IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i12p7310-d839109.html
   My bibliography  Save this article

Power Optimization Model for Energy Sustainability in 6G Wireless Networks

Author

Listed:
  • Ashu Taneja

    (Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, India)

  • Nitin Saluja

    (Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, India)

  • Neeti Taneja

    (Noida Institute of Engineering and Technology, Greater Noida 201306, India)

  • Ali Alqahtani

    (College of Computer Science and Information Systems, Najran University, Najran 61441, Saudi Arabia)

  • M. A. Elmagzoub

    (College of Computer Science and Information Systems, Najran University, Najran 61441, Saudi Arabia)

  • Asadullah Shaikh

    (College of Computer Science and Information Systems, Najran University, Najran 61441, Saudi Arabia)

  • Deepika Koundal

    (School of Computer Science, University of Petroleum & Energy Studies, Dehradun 248007, India)

Abstract

Internet-of-Things (IoT) networks are witnessing a rapid proliferation of connected devices and mobile terminals each day. The wireless information flow between these massive battery-powered devices has a huge energy burden and will lead to an energy crisis in the near future; thus, there is an urgent search for sustainable energy networks. To offer a sustainable energy solution in order to meet the energy demands of these massive IoT networks, this paper presents a dynamic practical model that enables the efficient management of power resources. Two user-scheduling algorithms, namely, minimum distance scheduling (MDS) and maximum channel gain scheduling (MCS), are proposed; when these algorithms were used alongside a power optimization, they led to improved network efficiency. Further, the network’s performance was measured with parametric variations in the number of access points (APs); the deployment of APs and AP configuration is carried out for different precoding schemes. The impact of spatial correlation and the access to perfect channel state information (CSI) on the spectral efficiency of the system was also evaluated. In the end, the study compares the performance of different power-allocation methods and suggests that the power allocated to a particular user node by an AP can be controlled using the proposed algorithms. It is observed that, as compared to the MDS algorithm, the MCS algorithm results in better spectral efficiency for all the users with fractional power allocation. In addition, each AP assigns a maximum power of 141.7 mW to a user with strong channel conditions with the AP, and a minimum power of 3.1882 mW to the user with the worst channel conditions using centralized PMMSE precoding.

Suggested Citation

  • Ashu Taneja & Nitin Saluja & Neeti Taneja & Ali Alqahtani & M. A. Elmagzoub & Asadullah Shaikh & Deepika Koundal, 2022. "Power Optimization Model for Energy Sustainability in 6G Wireless Networks," Sustainability, MDPI, vol. 14(12), pages 1-15, June.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:7310-:d:839109
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/12/7310/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/12/7310/
    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:jsusta:v:14:y:2022:i:12:p:7310-:d:839109. 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.