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R. Marini, K. Mikhaylov, G. Pasolini and C. Buratti, "Low-Power Wide-Area Networks: Comparison of LoRaWAN and NB-IoT Performance," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2022.3176394.

Low-Power Wide-Area Networks : comparison of LoRaWAN and NB-IoT performance

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Author: Marini, Riccardo1; Mikhaylov, Konstantin2; Pasolini, Gianni1;
Organizations: 1Wilab, CNIT and DEI Department, University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy
2Centre for Wireless Communications, University of Oulu, Erkki Koiso-Kanttilan katu 3, 90570 Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 4.8 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2022081955863
Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2022-08-19
Description:

Abstract

Low Power Wide Area Networks (LPWANs) have become an important enabler for the Internet of Things (IoT) connectivity. Application domains like smart cities, smart agriculture, intelligent logistics and transportation, require communication technologies that combine long transmission ranges and energy efficiency. Recent and future trends make Long Range Wide Area Network (LoRaWAN) and Narrowband-IoT (NB-IoT) the most prospective drivers of the IoT business. In this paper, after discussing the main features of the two technologies, we carry out a fair quantitative comparison between the two, investigating different performance indicators, in order to guide designers in the selection of the most appropriate technology, depending on the application requirements.

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Series: IEEE internet of things journal
ISSN: 2372-2541
ISSN-E: 2327-4662
ISSN-L: 2327-4662
DOI: 10.1109/JIOT.2022.3176394
OADOI: https://oadoi.org/10.1109/JIOT.2022.3176394
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Internet of Things
LoRaWAN
Low Power Wide Area Networks
NB-IoT
Article
Funding: This work was carried out in the framework of the CNIT National Laboratory WiLab and of the COST Innovators Grant IG15104, IMMUNeT. The work of K. Mikhaylov have been supported by Academy of Finland projects RoboMesh (grant 336060), MRAT-SafeDrone (grant 341111) and 6G Flagship (grant 346208). The research was also supported by COST Action CA20120 INTERACT.
Academy of Finland Grant Number: 336060
341111
346208
Detailed Information: 336060 (Academy of Finland Funding decision)
341111 (Academy of Finland Funding decision)
346208 (Academy of Finland Funding decision)
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