IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v80y2022i3d10.1007_s11235-022-00903-4.html
   My bibliography  Save this article

A review: spreading factor allocation schemes for LoRaWAN

Author

Listed:
  • Poonam Maurya

    (Indian Institute of Technology)

  • Aatmjeet Singh

    (Indian Institute of Technology)

  • Arzad Alam Kherani

    (Indian Institute of Technology)

Abstract

LoRaWAN is one of the most suitable communication protocols for the IoT applications that require low power over long-range communication. However, the LoRa network suffers from scalability, low data rate, and other performance issues that significantly affect the network performance. The study of the optimal spreading factor allocation can overcome these issues and help to improve the network performance. Hence, this article puts forward the state-of-the-art literature review on the Spreading Factors Allocation schemes for the LoRaWAN. Industry and academia have done an extensive research to address the issues related to optimal resource allocation, like spreading factor allocation to the spatially distributed end-devices of the network. Most of the problems concerning spreading factor allocation are being explored and resolved. Therefore, this paper reviews and compares various spreading factor allocation schemes proposed by the researchers. Furthermore, we provide a summary of the different review studies of the LoRaWAN. The literature presented in this paper motivates researchers to examine other aspects of spreading factor allocation schemes to improve the LoRa network performance.

Suggested Citation

  • Poonam Maurya & Aatmjeet Singh & Arzad Alam Kherani, 2022. "A review: spreading factor allocation schemes for LoRaWAN," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 80(3), pages 449-468, July.
    • Handle: RePEc:spr:telsys:v:80:y:2022:i:3:d:10.1007_s11235-022-00903-4
    DOI: 10.1007/s11235-022-00903-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-022-00903-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11235-022-00903-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mehmet Ali Ertürk & Muhammed Ali Aydın & Muhammet Talha Büyükakkaşlar & Hayrettin Evirgen, 2019. "A Survey on LoRaWAN Architecture, Protocol and Technologies," Future Internet, MDPI, vol. 11(10), pages 1-34, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bernhard Koelmel & Max Borsch & Rebecca Bulander & Lukas Waidelich & Tanja Brugger & Ansgar Kuehn & Matthias Weyer & Luc Schmerber & Michael Krutwig, 2023. "Quantifying the Economic and Financial Viability of NB-IoT and LoRaWAN Technologies: A Comprehensive Life Cycle Cost Analysis Using Pragmatic Computational Tools," FinTech, MDPI, vol. 2(3), pages 1-17, July.
    2. Kerima Saleh Abakar & Ismail Bennis & Abdelhafid Abouaissa & Pascal Lorenz, 2022. "A Multi-Gateway Behaviour Study for Traffic-Oriented LoRaWAN Deployment," Future Internet, MDPI, vol. 14(11), pages 1-15, October.
    3. Evangelos Syrmos & Vasileios Sidiropoulos & Dimitrios Bechtsis & Fotis Stergiopoulos & Eirini Aivazidou & Dimitris Vrakas & Prodromos Vezinias & Ioannis Vlahavas, 2023. "An Intelligent Modular Water Monitoring IoT System for Real-Time Quantitative and Qualitative Measurements," Sustainability, MDPI, vol. 15(3), pages 1-20, January.
    4. Pavel Masek & Martin Stusek & Ekaterina Svertoka & Jan Pospisil & Radim Burget & Elena Simona Lohan & Ion Marghescu & Jiri Hosek & Aleksandr Ometov, 2021. "Measurements of LoRaWAN Technology in Urban Scenarios: A Data Descriptor," Data, MDPI, vol. 6(6), pages 1-20, June.
    5. Artur Felipe da Silva Veloso & José Valdemir Reis Júnior & Ricardo de Andrade Lira Rabelo & Jocines Dela-flora Silveira, 2021. "HyDSMaaS: A Hybrid Communication Infrastructure with LoRaWAN and LoraMesh for the Demand Side Management as a Service," Future Internet, MDPI, vol. 13(11), pages 1-45, October.
    6. Patricia Franco & José M. Martínez & Young-Chon Kim & Mohamed A. Ahmed, 2022. "A Cyber-Physical Approach for Residential Energy Management: Current State and Future Directions," Sustainability, MDPI, vol. 14(8), pages 1-33, April.

    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:spr:telsys:v:80:y:2022:i:3:d:10.1007_s11235-022-00903-4. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.