Open AccessCommunication
Prediction of Power Fluctuations of Gaussian Beams After Transmission Through Turbulent Atmosphere
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Zhihao Wan, Jiayi Zhu, Cheng Huang, Zhimin He, Jun Zeng, Fuchang Chen, Chaoqun Yu, Yan Li, Huanting Chen, Yongtao Zhang, Jixiong Pu and Huichuan Lin
Abstract
As laser beams propagate through free space, power fluctuation occurs due to atmospheric turbulence, which significantly increases the bit error rate of free-space optical communication. If the precise prediction of power fluctuations can be achieved, it will be of great benefit for improving
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As laser beams propagate through free space, power fluctuation occurs due to atmospheric turbulence, which significantly increases the bit error rate of free-space optical communication. If the precise prediction of power fluctuations can be achieved, it will be of great benefit for improving communication efficiency. To achieve this goal, this paper proposes a novel Time Series Long Short-Term Memory Fully Connected Processing Network (TSLSTMFCPN), which consists of two long short-term memory (LSTM) network layers and a fully connected layer, for predicting the power fluctuations of laser beams caused by atmospheric turbulence. The experimental results show that the mean absolute percentage error of the TSLSTMFCPN in predicting laser power fluctuations is only 1.2%. This result indicates that this model can accurately predict the laser power fluctuations caused by atmospheric turbulence. Our results are expected to be applied in free-space optical communication systems and imaging laser radar system.
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