Temperature impact in LoraWAN—A case study in northern Sweden

Abstract

LoRa Wide Area Network (LoRaWAN) has become popular as an Internet of Things (IoT) enabler. The low cost, ease of installation and the capacity of fine-tuning the parameters make this network a suitable candidate for the deployment of smart cities. In northern Sweden, in the smart region of Skellefteå, we have deployed a LoRaWAN to enable IoT applications to assist the lives of citizens. As Skellefteå has a subarctic climate, we investigate how the extreme changes in the weather happening during a year affect a real LoRaWAN deployment in terms of Signal-to-Noise Ratio (SNR), Received Signal Strength Indication (RSSI) and the use of Spreading Factors (SFs) when Adaptive Data Rate (ADR) is enabled. Additionally, we evaluate two propagation models (Okumura-Hata and Irregular Terrain Model (ITM)) and verify if any of those models fit the measurements obtained from our real-life network. Our results regarding the weather impact show that cold weather improves the SNR while warm weather makes the sensors select lower SFs, to minimize the time-on-air. Regarding the tested propagation models, Okumura-Hata has the best fit to our data, while ITM tends to overestimate the RSSI values.