A Self-organized Adaptation of Spreading Factor for LoRa Radio Layer Based on Experimental Study

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Abstract

LoRa technology provides low power, long range and low data rate communication solution for sensor nodes on Internet of the Things (IoT) applications. In this work, we study experimentally the performance of LoRa radio for a device-to-device communication with different spreading factors. A measurement campaign is carried out under different scenarios such as outdoor, indoor, different altitudes, and different distances. In all scenarios, we measure Packet Delivery Ratio (PDR) and Signal to Noise Ratio (SNR). The results show that the distance between a transmitter and a receiver is not the only effective parameter determining the SNR but also environmental conditions and the altitude of a receiver impact on the SNR. We show also that the PDR depends on the applied spreading factor. Besides, we derive a mapping between the SNR to a proper spreading factor of the LoRa radio for different PDR requirements using our empirical results. Applying this mapping, we propose a self-organized algorithm that adapts the spreading factor in LoRa radio to achieve a required PDR. The results show that the proposed adaptive scheme adapts the LoRa radio to provide a given 80% PDR requirement between two LoRa nodes.

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APA

Casas, V., Harounabadi, M., & Mitschele-Thiel, A. (2021). A Self-organized Adaptation of Spreading Factor for LoRa Radio Layer Based on Experimental Study. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 382, pp. 25–36). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-78459-1_2

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