LoRaWAN Network: Radio Propagation Models and Performance Evaluation in Various Environments in Lebanon

Chall, Rida El; Lahoud, Samer; Helou, Melhem El

doi:10.1109/jiot.2019.2906838

Cited by 159 publications

(125 citation statements)

References 22 publications

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“…[24] provides an experimental study on LPWANs for mobile IoT applications, arguing that mobility impacts LoRaWANs performance significantly even in very low speed scenarios. [25] provided a study of LoRa in long-range use-cases and produced certain radio propagation models to be used when designing LoRabased solutions. Their work confirmed coverage of up to 8Km in urban and 45Km in rural areas (with line-of-sight).…”

Section: Previous Related Workmentioning

confidence: 99%

A Comparative Study of LoRa and IEEE 802.15.4-Based IoT Deployments Inside School Buildings

et al. 2020

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This work has been supported by the EU research project "European Extreme Performing Big Data Stacks" (E2Data), funded by the European Commission under H2020 and contract number 780245, and the "Green Awareness In Action" (GAIA) project, funded by the European Commission and the EASME under H2020 and contract number 696029. This document reflects only the authors' views and the EC and EASME are not responsible for any use that may be made of the information it contains.

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Section: Previous Related Workmentioning

confidence: 99%

A Comparative Study of LoRa and IEEE 802.15.4-Based IoT Deployments Inside School Buildings

et al. 2020

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“…[24], this would be the frequency range allocated to Colombia for this technology. Literature reviewed [25][26][27][28] on LoRa recommends some values for SF and BW; however, we performed some tests modifying those values (experiment 2, Executed Experiments section), with the aim of optimizing range, message size, and frequency of sending messages. We determined that the appropriate values were 7 for the SF (which can be set between 1 and 12) and 125 KHz for the BW (which can be 125 KHz, 250 KHz, or 500 KHz).…”

Section: Journal Of Computer Network and Communicationsmentioning

confidence: 99%

Proof of Concept of an IoT-Based Public Vehicle Tracking System, Using LoRa (Long Range) and Intelligent Transportation System (ITS) Services

Salazar-Cabrera

Cruz

Molina

2019

Journal of Computer Networks and Communications

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Systems trying to solve mobility issues in cities, such as high levels of accidents and traffic congestion, have been developed worldwide. Intelligent Transportation Systems (ITS) services focused on urban public transport are an option contributing to solve such issues. A few intermediate cities in the Latin American context have developed some of these ITS services, which are mainly based on a tracking system for public transport vehicles. Such tracking systems have great limitations in terms of coverage, availability, and operational cost. In addition, they are commonly isolated mobility solutions, which cannot be easily integrated with other mobility services in the city because they are not based on an ITS architecture. In order to improve public transportation systems in intermediate cities, we proposed the development of an IoT-based public vehicle tracking system, using LoRa (Long Range) and ITS services. In this research, we developed the proposed system as a proof of concept. We designed and executed some experiments, in order to adjust parameters of the LoRa technology and to test its operation. is article presents the methods we followed for developing the proof-of-concept model, a description of the experiments, and their results. e results lead to conclude that the LoRa technology and an IoT-based system are adequate for implementation of a mobility service such as the one we propose, once important technical restrictions related mainly to Line of Sight (LoS) are considered. Key aspects for implementation were also identified for deploying the service (as a prototype) in the city of Popayán.

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“…Our goal, also data driven, is however different in that we want to provide RSSI estimates in a heterogeneous environment. Chall et al [18] proposed a large-scale radio propagation model. But, once again, it is a blanket model for the entire region, and does not handle heterogeneity.…”

Section: Introductionmentioning

confidence: 99%

Coverage Estimation in Outdoor Heterogeneous Propagation Environments

Rathod

Subramanian²,

Sundaresan

2020

IEEE Access

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This paper is on a coverage estimation procedure for the deployment of outdoor Internet of Things (IoT). In the first part of the paper, a data-driven coverage estimation technique is proposed. The estimation technique combines multiple machine-learning-based regression ideas. The proposed technique achieves two purposes. The first purpose is to reduce the bias in the estimated received signal strength arising from estimations performed only on the successfully received packets. The second purpose is to exploit commonality of physical parameters, e.g. antenna-gain, in measurements that are made across multiple propagation environments. It also provides the correct link function for performing a nonlinear regression in our communication systems context. In the second part of the paper, a method to use readily available geographic information system (GIS) data (for classifying geographic areas into various propagation environments) followed by an algorithm for estimating received signal strength (which is motivated by the first part of the paper) is proposed. Together they enable quick and automated estimation of coverage in outdoor environments. It is anticipated that these will lead to faster and more efficient deployment of outdoor Internet of Things. INDEX TERMS Coverage, geographic information system (GIS), heterogeneous propagation environment, Internet of Things (IoT) deployment. NIHESH RATHOD received the B.E. degree in electronics and communication from Dharmsinh Desai University, Nadiad, in 2012, and the M.E. degree in telecommunication from the Indian Institute of Science, Bengaluru, in 2015, where he is currently pursuing the Ph.D. degree in communication and networks. Since 2015, he has been a Cisco Research Scholar with the Department of Electrical Communication Engineering, Indian Institute of Science. His interest includes the areas in design and implementation of the Internet of Things (IoT). RENU SUBRAMANIAN received the B.Tech. degree in electrical and electronics from the Rajiv

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LoRaWAN Network: Radio Propagation Models and Performance Evaluation in Various Environments in Lebanon

Cited by 159 publications

References 22 publications

A Comparative Study of LoRa and IEEE 802.15.4-Based IoT Deployments Inside School Buildings

A Comparative Study of LoRa and IEEE 802.15.4-Based IoT Deployments Inside School Buildings

Proof of Concept of an IoT-Based Public Vehicle Tracking System, Using LoRa (Long Range) and Intelligent Transportation System (ITS) Services

Coverage Estimation in Outdoor Heterogeneous Propagation Environments

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