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：
英国工程与自然科学研究理事会; 欧盟第七框架计划;
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.
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页数：4
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