IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/2139629.html
   My bibliography  Save this article

Data Transmission Control Method of Electrical Equipment of Automobile Based on the 5G Communication Technology

Author

Listed:
  • Yajun Han
  • Naeem Jan

Abstract

Conflicts emerge when the data transmission occurs between electrical equipment in an automobile. Hence, transmission delays appear as issues. For this reason, a method, called data transmission control, for electrical equipment of automobiles based on the 5G communication technology is proposed in this paper. Firstly, the wavelet feature decomposition was utilized to partition the frequency spectrum, and thus the statistical characteristics of electrical equipment of automobiles concerning the transmitted data were obtained. Then, the high-order approximate distribution method was adopted to construct a channel for a 5G network data transmission. Afterward, the control logic structure of the data transmission was built, and the problem, called the conflict of the data transmission, was alleviated through concurrent data collection and processing methods. On this basis, coding coefficients of a constructed global coding matrix were selected to encode and transmit source information. Also, the number of redundant data packets at each layer was adjusted. Finally, the data transmission control of the electrical equipment of the automobile was realized through the linear combination of the network nodes. The simulation results showed that the throughput of the proposed method was always higher than 7.7 MB/s, the bit error rate was around 0 when the signal-to-noise ratio was lower than 3, and the transmission delay was always below 0.5 s, which could provide a reference for the efficient and safe operation of automobiles.

Suggested Citation

  • Yajun Han & Naeem Jan, 2022. "Data Transmission Control Method of Electrical Equipment of Automobile Based on the 5G Communication Technology," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-9, March.
  • Handle: RePEc:hin:jnlmpe:2139629
    DOI: 10.1155/2022/2139629
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/2139629.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/mpe/2022/2139629.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2022/2139629?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:2139629. 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.