TM multi-agent framework to coordinate charging and data collection. The key contributions include a detailed WLPT principles-and-advantages discussion, a paradigm taxonomy with practical application insights, and a MAPPO-TM case study demonstrating improvements in energy sustainability and data freshness. This work highlights the potential of WLPT to enable autonomous, resilient UAV-IoT operations and outlines directions for hardware, control, network integration, and safety in future deployments.

Abstract

Low-altitude uncrewed aerial vehicles (UAVs) have become integral enablers for the Internet of Things (IoT) by offering enhanced coverage, improved connectivity and access to remote areas. A critical challenge limiting their operational capacity lies in the energy constraints of both aerial platforms and ground-based sensors. This paper explores WLPT as a transformative solution for sustainable energy provisioning in UAV-assisted IoT networks. We first systematically investigate the fundamental principles of WLPT and analysis the comparative advantages. Then, we introduce three operational paradigms for system integration, identify key challenges, and discuss corresponding potential solutions. In case study, we propose a multi-agent reinforcement learning framework to address the coordination and optimization challenges in WLPT-enabled UAV-assisted IoT data collection. Simulation results demonstrate that our framework significantly improves energy sustainability and data freshness. Finally, we discuss some future directions.

Paper Structure

This paper contains 19 sections, 3 figures.

Table of Contents

  1. Introduction
  2. Principles and Advantages of WLPT
  3. Principles of WLPT
  4. Advantages over Other WPT Methods
  5. WLPT for Low-altitude UAV-assisted IoT
  6. Paradigms of WLPT in Low-altitude UAV-assisted IoT
  7. Applications of WLPT in Low-altitude UAV-assisted IoT
  8. Challenges in WLPT for Low-altitude UAV-assisted IoT
  9. Solutions in WLPT for Low-altitude UAV-assisted IoT
  10. Case Study
  11. Scenario Description
  12. Proposed Framework
  13. Simulation Results
  14. Future Directions
  15. Miniaturization of High-Efficiency Photovoltaic Receivers
  16. ...and 4 more sections

Figures (3)

  • Figure 1: Principles, system architectures and application domains of major WPT technologies.
  • Figure 2: Paradigms, comparison and challenges of WLPT for low-altitude UAV-assisted IoT.
  • Figure 4: Performance Comparison. (a) Reward training curves in terms of different algorithms. (b) Peak AoI comparison of different algorithms under various laser-to-electricity conversion efficiencies. (c) Trajectory of UAVs controlled by MAPPO-TM.