Power Profile Estimation of Optical Transmission Links Based on Machine Learning

被引：3
|
作者：
Schanner, Lucas Silva [1 ]
Da Cruz Junior, Jose Helio [1 ]
Sutili, Tiago [1 ]
Figueiredo, Rafael C. [1 ]
机构：
[1] CPQD Opt Commun Solut, BR-13086902 Campinas, SP, Brazil
来源：
IEEE PHOTONICS TECHNOLOGY LETTERS | 2021年 / 33卷 / 19期
关键词：
Nonlinear optics; Optical receivers; Adaptive optics; Power measurement; Optical polarization; Optical fiber communication; Optical distortion; Optical communications; unrepeatered transmission; digital signal processing; power profile estimation;
D O I：
10.1109/LPT.2021.3104508
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We propose a method for estimation of power profile in optical transmissions by employing machine learning optimization to a digital back-propagation model. The method allows to estimate the absolute power values along the link and it requires solely the coherently acquired data at the receiver-side. The estimated values are validated using experimental results from an unrepeatered transmission, employing remote and Raman amplification.
引用
收藏
页码：1089 / 1092
页数：4
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