Sparse Identification for Nonlinear Optical Communication Systems

被引：0

作者：

Sorokina, Mariia ^{[1
]}

Sygletos, Stylianos ^{[1
]}

Turitsyn, Sergei ^{[1
]}

机构：

[1] Aston Univ, Aston Inst Photon Technol, Birmingham B4 7ET, W Midlands, England

来源：

2017 19TH INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS (ICTON) | 2017年

基金：

欧盟第七框架计划; 英国工程与自然科学研究理事会;

关键词：

nonlinear analysis; machine learning; fiber optic communications; spatial division multiplexing; COMPENSATION;

D O I：

暂无

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 have developed a low complexity machine learning based nonlinear impairment equalization scheme and demonstrated its successful performance in SDM transmission links achieving compensation of both inter- and intra- channel Kerr-based nonlinear effects. The method operates in one sample per symbol and in one computational step. It is adaptive, i.e. it does not require a knowledge of system parameters, and it is scalable to different power levels and modulation formats. The method can be straightforwardly expanded to multi-channel systems and to any other type of nonlinear impairment.

引用

页数：4

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