Accuracy Assessment and Cross-Validation of LPWAN Propagation Models in Urban Scenarios

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.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.