LoRaWAN has become popular as an 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 SNR, RSSI and the use of SF when ADR is enabled. Additionally, we evaluate two propagation models (Okumura-Hata and 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.
LoRa is a physical layer technology with the ability to connect multiple devices in a wide area of coverage, with low power consumption and with interference robustness. The LoRaWAN specification introduces the protocol for communication between multiple devices and the gateway and defines an algorithm for spreading factor allocation. In this Letter, we investigate the efficiency of LoRa to send multiple uplink streams, analyzing different spreading factor allocation strategies to bring light to the coverage-capacity tradeoff. Additionally, we present a complete open-source simulation framework based on ns-3 simulator that can be used to propose, test and analyze the performance of new algorithms or heuristics that may outperform LoRaWAN ADR or any other baseline strategies defined here.
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