Physics-based deep learning for fiber-optic communication systems
C Häger, HD Pfister - IEEE Journal on Selected Areas in …, 2020 - ieeexplore.ieee.org
We propose a new machine-learning approach for fiber-optic communication systems
whose signal propagation is governed by the nonlinear Schrödinger equation (NLSE). Our …
whose signal propagation is governed by the nonlinear Schrödinger equation (NLSE). Our …
Deep learning based digital backpropagation demonstrating SNR gain at low complexity in a 1200 km transmission link
A deep learning (DL) based digital backpropagation (DBP) method with a 1 dB SNR gain
over a conventional 1 step per span DBP is demonstrated in a 32 GBd 16QAM transmission …
over a conventional 1 step per span DBP is demonstrated in a 32 GBd 16QAM transmission …
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 …
Comparative study of neural network architectures for modelling nonlinear optical pulse propagation
Ultrashort pulses have a crucial role in the evolution of different areas of science such as
ultra fast imaging, femtochemistry and high harmonic spectroscopy and therefore …
ultra fast imaging, femtochemistry and high harmonic spectroscopy and therefore …
A Parametric Network for the Global Compensation of Physical Layer Linear Impairments in Coherent Optical Communications
This paper proposes a parametric network for the joint compensation of multiple linear
impairments in coherent optical communication systems. The considered linear impairments …
impairments in coherent optical communication systems. The considered linear impairments …
Reducing training time of deep learning based digital backpropagation by stacking
BI Bitachon, M Eppenberger… - IEEE Photonics …, 2022 - ieeexplore.ieee.org
A method for reducing the training time of a deep learning based digital backpropagation
(DL-DBP) is presented. The method is based on dividing a link into smaller sections. A …
(DL-DBP) is presented. The method is based on dividing a link into smaller sections. A …
Weight pruning techniques towards photonic implementation of nonlinear impairment compensation using neural networks
Neural networks (NNs) are attractive for nonlinear impairment compensation applications in
communication systems, such as optical fiber nonlinearity, nonlinearity of driving amplifiers …
communication systems, such as optical fiber nonlinearity, nonlinearity of driving amplifiers …
Improving the Resistance of AO-OFDM Signal to Fiber Four-Wave Mixing Effect Based on Insertion Guard Interval
K Lv, H Liu, A Zhang, L Feng, X Sheng, Y Liu, J Li… - Photonics, 2023 - mdpi.com
In this paper, a method to suppress the impact of the nonlinear effects on an all optical
orthogonal frequency division multiplexing (AO-OFDM) system is proposed. By inserting a …
orthogonal frequency division multiplexing (AO-OFDM) system is proposed. By inserting a …
Learned modified perturbation backpropagation for fiber nonlinear equalization in high-symbol-rate transmission systems
Z Wu, D Tang, Y Jiang, Y Lu, Y Qiao - Optics Communications, 2022 - Elsevier
A novel learned modified perturbation backpropagation (L-MPBP) algorithm for high-symbol-
rate (HSR) coherent optical transmission system is proposed in this paper. As an extension …
rate (HSR) coherent optical transmission system is proposed in this paper. As an extension …
Machine learning for optical fibre communication systems
J Nevin - 2023 - repository.cam.ac.uk
Global demand for internet traffic is growing at a rapid rate, driven by the adoption of new
technologies and increased demand from consumers. This continued growth is exerting …
technologies and increased demand from consumers. This continued growth is exerting …