IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2023i6p1149-d1159153.html
   My bibliography  Save this article

Energy-Efficient Resource Allocation Algorithm for CR-WSN-Based Smart Irrigation System under Realistic Scenarios

Author

Listed:
  • Emad S. Hassan

    (Department of Electrical Engineering, College of Engineering, Jazan University, Jizan 45142, Saudi Arabia
    Department of Electronics and Electrical Communication Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf 32952, Egypt)

Abstract

Cognitive radio wireless sensor networks (CR-WSNs) are a type of WSNs that use cognitive radio technology to enhance the spectrum utilization and energy efficiency. This paper proposes an energy-efficient resource allocation algorithm (EERAA) to prolong the lifetime of a WSN-based smart irrigation system under realistic scenarios. In the proposed algorithm, power allocation and subcarrier assignment are performed consecutively. Considering the impact of the intercarrier interference (ICI) caused by timing offset, the problem of maximizing network-averaged capacity is formulated considering power and interference constraints in realistic scenarios. The obtained results reveal that the proposed algorithm attempts to maximize the averaged capacity of the CR-WSN subject to the total power constraint and tolerable interference. Numerically, the proposed algorithm can reduce the network energy consumption by up to 30%, compared with conventional approaches, while maintaining a high level of system performance in terms of secondary users’ (SUs) averaged capacity.

Suggested Citation

  • Emad S. Hassan, 2023. "Energy-Efficient Resource Allocation Algorithm for CR-WSN-Based Smart Irrigation System under Realistic Scenarios," Agriculture, MDPI, vol. 13(6), pages 1-13, May.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:6:p:1149-:d:1159153
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/6/1149/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/13/6/1149/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohammed Al-Medhwahi & Fazirulhisyam Hashim & Borhanuddin Mohd Ali & A Sali & Abdulsalam Alkholidi, 2019. "Resource allocation in heterogeneous cognitive radio sensor networks," International Journal of Distributed Sensor Networks, , vol. 15(7), pages 15501477198, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hao Wang & Lixin Zhang & Bao Liu, 2024. "Research and Design of a Hybrid DV-Hop Algorithm Based on the Chaotic Crested Porcupine Optimizer for Wireless Sensor Localization in Smart Farms," Agriculture, MDPI, vol. 14(8), pages 1-18, July.

    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.

      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:jagris:v:13:y:2023:i:6:p:1149-:d:1159153. 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: 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.