Cross-City Validation and Refinement of a Path-Loss Model for NB-IoT in Urban Scenarios

The Narrowband Internet of Things (NB-IoT) technology has an important role in the mobile cellular ecosystem, enabling massive Machine Type Communication (mMTC) services. NB-IoT propagation was preliminarily analyzed via a measurement campaign carried out in 2020 in the city of Oslo, Norway. This investigation resulted in Oslo-2020, the first NB-IoT-specific Alpha-Beta-Gamma (ABG) path loss (PL) model, which showed higher prediction accuracy compared to models developed for different technologies but often used for NB-IoT. In this paper, to further investigate NB-IoT PL in urban scenarios, we analyze new measurement campaigns performed in 2020-2021 and 2023 in the city of Rome, Italy. First, we use the 2020-2021 measurements to derive Rome-2021, a new NB-IoT-specific ABG PL model. We show that Rome-2021 preserves the statistical properties of Oslo-2020 (e.g., the Gaussianity of the PL exponent distribution across base stations), although the moments of the distributions are different due to city-specific environmental characteristics. We also use new data on signal losses due to outdoor-to-indoor propagation to refine the analysis of this scenario. Finally, we propose a methodology to combine Oslo-2020 and Rome-2021 into a more general model. Our methodology uses so-called Mixture Distributions (MDs), thus leveraging the shared statistical properties between Oslo-2020 and Rome-2021. By using the 2023 measurements, we show that our MD-based approach estimates PL model parameters with higher accuracy compared to Oslo-2020 and Rome-2021 models used separately, thus providing an effective solution for predicting NB-IoT urban PL in lack of site-specific measurements and information.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-04-03
DOI
https://doi.org/10.1109/jiot.2025.3557172
Primary Topic
IoT and Edge/Fog Computing
Type
article
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article

Cross-City Validation and Refinement of a Path-Loss Model for NB-IoT in Urban Scenarios

Anna Brunström, Luca De Nardis, Özgü Alay, Maria‐Gabriella Di Benedetto et al.
IEEE Internet of Things Journal
IoT and Edge/Fog Computing
article

Cross-City Validation and Refinement of a Path-Loss Model for NB-IoT in Urban Scenarios

Anna Brunström, Luca De Nardis, Özgü Alay, Maria‐Gabriella Di Benedetto, Giuseppe Caso, Federico Ferretti, Marco Neri, M. Savelli
article en

Abstract

The Narrowband Internet of Things (NB-IoT) technology has an important role in the mobile cellular ecosystem, enabling massive Machine Type Communication (mMTC) services. NB-IoT propagation was preliminarily analyzed via a measurement campaign carried out in 2020 in the city of Oslo, Norway. This investigation resulted in Oslo-2020, the first NB-IoT-specific Alpha-Beta-Gamma (ABG) path loss (PL) model, which showed higher prediction accuracy compared to models developed for different technologies but often used for NB-IoT. In this paper, to further investigate NB-IoT PL in urban scenarios, we analyze new measurement campaigns performed in 2020-2021 and 2023 in the city of Rome, Italy. First, we use the 2020-2021 measurements to derive Rome-2021, a new NB-IoT-specific ABG PL model. We show that Rome-2021 preserves the statistical properties of Oslo-2020 (e.g., the Gaussianity of the PL exponent distribution across base stations), although the moments of the distributions are different due to city-specific environmental characteristics. We also use new data on signal losses due to outdoor-to-indoor propagation to refine the analysis of this scenario. Finally, we propose a methodology to combine Oslo-2020 and Rome-2021 into a more general model. Our methodology uses so-called Mixture Distributions (MDs), thus leveraging the shared statistical properties between Oslo-2020 and Rome-2021. By using the 2023 measurements, we show that our MD-based approach estimates PL model parameters with higher accuracy compared to Oslo-2020 and Rome-2021 models used separately, thus providing an effective solution for predicting NB-IoT urban PL in lack of site-specific measurements and information.

IEEE Internet of Things JournalVol. 12(13)
University of Oslo (NO), Rohde & Schwarz (Germany) (DE), New York Times (US), Karlstad University (SE), Sapienza University of Rome (IT)
Sustainable cities and communities
Openalex Percentile: Top 94%
IoT and Edge/Fog Computing
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