@inproceedings{b5ba9826429346aa99169eb8024e9e1f,
title = "Wave-front restoration of orbital-angular-momentum beam based on phase diversity with GRNN",
abstract = "Orbital angular momentum (OAM) of vortex beams can extend the capacity and spectral efficiency of free-space optical (FSO) communication for its orthogonality provide an extra dimension. However, atmospheric turbulence (AT) will lead to wave-front distortion, crosstalk between OAM modes and eventually reduce the communication system performance. This paper uses a Phase Diversity (PD)-based adaptive optics (AO) schema to compensate the OAM beam. With the General Regression Neural Network (GRNN), the relationship between the intensity distribution and the wave-front distortion of propagation in AT channel is established, and the wave-front aberration is retrieved. This method is simple in structure without phase sensor and probe beam, and reduces computation compared with the common phase retrieval algorithms. Therefore, it can compensate OAM beam in a second and ensure the similar retrieve effect.",
keywords = "adaptive optics, atmospheric turbulence, orbital angular momentum, phase diversity",
author = "Yuanzhi Su and Xiaoli Yin and Huan Chang and Zhaoyuan Zhang and Yuhang Liu",
note = "Publisher Copyright: {\textcopyright} 2021 SPIE.; 2021 International Conference on Optics and Image Processing, ICOIP 2021 ; Conference date: 04-06-2021 Through 06-06-2021",
year = "2021",
doi = "10.1117/12.2605890",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Xizheng Ke and Fengxin Cen",
booktitle = "International Conference on Optics and Image Processing, ICOIP 2021",
address = "United States",
}