Fast signal quality monitoring for coherent communications enabled by CNN-based EVM estimation
Artikel i vetenskaplig tidskrift, 2021

We propose a fast and accurate signal quality monitoring scheme that uses convolutional neural networks (CNN) 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 (AWGN) impaired channel, the proposed EVM estimation scheme shows a normalized mean absolute estimation error of 3.7% for quadrature phase shift keying (QPSK), 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 bit-error-rate (BER) estimation, enabling solutions for intelligent optical performance monitoring.

Författare

Yuchuan Fan

RISE Research Institutes of Sweden

Kungliga Tekniska Högskolan (KTH)

Aleksejs Udalcovs

RISE Research Institutes of Sweden

Xiaodan Pang

RISE Research Institutes of Sweden

Kungliga Tekniska Högskolan (KTH)

Carlos Natalino Da Silva

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Optiska nätverk

Marija Furdek Prekratic

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Optiska nätverk

Sergei Popov

Kungliga Tekniska Högskolan (KTH)

Oskars Ozolins

RISE Research Institutes of Sweden

Kungliga Tekniska Högskolan (KTH)

Journal of Optical Communications and Networking

1943-0620 (ISSN)

Vol. 13 4 B12-B20 409704

Skydda optiska kommunikationsnätverk från cyber-säkerhetsattacker

Vetenskapsrådet (VR), 2020-01-01 -- 2023-12-31.

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Telekommunikation

DOI

10.1364/JOCN.409704

Relaterade dataset

2020_JOCN_CONSTELLATION_DATASET [dataset]

URI: https://ieee-dataport.org/documents/2020jocnconstellationdataset DOI: 10.21227/1684-a275

Mer information

Senast uppdaterat

2021-02-24