Deep Learning-Based Channel Estimation for Wireless ultraviolet MIMO Communication Systems
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Abstract:
To solve the problems of pulse broadening and channel fading caused by atmospheric scattering and turbulence, multiple-input multiple-output (MIMO) technology is an valid way. A wireless ultraviolet MIMO channel estimation approach based on deep learning is provided in this paper, 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 structure 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 ultraviolet MIMO communication and can better suppress the fading caused by scattering and turbulence in the MIMO scat-tering channel.
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Project Supported:
National Natural Science Foundation of China (61971345)，Shaanxi Province Key R&D Program General Project (2021GY-044), Technology Program of Yulin City (2019-145)，Artificial Intelligence Key Laboratory of Sichuan Province（2022RYY01）
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