| 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 Skelleftea, we have deployed a LoRaWAN to enable IoT applications to assist the lives of citizens. As Skelleftea 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. |
