Paper Info
Title
Experimental Link Quality Analysis for LoRa-Based Wireless Underground Sensor Networks
Abstract
A variety of industrial applications are deployed in underground environments, such as soil condition assessment and pipeline monitoring (PM). Wireless underground sensor networks (WUSNs) are capable of continuously monitoring pipelines and promptly alerting any anomaly of entities. However, underground soils significantly influence the traditional WUSNs connectivity success. Long range (LoRa), being a leading low-power wide-area networks (LPWANs) technology, provides a new solution for underground industrial monitoring with its advantages in long-range capability and ultralow power consumption. Nevertheless, the LoRa-based link quality characteristics have not yet been quantitatively evaluated for WUSNs. In this article, the channel models of both the underground-to-aboveground (UG2AG) and aboveground-to-underground (AG2UG) communications are investigated. We experimentally analyze the impact of the propagation direction, burial depth and LoRa physical layer parameters on the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in-situ</italic> LoRa propagation performance. The received signal strength indictor (RSSI), signal-to-noise ratio (SNR), and packet deliver ratio (PDR) are characterized for both communication channels in LoRa-based WUSNs. The semiempirical path-loss models are successfully verified by our field results, and we demonstrate that the communication range can be greater than 50 m at the burial depth of 0.4 m by adjusting the LoRa transmission/receiving settings. The combination of RSSI and SNR can be a better indicator of PDR than relying on either of them alone. Finally, the frame error rate (FER) is calculated to estimate the link performance with EM interferences. These results successfully demonstrate the advantages of LoRa for PM applications, which serve the first step toward the efficient protocol development of LoRa-based WUSNs.
Year
DOI
Venue
2021
10.1109/JIOT.2020.3044647
IEEE Internet of Things Journal
Keywords
DocType
Volume
Soil,Wireless communication,Wireless sensor networks,Signal to noise ratio,Monitoring,Topology,Pipelines
Journal
8
Issue
ISSN
Citations 
8
2327-4662
1
PageRank 
References 
Authors
0.36
0
2
Name
Order
Citations
PageRank
Kaiqiang Lin111.38
Tong Hao213.07