Deep learning-based channel estimation for wireless ultraviolet MIMO communication systems

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.

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