Toward Sustainable Subterranean mMTC: Space-Air-Ground-Underground Networks Powered by LoRaWAN and Wireless Energy Transfer

TL;DR

The paper addresses the challenge of sustainable massive machine-type communications in subterranean environments by proposing a space-air-ground-underground integrated network (SAGUIN) that leverages LoRaWAN and wireless energy transfer (WET). It articulates a multi-layer architecture integrating LEO satellites, high-altitude platforms, UAVs, terrestrial gateways, and underground devices to enable energy harvesting and data delivery in remote and post-disaster scenarios. Through a detailed pipeline-monitoring use case with 10k underground devices and a HAP relay to a LEO satellite, it demonstrates how joint optimization of LoRaWAN spread factor and WET duration can substantially extend device lifetimes, enabling large-scale underground monitoring. The study also identifies key challenges in channel modeling, CSI acquisition, coordination, scalability, and efficient WET operation, outlining future research directions toward practical SAGUIN deployment in subterranean settings.

Abstract

Wireless underground sensor networks (WUSNs), which enable real-time sensing and monitoring of underground resources by underground devices (UDs), hold great promise for delivering substantial social and economic benefits across various verticals. However, due to the harsh subterranean environment, scarce network resources, and restricted communication coverage, WUSNs face significant challenges in supporting sustainable massive machine-type communications (mMTC), particularly in remote, disaster-stricken, and hard-to-reach areas. To complement this, we conceptualize in this study a novel space-air-ground-underground integrated network (SAGUIN) architecture that seamlessly incorporates satellite systems, aerial platforms, terrestrial networks, and underground communications. On this basis, we integrate LoRaWAN and wireless energy transfer (WET) technologies into SAGUIN to enable sustainable subterranean mMTC. We begin by reviewing the relevant technical background and presenting the architecture and implementation challenges of SAGUIN. Then, we employ simulations to model a remote underground pipeline monitoring scenario to evaluate the feasibility and performance of SAGUIN based on LoRaWAN and WET technologies, focusing on the effects of parameters such as underground conditions, time allocation, LoRaWAN spread factor (SF) configurations, reporting periods, and harvested energy levels. Our results evidence that the proposed SAGUIN system, when combined with the derived time allocation strategy and an appropriate SF, can effectively extend the operational lifetime of UDs, thereby facilitating sustainable subterranean mMTC. Finally, we pinpoint key challenges and future research directions for SAGUIN.

Figures (4)

• Figure 1: Proposed SAGUIN system integrating LoRaWAN and WET solutions, where each UD harvests energy from aboveground hybrid stations and UAVs, and then utilizes this energy to communicate with various NTN platforms, including UAVs, HAPs, and LEO satellites. This system is applicable in urban, rural, and remote areas, as well as post-disaster regions, enabling various applications such as smart agriculture, underground pipeline monitoring, and post-disaster positioning.
• Figure 2: Simulated underground pipeline monitoring scenarios in Saudi Arabia and the corresponding system model, where each UD buried at a depth of $d_u$ harvests energy from UAVs and power beacons via WET during $T_w$ and utilizes the harvested energy to transmit a 10-byte packet to the HAP during $T_t$ within a reporting period of $T$.
• Figure 3: Average success probability $P_S$ and EPP across all UDs for various burial depths and VWC values as a function of LoRaWAN SF configurations.
• Figure 4: (a) Average lifetime over all UDs under different LoRaWAN SF configurations as a function of WET phase duration $T_w$; (b) Average lifetime of all UDs for two reporting periods versus the number of UDs at different harvested energy levels, considering the derived optimal SF configuration and time allocation, where $P_r = 0$ indicates that the UDs are powered solely by their pre-equipped batteries without WET.