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Cognitive-LoRa: Adaptation-Aware of the Physical Layer in LoRa-Based Networks

EasyChair Preprint no. 3735

6 pagesDate: July 3, 2020


Network technologies for large areas based on sub-GHz have emerged as a way to provide long-range communication with low cost and complexity. Among the various existing solutions, LoRa is arguably the most adopted and promising in this context. Its main application has been to allow the possibility of ubiquitous connectivity to IoT from a simple network and management structure. Some factors must be taken into account when proposing a LoRa network. The type of application directly affects the LoRa network communication, such as the center frequency, the spreading factor, the bandwidth, and the coding rates chosen by each node. We will observe in this work the characteristics of LoRa physical-layer and its automatic configuration based on the quality of the perceived signal-to-noise ratio (SNR). In this way, we propose an adaptable protocol for LoRa networks with low overhead and complexity. The results obtained by a real scenario show that only 23\% of the observation time make changes in the configuration and has an average gain of 4.68\% for SNR.

Keyphrases: IoT, LoRa, Signal to Noise Ratio, Smart City, sub-GHz, Wireless Cognitive Radio

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Lucas Martins Figueiredo and Edelberto Franco Silva},
  title = {Cognitive-LoRa: Adaptation-Aware of the Physical Layer in LoRa-Based Networks},
  howpublished = {EasyChair Preprint no. 3735},

  year = {EasyChair, 2020}}
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