IDEAS home Printed from https://ideas.repec.org/a/igg/jamc00/v12y2021i3p180-194.html
   My bibliography  Save this article

Swarm Intelligence-Based Uplink Power Control in Cognitive Internet of Things (CIoT) for Underlay Environment

Author

Listed:
  • Babar Sultan

    (Department of Electrical Engineering, Abasyn University, Islamabad, Pakistan)

  • Imran Shafi

    (Department of Electrical Engineering, Abasyn University, Islamabad, Pakistan)

  • Jamil Ahmad

    (Kohat University of Science and Technology, Pakistan)

Abstract

Internet of things (IoT) aims to shift intelligence to things and tends to increase the spectrum utilization efficiency. However, in doing so, it might generate high interference to the primary users (PUs) due to massive data flow into the networks. Cognitive radio smartly addresses this challenge by enabling different spectrum sharing modes while guaranteeing the quality of service. Motivated by this fact, the incorporation of cognitive abilities in IoT has given birth to a new sub-domain in IoT, known as Cognitive IoT (CIoT). This paper considers a single cell scenario in which multiple CIoT users (CUs) coexist with a PU in an underlay environment, and their communication performance has been optimized while adhering to the transmit power and interference constraints. Furthermore, two swarm intelligence-based implementations of the proposed algorithm have been provided, one based on Artificial Bee Colony (ABC) and the other based on Particle Swarm Optimization (PSO), and their effectiveness to solve the constrained power allocation problem for CIoT networks has been proved through simulations.

Suggested Citation

  • Babar Sultan & Imran Shafi & Jamil Ahmad, 2021. "Swarm Intelligence-Based Uplink Power Control in Cognitive Internet of Things (CIoT) for Underlay Environment," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 12(3), pages 180-194, July.
  • Handle: RePEc:igg:jamc00:v:12:y:2021:i:3:p:180-194
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAMC.2021070108
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:igg:jamc00:v:12:y:2021:i:3:p:180-194. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.