An optical communication's perspective on machine learning and its applications
Machine learning (ML) has disrupted a wide range of science and engineering disciplines in
recent years. ML applications in optical communications and networking are also gaining …
recent years. ML applications in optical communications and networking are also gaining …
Application of machine learning in fiber nonlinearity modeling and monitoring for elastic optical networks
Fiber nonlinear interference (NLI) modeling and monitoring are the key building blocks to
support elastic optical networks. In the past, they were normally developed and investigated …
support elastic optical networks. In the past, they were normally developed and investigated …
A survey on machine learning for optical communication [machine learning view]
MA Amirabadi - arXiv preprint arXiv:1909.05148, 2019 - arxiv.org
Machine Learning (ML) for Optical Communication (OC) is certainly a hot topic emerged
recently and will continue to raise interest at least for the next few years. The rate of research …
recently and will continue to raise interest at least for the next few years. The rate of research …
Practical considerations for near-zero margin network design and deployment
Maximizing the delivered capacity of optical transponders by mining the SNR margin to a
near-zero level is of critical importance for the economic viability of future optical networks …
near-zero level is of critical importance for the economic viability of future optical networks …
Fiber nonlinear noise-to-signal ratio estimation by machine learning
Fiber Nonlinear Noise-to-Signal Ratio Estimation by Machine Learning Page 1 Th2A.45.pdf
OFC 2019 © OSA 2019 Fiber Nonlinear Noise-to-Signal Ratio Estimation by Machine Learning …
OFC 2019 © OSA 2019 Fiber Nonlinear Noise-to-Signal Ratio Estimation by Machine Learning …
Optical filtering penalty estimation using artificial neural network in elastic optical networks with cascaded reconfigurable optical add–drop multiplexers
B Zhang, R Zhang, Q Zhang, X Xin - Optical Engineering, 2019 - spiedigitallibrary.org
For future elastic optical networks, the narrow filtering effect induced by cascaded
reconfigurable optical add–drop multiplexers (ROADMs) is one of the major impairments. It …
reconfigurable optical add–drop multiplexers (ROADMs) is one of the major impairments. It …
Artificial neural network-based equaliser in the nonlinear Fourier domain for fibre-optic communication applications
M Kamalian-Kopae, A Vasylchenkova… - 2019 Conference on …, 2019 - ieeexplore.ieee.org
Nonlinear Fourier transform (NFT) has shown its potential to overcome some challenges of
nonlinear signal distortions in fibre-optic communications ystems [1]. However, there is yet …
nonlinear signal distortions in fibre-optic communications ystems [1]. However, there is yet …
OSNR estimation providing self-confidence level as auxiliary output from neural networks
Accurate optical monitors are critical for automating operations of fiber-optic networks. Deep
neural network (DNN) based optical monitors have been investigated as accurate optical …
neural network (DNN) based optical monitors have been investigated as accurate optical …
Pilot-aided self-phase modulation noise monitoring based on artificial neural network
Pilot-aided Self-phase Modulation Noise Monitoring Based on Artificial Neural Network Page 1
M4A.9.pdf Asia Communications and Photonics Conference (ACP) © OSA 2019 Pilot-aided …
M4A.9.pdf Asia Communications and Photonics Conference (ACP) © OSA 2019 Pilot-aided …
Machine learning techniques to mitigate nonlinear phase noise in moderate baud rate optical communication systems
Nonlinear phase noise (NLPN) is the most common impairment that degrades the
performance of radio-over-fiber networks. The effect of NLPN in the constellation diagram …
performance of radio-over-fiber networks. The effect of NLPN in the constellation diagram …