University of Oulu

M. Stusek et al., "Accuracy Assessment and Cross-Validation of LPWAN Propagation Models in Urban Scenarios," in IEEE Access, vol. 8, pp. 154625-154636, 2020, doi: 10.1109/ACCESS.2020.3016042

Accuracy assessment and cross-validation of LPWAN propagation models in urban scenarios

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Author: Stusek, Martin1,2; Moltchanov, Dmitri2; Masek, Pavel1;
Organizations: 1Department of Telecommunications, Brno University of Technology, 616 00 Brno, Czech Republic
2Unit of Electrical Engineering, Tampere University, 33100 Tampere, Finland
3Centre for Wireless Communications, University of Oulu, 90014 Oulu, Finland
4Vodafone Czech Republic a.s., 15500 Prague, Czech Republic
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 3.4 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2020110288966
Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2020-11-02
Description:

Abstract

With the proliferation of machine-to-machine (M2M) communication in the course of the last decade, the importance of low-power wide-area network (LPWAN) technologies intensifies. However, the abundance of accurate propagation models proposed for these systems by standardization bodies, vendors, and research community hampers the deployment planning. In this paper, we question the selection of accurate propagation models for Narrowband IoT (NB-IoT), LoRaWAN, and Sigfox LPWAN technologies, based on extensive measurement campaign in two mid-size European cities. Our results demonstrate that none of the state-of-the-art models can accurately describe the propagation of LPWAN radio signals in an urban environment. For this reason, we propose enhancements to the selected models based on our experimental measurements. Performing the fine-tuning of the propagation models for one of the cities, we select Ericsson Urban (NB-IoT, LoRaWAN) and 3GPP (Sigfox) models as the ones providing the closest match. Finally, we proceed to perform cross-validation of the propagation models using the data set for another city. The tuned models demonstrate an excellent match with the real data in the cross-validation phase. They outperform their competitors by at least 20–80% in terms of relative deviation from the measured signal levels presenting the accurate option for NB-IoT, LoRaWAN, and Sigfox deployments planning in mid-size cities.

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Series: IEEE access
ISSN: 2169-3536
ISSN-E: 2169-3536
ISSN-L: 2169-3536
Volume: 8
Pages: 154625 - 154636
DOI: 10.1109/ACCESS.2020.3016042
OADOI: https://oadoi.org/10.1109/ACCESS.2020.3016042
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: This work was supported in part by the European Union, Ministry of Education, Youth and Sports, Czech Republic, and Brno University of Technology through the International Mobility Project MeMoV under Grant CZ.02.2.69/0.0/0.0/16_02/00083710, and in part by the Technology Agency of the Czech Republic under Project TN01000007. The work of Konstantin Mikhaylov was supported by the Academy of Finland 6G Flagship under Grant 318927. The work of Dmitri Moltchanov was supported by the Business Finland Project 5G-FORCE.
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
Copyright information: © The Authors 2020. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
  https://creativecommons.org/licenses/by/4.0/