MURAL - Maynooth University Research Archive Library



    Analysis and Enhancement of the LoRaWAN Adaptive Data Rate Scheme


    Finnegan, Joseph and Farrell, Ronan and Brown, Stephen (2020) Analysis and Enhancement of the LoRaWAN Adaptive Data Rate Scheme. IEEE Internet of Things Journal, 7 (8). pp. 7171-7180. ISSN 2372-2541

    [img]
    Preview
    Download (1MB) | Preview


    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...



    Add this article to your Mendeley library


    Abstract

    The adaptive data rate (ADR) algorithm is a key component of the LoRaWAN protocol which controls the performance of a LoRaWAN Network. This modifies the data rate parameter of a device based on the current wireless conditions. In this article, we present substantive enhancements for the End Device and Network Server which reduce the convergence time for LoRaWAN devices to reach their optimal data rate. We extend the LoRaWAN module in ns-3 by adding ADR, enabling the simulation of realistic LoRaWAN networks, and add the implementation of the new enhancements in this module. The simulations show that these modifications can result in a significant reduction of the data rate convergence time for LoRaWAN devices and lead to an increased overall packet delivery rate for the network in a dynamic network environment. Our contributions are a publicly available implementation of ADR in ns-3, an analysis of the original algorithm behaviour, and a novel version of the algorithm with enhancements that improve performance in every case while remaining easily integrable into an existing LoRaWAN system.

    Item Type: Article
    Additional Information: Cite as: J. Finnegan, R. Farrell and S. Brown, "Analysis and Enhancement of the LoRaWAN Adaptive Data Rate Scheme," in IEEE Internet of Things Journal, vol. 7, no. 8, pp. 7171-7180, Aug. 2020, doi: 10.1109/JIOT.2020.2982745.
    Keywords: Downlink; Uplink; Internet of Things; Protocols; Adaptive Systems; Performance evaluation; Network servers;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Faculty of Science and Engineering > Theoretical Physics
    Item ID: 15948
    Identification Number: https://doi.org/10.1109/JIOT.2020.2982745
    Depositing User: Ronan Farrell
    Date Deposited: 12 May 2022 10:40
    Journal or Publication Title: IEEE Internet of Things Journal
    Publisher: IEEE Explore
    Refereed: Yes
    URI:

    Repository Staff Only(login required)

    View Item Item control page

    Downloads

    Downloads per month over past year