Performance evaluation of Spreading Factors in LoRa networks

Abstract

LoRa Networks is one of the fast-growing and promising technologies to enable communications for the Internet of Things (IoT) devices on a large scale or long-range communication. Spreading Factors (SF) plays a significant role in enabling multiple long-range receptions of packets with every packet assigned a different spreading factor. Therefore, a change in SF is necessary for improving the data rate for transmission where the link is better and allow LoRa networks to adapt the range trade-off. This work uses FLoRa open source framework for carrying out end-to-end LoRa simulations network in the OMNET++ simulator. In this paper, we investigated the Adaptive Data Rate (ADR) and provided the behaviour of SF and data rate in LoRa wide Are network (LoRaWAN). Some of the findings includes the ability of transmitting data very fast possessed by the low SF no matter the size of the network and high amount of energy consumed by the high SF.