TY - JOUR
T1 - Performance analysis of LoRaWAN underground-to-satellite connectivity
T2 - An urban underground pipelines monitoring case study
AU - Lin, Kaiqiang
AU - Ullah, Asad
AU - Lei, Lei
AU - Alves, Hirley
AU - Mikhaylov, Konstantin
AU - Hao, Tong
PY - 2025/3/15
Y1 - 2025/3/15
N2 - Urban underground pipelines (UUPs) serve the cardiovascular system of our society and the cornerstone of various smart city and industrial applications. Although the leakage of UUPs can be effectively detected and localized by utilizing the measurements of different types of sensors, the reliable transmission of sensor data remains challenging in large-scale UUPs monitoring due to the harsh underground conditions and the complex urban environments. Motivated by recent successful integration of LoRaWAN and satellites, we investigate in this study the feasibility of the massive machine-type communication (mMTC) based sensing approach, which utilizes the underground-to-satellite (UtS) connectivity for monitoring large-scale UUPs. Specifically, we consider two alternative network architectures, i.e., underground direct-to-satellite (U-DtS) and underground indirect-to-satellite (U-ItS), and discuss their pros, cons, and trade-offs. To assess the feasibility and performance of U-ItS and UtS in large-scale UUPs monitoring, we develop the Monte Carlo UtS simulator, featuring realistic UUPs deployments, regional LoRaWAN configurations, semi-empirical propagation models, two gateway deployment approaches, and data aggregation for U-ItS. Our results reveal that U-DtS fails to counter underground propagation losses and shadowing effects in urban environments. However, U-ItS is demonstrated as a promising solution for the reliable wireless monitoring of UUPs, whose performance can be further improved by utilizing data aggregation. Finally, we verify that the transmission success probability of U-DtS and U-ItS is strongly affected by the underground parameters, i.e., the burial depth of devices and the volumetric water content of soil.
AB - Urban underground pipelines (UUPs) serve the cardiovascular system of our society and the cornerstone of various smart city and industrial applications. Although the leakage of UUPs can be effectively detected and localized by utilizing the measurements of different types of sensors, the reliable transmission of sensor data remains challenging in large-scale UUPs monitoring due to the harsh underground conditions and the complex urban environments. Motivated by recent successful integration of LoRaWAN and satellites, we investigate in this study the feasibility of the massive machine-type communication (mMTC) based sensing approach, which utilizes the underground-to-satellite (UtS) connectivity for monitoring large-scale UUPs. Specifically, we consider two alternative network architectures, i.e., underground direct-to-satellite (U-DtS) and underground indirect-to-satellite (U-ItS), and discuss their pros, cons, and trade-offs. To assess the feasibility and performance of U-ItS and UtS in large-scale UUPs monitoring, we develop the Monte Carlo UtS simulator, featuring realistic UUPs deployments, regional LoRaWAN configurations, semi-empirical propagation models, two gateway deployment approaches, and data aggregation for U-ItS. Our results reveal that U-DtS fails to counter underground propagation losses and shadowing effects in urban environments. However, U-ItS is demonstrated as a promising solution for the reliable wireless monitoring of UUPs, whose performance can be further improved by utilizing data aggregation. Finally, we verify that the transmission success probability of U-DtS and U-ItS is strongly affected by the underground parameters, i.e., the burial depth of devices and the volumetric water content of soil.
KW - Data aggregation
KW - LoRaWAN
KW - Underground-to-satellite connectivity
KW - Urban underground pipelines monitoring
UR - http://www.scopus.com/inward/record.url?scp=85214257006&partnerID=8YFLogxK
U2 - 10.1016/j.adhoc.2024.103747
DO - 10.1016/j.adhoc.2024.103747
M3 - Article
SN - 1570-8705
VL - 169
JO - Ad Hoc Networks
JF - Ad Hoc Networks
M1 - 103747
ER -