Machine learning for optical fiber communication systems: An introduction and overview
Optical networks generate a vast amount of diagnostic, control, and performance monitoring
data. When information is extracted from these data, reconfigurable network elements and …
data. When information is extracted from these data, reconfigurable network elements and …
Digital Twin of Optical Networks: A Review of Recent Advances and Future Trends
Digital twin (DT) has revolutionized optical communication networks by enabling their full life-
cycle management, including planning, prediction, optimization, upgrade, and …
cycle management, including planning, prediction, optimization, upgrade, and …
Deep learning based end-to-end visible light communication with an in-band channel modeling strategy
Aside from ambient light noise, shot noise, and linear/nonlinear effects, strong low-frequency
noise (LFN) severely affects the signal quality in LED-based visible light communication …
noise (LFN) severely affects the signal quality in LED-based visible light communication …
Optical power control for GSNR optimization based on C+ L-band digital twin systems
The generalized signal-to-noise ratio (GSNR) is a typical metric for quality of transmission
(QoT), which in wideband systems may not be uniform without adjustment after multi-span …
(QoT), which in wideband systems may not be uniform without adjustment after multi-span …
Measurement informed models and digital twins for optical fiber communication systems
Digital coherent transceivers have developed to the stage that they can monitor the physical
state of an optical network and thus are capable of generating data to build measurement …
state of an optical network and thus are capable of generating data to build measurement …
[PDF][PDF] Machine learning enhancement of a digital twin for WDM network performance prediction leveraging Quality of Transmission parameter refinement
Digital twins hold the promise of enabling efficient design and operation of complex optical
networks. They may be used as tools for offline system simulation and aid the design of …
networks. They may be used as tools for offline system simulation and aid the design of …
Tandem structure neural network-based channel power optimization in wavelength-division multiplexing systems
For C-band wavelength-division multiplexing (WDM) transmission systems, achieving
balanced output channel power is a practical goal for performance maintenance, given the …
balanced output channel power is a practical goal for performance maintenance, given the …
Measurement Informed Models and Digital Twins for Optical Fiber Communication Systems
Digital coherent transceivers have developed to the stage that they can monitor the physical
state of an optical network and thus are capable of generating data to build measurement …
state of an optical network and thus are capable of generating data to build measurement …
Machine learning enhancement of a digital twin for wavelength division multiplexing network performance prediction leveraging quality of transmission parameter …
N Morette, H Hafermann, Y Frignac… - Journal of Optical …, 2023 - opg.optica.org
Digital twins capable of quality of transmission (QoT) estimation and prediction are powerful
tools for efficient design and operation of optical networks. In this paper, we employ machine …
tools for efficient design and operation of optical networks. In this paper, we employ machine …
Channel Power Control for Full C-band Generalized Signal-to-Noise Ratio Optimization Based on Deep Reinforcement Learning
J Xiao, Z Niu, L Li, M Shi, W Hu… - … Asia Communications and …, 2024 - ieeexplore.ieee.org
Channel Power Control for Full C-band Generalized Signal-to-Noise Ratio Optimization Based
on Deep Reinforcement Learning Page 1 Channel Power Control for Full C-band Generalized …
on Deep Reinforcement Learning Page 1 Channel Power Control for Full C-band Generalized …