传输(电信)
连贯性(哲学赌博策略)
编码(内存)
光学
数据传输
光通信
计算机科学
弹性(材料科学)
电子工程
传动系统
灰度
物理
卷积神经网络
通信系统
比例(比率)
自适应光学
角动量
人工神经网络
工程类
遥感
缩放比例
光学性能监测
自由空间光通信
人工智能
作者
Yao, Linxuan,Yuan, Yangsheng,Gao, Yaru,Hoenders, Bernhard,Wei, Dong,Cai, Yangjian,Zeng, Jun,Zhang, Hui
标识
DOI:10.6084/m9.figshare.c.7975364.v1
摘要
Increasing capacity and improving accuracy of free-space optical (FSO) communication is an urgent demand .We introduce a high-dimensional data transmission system (with a < 1 kHz refresh rate) based on high-order partially coherent Laguerre-Gaussian (LG) beams, that provides resilience against a turbulent atmosphere. Beyond encoding in the orbital angular momentum (OAM) dimension, we expand the encoding dimensions of partially coherent LG beams by including the radial index and coherence length. This method increases the capacity of data transmission even further. The convolutional neural network (CNN) is introduced to enhance the capability of extracting information features from high-order partially coherent LG beams. We experimentally demonstrated that even in a strong turbulent atmosphere with a temperature difference ΔT=175K, the accuracy of transmitting 128-level grayscale images reached 97.94%. Our communication system therefore provides a turbulence-resilient solution for high-capacity FSO communication.
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