IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/3390075.html
   My bibliography  Save this article

Addressing the Real World Problem of Managing Wireless Communication Systems Using Explainable AI-Based Models through Correlation Analysis

Author

Listed:
  • S. Surya
  • Sumeet Gupta
  • Abolfazl Mehbodniya
  • Jeidy Panduro-Ramirez
  • Prabhakara Rao Kapula
  • Tanweer Alam
  • Karthikeyan Kaliyaperumal
  • Vijay Kumar

Abstract

In a general parlance, wireless communication tends to be investigated based on the available methods that support enhancing the optimized data link, especially the software-based methods. AI is mainly used to create and design efficient communication network systems and variable node locations. The major factors impacting wireless communications in the current context are enhanced channel frequency, efficiency of using the bandwidth, and modulation type. The software-defined ratio enables collecting the information and analyzing the overall signal-related components and processing them in real-time situations. This will support in detecting unnecessary information and identifying latency at each stage of communication. The study is intended to measure the influence of critical factors in enhancing the overall management of wireless communication systems through the application of AI technologies. The researchers used the questionnaire method in order to collect the data from the respondents and enable them to analyze the data using the SPSS data package.

Suggested Citation

  • S. Surya & Sumeet Gupta & Abolfazl Mehbodniya & Jeidy Panduro-Ramirez & Prabhakara Rao Kapula & Tanweer Alam & Karthikeyan Kaliyaperumal & Vijay Kumar, 2022. "Addressing the Real World Problem of Managing Wireless Communication Systems Using Explainable AI-Based Models through Correlation Analysis," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-6, March.
    • Handle: RePEc:hin:jnlmpe:3390075
    DOI: 10.1155/2022/3390075
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/3390075.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/mpe/2022/3390075.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2022/3390075?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
    ---><---

    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:hin:jnlmpe:3390075. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.