Complex-valued neural network design for mitigation of signal distortions in optical links
Nonlinearity compensation is considered as a key enabler to increase channel transmission
rates in the installed optical communication systems. Recently, data-driven approaches …
rates in the installed optical communication systems. Recently, data-driven approaches …
Advanced convolutional neural networks for nonlinearity mitigation in long-haul WDM transmission systems
Practical implementation of digital signal processing for mitigation of transmission
impairments in optical communication systems requires reduction of the complexity of the …
impairments in optical communication systems requires reduction of the complexity of the …
Revisiting efficient multi-step nonlinearity compensation with machine learning: An experimental demonstration
Efficient nonlinearity compensation in fiber-optic communication systems is considered a
key element to go beyond the “capacity crunch”. One guiding principle for previous work on …
key element to go beyond the “capacity crunch”. One guiding principle for previous work on …
Transfer learning for neural networks-based equalizers in coherent optical systems
In this work, we address the question of the adaptability of artificial neural networks (NNs)
used for impairments mitigation in optical transmission systems. We demonstrate that by …
used for impairments mitigation in optical transmission systems. We demonstrate that by …
Compensation of fiber nonlinearities in digital coherent systems leveraging long short-term memory neural networks
We introduce for the first time the utilization of Long short-term memory (LSTM) neural
network architectures for the compensation of fiber nonlinearities in digital coherent systems …
network architectures for the compensation of fiber nonlinearities in digital coherent systems …
Fiber nonlinearity compensation: commercial applications and complexity analysis
D Rafique - Journal of Lightwave Technology, 2016 - opg.optica.org
Fiber nonlinearities define the ultimate performance bound for optical communication
systems. Todays 100 Gb/s commercial products employ advanced digital signal processing …
systems. Todays 100 Gb/s commercial products employ advanced digital signal processing …
SNR optimization of multi-span fiber optic communication systems employing EDFAs with non-flat gain and noise figure
Throughput optimization of optical communication systems is a key challenge for current
optical networks. The use of gain-flattening filters (GFFs) simplifies the problem at the cost of …
optical networks. The use of gain-flattening filters (GFFs) simplifies the problem at the cost of …
Machine learning methods for optical communication systems
Machine Learning Methods for Optical Communication Systems Page 1 SpW2F.3.pdf Advanced
Photonics Congress (IPR, Networks, NOMA, PS, Sensors, SPPCom) © OSA 2017 1 Machine …
Photonics Congress (IPR, Networks, NOMA, PS, Sensors, SPPCom) © OSA 2017 1 Machine …
Applications of machine-learning in optical communications and networks
We discuss various applications of machine learning techniques in different aspects of
optical communications and networking including optical performance monitoring, fiber …
optical communications and networking including optical performance monitoring, fiber …
Performance and complexity analysis of bi-directional recurrent neural network models versus volterra nonlinear equalizers in digital coherent systems
S Deligiannidis, C Mesaritakis… - Journal of Lightwave …, 2021 - opg.optica.org
We investigate the complexity and performance of recurrent neural network (RNN) models
as post-processing units for the compensation of fibre nonlinearities in digital coherent …
as post-processing units for the compensation of fibre nonlinearities in digital coherent …