University of Oulu

M. A. Ullah, K. Mikhaylov and H. Alves, "Enabling mMTC in Remote Areas: LoRaWAN and LEO Satellite Integration for Offshore Wind Farm Monitoring," in IEEE Transactions on Industrial Informatics, vol. 18, no. 6, pp. 3744-3753, June 2022, doi: 10.1109/TII.2021.3112386

Enabling mMTC in remote areas : LoRaWAN and LEO satellite integration for offshore wind farms monitoring

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Author: Asad Ullah, Muhammad1; Mikhaylov, Konstantin1; Alves, Hirley1
Organizations: 1University of Oulu, Centre for Wireless Communications, Oulu, Finland, FI 90014
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.7 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2021-12-17


The offshore wind farms are gaining momentum due to their promise to offer sustainable energy with low pollution and greenhouse gases emission. However, despite all the immense technological progress of recent years, the operation in a harsh and hard-to-reach environment remains challenging. According to the reports, each offshore wind turbine requires five maintenance visits a year on average, and the cumulative repair costs constitute around 30% of the turbine’s life-cycle expenditure. Motivated by the advancement of massive machine-type connectivity (mMTC) and satellite technologies, in this study, we investigate the potential of these to enable remote monitoring of the offshore wind farms. Specifically, the two alternative architectures are considered. The indirect architecture relies on using a local mMTC gateway (GW) with a backbone over a reliable communication channel (e.g., satellite or wire-based). The direct approach implies the transmission of the data by sensors on the wind turbines directly to the mMTC GW on the low-earth orbit (LEO) satellite. The details of the system design, the alternative implementation strategies and relevant pros, cons, and trade-offs are pin-pointed. Finally, we employ simulations using realistic deployment and traffic and advanced propagation and collision models to characterize these two approaches’ feasibility and packet delivery probability numerically when implemented over LoRaWAN mMTC technology.

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Series: IEEE transactions on industrial informatics
ISSN: 1551-3203
ISSN-E: 1941-0050
ISSN-L: 1551-3203
Volume: 18
Issue: 6
Pages: 3744 - 3753
DOI: 10.1109/TII.2021.3112386
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This research has been financially supported by Academy of Finland, 6Genesis Flagship (Grant no318927) and MRAT-SafeDrone (Grant no341111)
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
341111 (Academy of Finland Funding decision)
Copyright information: This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see