ZHAO Taifei,SUNYuxin,Lü Xinzhe,，ZHANG Shuang.Deep learning-based channel estimation for wireless ultraviolet MIMO communication systems[J].Optoelectronics Letters,2024,(1):35-41 Deep learning-based channel estimation for wireless ultraviolet MIMO communication systems Author Name Affiliation ZHAO Taifei  Faculty of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, China Xian Key Laboratory of Wireless Optical Communication and Network Research, Xi’an 710048, China  SUNYuxin  Faculty of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, China  Lü Xinzhe  Faculty of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, China  ，ZHANG Shuang  Faculty of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, China Xian Key Laboratory of Wireless Optical Communication and Network Research, Xi’an 710048, China  Abstract:       To solve the problems of pulse broadening and channel fading caused by atmospheric scattering and turbulence, multiple-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 communication and can better suppress the fading caused by scattering and turbulence in the MIMO scattering channel. Hits: 46 Download times: 0 View Full Text    Download reader