Fast signal quality monitoring for coherent communications enabled by CNN-based EVM estimation

被引：11

作者：

Fan, Yuchuan ^{[1
,2
]}

Udalcovs, Aleksejs ^{[2
]}

Pang, Xiaodan ^{[1
,2
]}

Natalino, Carlos ^{[3
]}

Furdek, Marija ^{[3
]}

Popov, Sergei ^{[1
]}

Ozolins, Oskars ^{[1
,2
]}

机构：

[1] KTH Royal Inst Technol, Sch Engn Sci, Isafjordsgatan 22, S-16440 Kista, Sweden

[2] RISE Res Inst Sweden, Isafjordsgatan 22, S-16440 Kista, Sweden

[3] Chalmers Univ Technol, Dept Elect Engn, Chalmersplatsen 4, S-41296 Gothenburg, Sweden

来源：

JOURNAL OF OPTICAL COMMUNICATIONS AND NETWORKING | 2021年 / 13卷 / 04期

关键词：

JOINT OSNR;

D O I：

10.1364/JOCN.409704

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose a fast and accurate signal quality monitoring scheme that uses convolutional neural networks for error vector magnitude (EVM) estimation in coherent optical communications. We build a regression model to extract EVM information from complex signal constellation diagrams using a small number of received symbols. For the additive-white-Gaussian-noise-impaired channel, the proposed EVM estimation scheme shows a normalized mean absolute estimation error of 3.7% for quadrature phase-shift keying, 2.2% for 16-ary quadrature amplitude modulation (16QAM), and 1.1% for 64QAM signals, requiring only 100 symbols per constellation cluster in each observation period. Therefore, it can be used as a low-complexity alternative to conventional biterror-rate estimation, enabling solutions for intelligent optical performance monitoring. (C) 2021 Optical Society of America

引用

页码：B12 / B20

页数：9

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