Optoelectronics Letters, Volume. 20, Issue 1, 35(2024)

Deep learning-based channel estimation for wireless ul-traviolet MIMO communication systems

Taifei ZHAO1,2、*, Yuxin SUN1, Xinzhe Lü1, and Shuang and ZHANG1,2
Author Affiliations
  • 1Faculty of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, China
  • 2Xian Key Laboratory of Wireless Optical Communication and Network Research, Xi’an 710048, China
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    To solve the problems of pulse broadening and channel fading caused by atmospheric scattering and turbulence, mul-tiple-input multiple-output (MIMO) technology is a valid way. A wireless ultraviolet (UV) MIMO channel estimation approach based on deep learning is provided in this paper. The deep learning is used to convert the channel estimation into the image processing. By combining convolutional neural network (CNN) and attention mechanism (AM), the learning model is designed to extract the depth features of channel state information (CSI). The simulation results show that the approach proposed in this paper can perform channel estimation effectively for UV MIMO communica-tion and can better suppress the fading caused by scattering and turbulence in the MIMO scattering channel.


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    ZHAO Taifei, SUN Yuxin, Lü Xinzhe, and ZHANG Shuang. Deep learning-based channel estimation for wireless ul-traviolet MIMO communication systems[J]. Optoelectronics Letters, 2024, 20(1): 35

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    Paper Information

    Received: Apr. 12, 2023

    Accepted: Jul. 3, 2023

    Published Online: May. 15, 2024

    The Author Email: Taifei ZHAO (year623@163.com)