IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v15y2023i8p273-d1218840.html
   My bibliography  Save this article

An Efficient Adaptive Data-Link-Layer Architecture for LoRa Networks

Author

Listed:
  • Micael Coutinho

    (Center of Physics, University of Minho, 4804-533 Guimarães, Portugal)

  • Jose A. Afonso

    (CMEMS-UMinho/LABBELS, University of Minho, 4800-058 Guimarães, Portugal)

  • Sérgio F. Lopes

    (Centro Algoritmi/LASI, University of Minho, 4804-533 Guimarães, Portugal)

Abstract

LoRa is one of the most popular low-power wireless network technologies for implementation of the Internet of Things, with the advantage of providing long-range communication, but lower data rates, when compared with technologies such as Zigbee or Bluetooth. LoRa is a single-channel physical layer technology on top of which LoRaWAN implements a more complex multi-channel network with enhanced functionalities, such as adaptive data rate. However, LoRaWAN relies on expensive hardware to support these functionalities. This paper proposes a LoRa data-link-layer architecture based on a multi-layer star network topology that adapts relevant LoRa parameters for each end node dynamically taking into account its link distance and quality in order to balance communication range and energy consumption. The developed solution is comprised of multiple components, including a LoRa parameter calculator to help the user to configure the network parameters, a contention-free MAC protocol to avoid collisions, and an adaptive spreading factor and transmission power mechanism. These components work together to ensure a more efficient use of the chosen ISM band and end node resources, but with low-cost implementation and operation requirements.

Suggested Citation

  • Micael Coutinho & Jose A. Afonso & Sérgio F. Lopes, 2023. "An Efficient Adaptive Data-Link-Layer Architecture for LoRa Networks," Future Internet, MDPI, vol. 15(8), pages 1-16, August.
  • Handle: RePEc:gam:jftint:v:15:y:2023:i:8:p:273-:d:1218840
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/15/8/273/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1999-5903/15/8/273/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:15:y:2023:i:8:p:273-:d:1218840. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.