LoRa-Based IoT Network Assessment in Rural and Urban Scenarios

Author:

Griva Aikaterini I.1ORCID,Boursianis Achilles D.1ORCID,Wan Shaohua2ORCID,Sarigiannidis Panagiotis3ORCID,Psannis Konstantinos E.4ORCID,Karagiannidis George5ORCID,Goudos Sotirios K.1ORCID

Affiliation:

1. ELEDIA@AUTH, School of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

2. Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen 518110, China

3. Department of Electrical and Computer Engineering, University of Western Macedonia, 50131 Kozani, Greece

4. Department of Applied Informatics, School of Information Sciences, University of Macedonia, 54636 Thessaloniki, Greece

5. School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

Abstract

The implementation of smart networks has made great progress due to the development of the Internet of Things (IoT). LoRa is one of the most prominent technologies in the Internet of Things industry, primarily due to its ability to achieve long-distance transmission while consuming less power. In this work, we modeled different environments and assessed the performances of networks by observing the effects of various factors and network parameters. The path loss model, the deployment area size, the transmission power, the spreading factor, the number of nodes and gateways, and the antenna gain have a significant effect on the main performance metrics such as the energy consumption and the data extraction rate of a LoRa network. In order to examine these parameters, we performed simulations in OMNeT++ using the open source framework FLoRa. The scenarios which were investigated in this work include the simulation of rural and urban environments and a parking area model. The results indicate that the optimization of the key parameters could have a huge impact on the deployment of smart networks.

Funder

European Union’s Horizon 2020 research and innovation program

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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