Research Article
Performance Evaluation of Spreading Factors in LoRa Networks
@INPROCEEDINGS{10.1007/978-3-030-70572-5_13, author={Smangaliso Mnguni and Pragasen Mudali and Adnan M. Abu-Mahfouz and Matthew Adigun}, title={Performance Evaluation of Spreading Factors in LoRa Networks}, proceedings={Towards new e-Infrastructure and e-Services for Developing Countries. 12th EAI International Conference, AFRICOMM 2020, Eb\'{e}ne City, Mauritius, December 2-4, 2020, Proceedings}, proceedings_a={AFRICOMM}, year={2021}, month={7}, keywords={Spreading factors LoRa networks IoT Gateway Simulation}, doi={10.1007/978-3-030-70572-5_13} }- Smangaliso Mnguni
Pragasen Mudali
Adnan M. Abu-Mahfouz
Matthew Adigun
Year: 2021
Performance Evaluation of Spreading Factors in LoRa Networks
AFRICOMM
Springer
DOI: 10.1007/978-3-030-70572-5_13
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.