IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i18p6550-d909444.html
   My bibliography  Save this article

Mine Intelligent Receiver: MIMO-OFDM Intelligent Receiver for Mine Information Recovery

Author

Listed:
  • Anyi Wang

    (School of Communication and Information Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
    Key Laboratory of Network Convergence Communication, Xi’an 710600, China)

  • Zhiyuan Feng

    (School of Communication and Information Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Xuhong Li

    (School of Communication and Information Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Yong Pan

    (School of Communication and Information Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

Abstract

With the advancement of an intellectual and numerical society, the coal mining industry has also begun to change to intelligence. As an important aspect of intelligent coal mine construction, coal mine communication has put forward more stringent standards for communication quality. For the complex communication environment in mines, the transmission of communication signals is always damaged by various noises and interferences, resulting in serious distortion of the communication signals received at the receiving end. Therefore, the use of traditional receivers for information recovery has the problem of high bit error rate (BER), which cannot meet the standard of intelligent coal mine construction. Based on this, the aim of this research is to combine convolutional neural networks (CNN) and multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) communication systems to design an intelligent receiver model for complex mine communication systems. At the receiver side, CNNs are used to take the place of all the information processing processes. First, features are extracted from the received IQ signal by the convolutional neural network, and then the original information bit is recovered using a multi-label classifier to finally realize end-to-end information restoration. The experimental results show that the intelligent receiver model designed in this research has more accurate information recovery capability in the complex mine channel environment compared with the traditional receiver. In addition, they also verify that the intelligent receiver can still recover information effectively when the traditional receiver cannot recover information properly in the case of partial loss of received data.

Suggested Citation

  • Anyi Wang & Zhiyuan Feng & Xuhong Li & Yong Pan, 2022. "Mine Intelligent Receiver: MIMO-OFDM Intelligent Receiver for Mine Information Recovery," Energies, MDPI, vol. 15(18), pages 1-17, September.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6550-:d:909444
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/18/6550/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/18/6550/
    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:15:y:2022:i:18:p:6550-:d:909444. 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.