Meta-learning-enabled accurate OSNR monitoring of directly detected QAM signals with one-shot training
Y Cheng, Z Yang, Z Yan, D Liu, S Fu, Y Qin - Optics Letters, 2022 - opg.optica.org
We experimentally demonstrate meta-learning-enabled accurate optical signal-to-noise ratio
(OSNR) monitoring of directly detected 16QAM signals with extremely few training data …
(OSNR) monitoring of directly detected 16QAM signals with extremely few training data …
Transfer learning simplified multi-task deep neural network for PDM-64QAM optical performance monitoring
We experimentally demonstrate a transfer learning (TL) simplified multi-task deep neural
network (MT-DNN) for joint optical signal-to-noise ratio (OSNR) monitoring and modulation …
network (MT-DNN) for joint optical signal-to-noise ratio (OSNR) monitoring and modulation …
Long short-term memory neural network (LSTM-NN) enabled accurate optical signal-to-noise ratio (OSNR) monitoring
Optical signal-to-noise ratio (OSNR) monitoring is essential to both the operation of reliable
and reconfigurable network and the supply of high quality-of-service. Recently, deep …
and reconfigurable network and the supply of high quality-of-service. Recently, deep …
Transfer learning assisted deep neural network for OSNR estimation
We propose a transfer learning assisted deep neural network (DNN) method for optical-
signal-to-noise ratio (OSNR) monitoring and realize fast remodel to response to various …
signal-to-noise ratio (OSNR) monitoring and realize fast remodel to response to various …
Accurate OSNR monitoring based on data-augmentation-assisted DNN with a small-scale dataset
Deep neural networks (DNNs) have been successfully applied for accurate optical signal-to-
noise ratio (OSNR) monitoring. However, the performance of OSNR monitoring substantially …
noise ratio (OSNR) monitoring. However, the performance of OSNR monitoring substantially …
Fast adaptation of multi-task meta-learning for optical performance monitoring
Y Zhang, P Zhou, Y Liu, J Wang, C Li, Y Lu - Optics Express, 2023 - opg.optica.org
An algorithm is proposed for few-shot-learning (FSL) jointing modulation format identification
(MFI) and optical signal-to-noise ratio (OSNR) estimation. The constellation diagrams of six …
(MFI) and optical signal-to-noise ratio (OSNR) estimation. The constellation diagrams of six …
Multi-task deep neural network (MT-DNN) enabled optical performance monitoring from directly detected PDM-QAM signals
We experimentally demonstrate a multi-task deep neutral network (MT-DNN) enabled
optical performance monitoring (OPM) for PDM-QPSK/8QAM/16QAM signals, by using the …
optical performance monitoring (OPM) for PDM-QPSK/8QAM/16QAM signals, by using the …
Linear regression vs. deep learning for signal quality monitoring in coherent optical systems
Error vector magnitude (EVM) is a metric for assessing the quality of m-ary quadrature
amplitude modulation (mQAM) signals. Recently proposed deep learning techniques, eg …
amplitude modulation (mQAM) signals. Recently proposed deep learning techniques, eg …
Joint OSNR monitoring and modulation format identification in digital coherent receivers using deep neural networks
We experimentally demonstrate the use of deep neural networks (DNNs) in combination
with signals' amplitude histograms (AHs) for simultaneous optical signal-to-noise ratio …
with signals' amplitude histograms (AHs) for simultaneous optical signal-to-noise ratio …
Joint modulation format identification and OSNR monitoring using cascaded neural network with transfer learning
J Zhang, Y Li, S Hu, W Zhang, Z Wan… - IEEE Photonics …, 2021 - ieeexplore.ieee.org
We propose a cascaded neural network (NN) to simultaneously identify the modulation
formats and monitor the optical-signal-to-noise ratio (OSNR). In the second-level network, it …
formats and monitor the optical-signal-to-noise ratio (OSNR). In the second-level network, it …