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

页码：1089 / 1092

页数：4

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