UAV-Enabled Wireless-Powered Underground Communication Networks: A Novel Time Allocation Approach

2025-07-19

AI Summary

Wireless power transfer in underground environments faces severe signal attenuation and high overhead for channel state information (CSI) acquisition, hindering scalable deployment of wireless-powered underground communication networks (WPUCNs). Method: This paper proposes a UAV-assisted hybrid energy provisioning architecture that synergistically integrates ground access points and UAVs for joint energy supply. We formulate an optimization framework jointly designing UAV trajectory, time allocation, and multi-antenna beamforming. Crucially, we introduce a dual-mode beamforming strategy—supporting both full-CSI and CSI-free operation—to minimize UAV energy consumption while guaranteeing target data throughput. Results: Simulations demonstrate that the proposed hybrid scheme significantly outperforms conventional approaches across diverse antenna configurations, communication distances, and underground media properties. The CSI-free beamforming achieves the lowest UAV energy consumption, substantially improving overall system energy efficiency and operational sustainability.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Web Mining and Content Analysis: Content-based information diffusion
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

Wireless-powered underground communication networks (WPUCNs), which allow underground devices (UDs) to harvest energy from wireless signals for battery-free communication, offer a promising solution for sustainable underground monitoring. However, the severe wireless signal attenuation in challenging underground environments and the costly acquisition of channel state information (CSI) make large-scale WPUCNs economically infeasible in practice. To address this challenge, we introduce flexible unmanned aerial vehicles (UAVs) into WPUCNs, leading to UAV-enabled WPUCN systems. In this system, a UAV is first charged by a terrestrial hybrid access point (HAP), then flies to the monitoring area to wirelessly charge UDs. Afterwards, the UAV collects data from the UDs and finally returns to the HAP for data offloading. Based on the proposed UAV-enabled WPUCN system, we first propose its energy consumption model and a hybrid wireless energy transfer (WET) approach (i.e., UDs can harvest energy from both the HAP and the UAV) relying on full-CSI and CSI-free multi-antenna beamforming. Then, we formulate and address a time allocation problem to minimize the energy consumption of UAV, while ensuring that the throughput requirements of all UDs are met and all sensor data is offloaded. Through simulations of a realistic farming scenario, we demonstrate that the proposed hybrid WET approach outperforms other WET approaches, with performance gains influenced by the number of antennas, communication distance, number of UDs, and underground conditions. Additionally, under the optimized time allocation, we found that the proposed hybrid WET approach based on a CSI-free multi-antenna scheme achieves the lowest UAV's energy consumption among all WET mechanisms, thereby enabling sustainable underground monitoring in WPUCNs.

Problem

• Address severe signal attenuation in underground wireless communication.
• Reduce energy consumption in UAV-enabled underground networks.
• Optimize time allocation for efficient data and energy transfer.

Innovation

• UAV-enabled wireless-powered underground communication networks
• Hybrid WET approach with full-CSI and CSI-free beamforming
• Optimized time allocation minimizes UAV energy consumption