|Authors||G. Caso, Ö. Alay, L. De Nardis, A. Brunström, M. Neri and M. Di Benedetto|
|Title||Empirical Models for NB-IoT Path Loss in an Urban Scenario|
|Project(s)||Department of Mobile Systems and Analytics|
|Publication Type||Journal Article|
|Year of Publication||2021|
|Journal||IEEE Internet of Things Journal|
|Keywords||Cellular Internet of Things, massive Machine Type Communications, Narrowband Internet of Things, Path Loss Empirical Models|
The lack of publicly available large scale measure- ments has hindered the derivation of empirical path loss (PL) models for Narrowband Internet of Things (NB-IoT). Therefore, simulation-based investigations currently rely on models con- ceived for other cellular technologies, which are characterized, however, by different available bandwidth, carrier frequency, and infrastructure deployment, among others. In this paper, we take advantage of data from a large scale measurement campaign in the city of Oslo, Norway, to provide the first empirical characterization of NB-IoT PL in an urban scenario. For the PL average term, we characterize Alpha-Beta-Gamma (ABG) and Close-In (CI) models. By analyzing multiple NB- IoT cells, we propose a statistical PL characterization, i.e., the model parameters are not set to a single, constant value across cells, but are randomly extracted from well-known distributions. Similarly, we define the PL shadowing distribution, correlation over distance, and inter-site correlation. Finally, we give initial insights on outdoor-to-indoor propagation, using measurements up to deep indoor scenarios. The proposed models improve PL estimation accuracy compared to the ones currently adopted in NB-IoT investigations, enabling more realistic simulations of urban scenarios similar to the sites covered by our measurements.