학술논문

Impairment Identification for PAM-4 Transceivers and Links Using Machine Learning
Document Type
Conference
Source
2021 Optical Fiber Communications Conference and Exhibition (OFC) Optical Fiber Communications Conference and Exhibition (OFC), 2021. :1-3 Jun, 2021
Subject
Communication, Networking and Broadcast Technologies
Photonics and Electrooptics
Training
Degradation
Maximum likelihood estimation
Bandwidth
Machine learning
Data models
Transceivers
Language
Abstract
We demonstrate simultaneous TDECQ estimation and impairment identification using convolutional neural networks. Robust training with representative impairments yielded identification accuracy of 100% for TDECQ >2.6 dB, when considering limited bandwidth, signal compression and SNR degradation.