Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
Conferences > CLEOPR > 2022 > CMP9A > CMP9A_03

A Comparison of Linear Regression and Deep Learning Model for EVM Estimation in Coherent Optical Systems

Yuchuan Fan, Xiaodan Pang, Aleksejs Udalcovs, Carlos Natalino, Lu Zhang, Sandis Spolitis, Vjaceslavs Bobrovs, Richard Schatz, Xianbin Yu, Marija Furdek, Sergei Popov, and Oskars Ozolins

Not Accessible

Your library or personal account may give you access

Abstract

We experimentally investigate EVM estimation approaches based on linear regression and deep learning for 28 Gbaud coherent optical systems. We show that the estimation performances are comparable when the modulation format is known.

© 2022 IEEE

PDF Article
More Like This
EVM Estimation for Performance Monitoring in Coherent Optical Systems: An Approach of Linear Regression

Yuchuan Fan, Xiaodan Pang, Aleksejs Udalcovs, Carlos Natalino, Lu Zhang, Sandis Spolitis, Vjaceslavs Bobrovs, Richard Schatz, Xianbin Yu, Marija Furdek, Sergei Popov, and Oskars Ozolins
SW4E.8 CLEO: Science and Innovations (CLEO:S&I) 2022

Deep Learning Assisted Pre-Carrier Phase Recovery EVM Estimation for Coherent Transmission Systems

Yuchuan Fan, Aleksejs Udalcovs, Xiaodan Pang, Carlos Natalino, Richard Schatz, Marija Furdek, Sergei Popov, and Oskars Ozolins
STh1F.2 CLEO: Science and Innovations (CLEO:S&I) 2021

Deep Learning Approach to Estimate Interchannel Interference in gridless Nyquist-WDM Systems

Natalia Pérez Puentes, Alejandro Escobar Pérez, and Jhon James Granada Torres
JW5B.55 Frontiers in Optics (FiO) 2022

View More...
Select as filters
Select Topics Cancel
Top
       
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.
Privacy | Terms of Use