IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i5p1148-d1600238.html
   My bibliography  Save this article

STAR-RIS-Assisted WET System Optimization: Minimizing Recharging Time Using PSO Based on S-CSI

Author

Listed:
  • Rogério Pereira Junior

    (National Institute of Telecommunications, Santa Rita do Sapucaí 37536-001, MG, Brazil)

  • Isabel Francine Mendes

    (National Institute of Telecommunications, Santa Rita do Sapucaí 37536-001, MG, Brazil)

  • Victoria Dala Pegorara Souto

    (National Institute of Telecommunications, Santa Rita do Sapucaí 37536-001, MG, Brazil)

  • Richard Demo Souza

    (Department of Electrical and Electronics Engineering, Federal University of Santa Catarina, Florianópolis 88040-900, SC, Brazil)

Abstract

Wireless Energy Transfer (WET) combined with Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface (STAR-RIS) technology offers a promising approach to optimize the recharging of Internet of Things (IoT) devices. In this work, we propose the use of STAR-RIS in the WET context to enable efficient recharging of IoT devices, with the goal of minimizing the total system recharging time while ensuring that each IoT device meets its minimum energy requirement. The optimization is performed using the Particle Swarm Optimization (PSO) technique, including the beamforming configuration of the power beacon (PB) as well as the phase and amplitude coefficients of the STAR-RIS elements. We compare two STAR-RIS operating protocols: time switching (TS) and energy splitting (ES). Simulation results indicate that it is possible to charge devices efficiently using only statistical channel state information (S-CSI), even in the absence of direct link between the PB and the IoT devices.

Suggested Citation

  • Rogério Pereira Junior & Isabel Francine Mendes & Victoria Dala Pegorara Souto & Richard Demo Souza, 2025. "STAR-RIS-Assisted WET System Optimization: Minimizing Recharging Time Using PSO Based on S-CSI," Energies, MDPI, vol. 18(5), pages 1-19, February.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:5:p:1148-:d:1600238
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/5/1148/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/5/1148/
    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:jeners:v:18:y:2025:i:5:p:1148-:d:1600238. 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.