Increasing the Capacity of Optical Nonlinear Interfering Channels
Optical fibers are strands of glass with the thickness of human hair that carry nearly all the world's Internet traffic. However, the installed fibers are running out of capacity. This project will use mathematics to increase the capacity of these fibers, which will guarantee faster future broadband connections.
Duration
August 2017 - July 2023Project Manager
In this project, we will answer different questions regarding information transmission through optical fibres. For example, what is the maximum amount of information that can be reliably transported by optical fibres? Or how to design coded modulation systems that approach this limit? To answer these questions, we will first develop accurate channel models for the nonlinear optical channel in the high-power regime. Novel coded modulation transceivers tailored to the nonlinear optical channel will then be designed. Techniques that will be considered in this project include (but not limited to):
• Signal (constellation) shaping: geometrical and probabilistic shaping;
• Error control coding (FEC), coded modulation, and maximum likelihood detection;
• Asymptotic analysis and mismatched decoding theory;
• Nonlinear compensation techniques, such as digital back-propagation and Volterra equalizers;
• Novel signaling techniques: nonlinear Fourier transform and eigenvalue communications.
In this project, we will answer different questions regarding information transmission through optical fibres. For example, what is the maximum amount of information that can be reliably transported by optical fibres? Or how to design coded modulation systems that approach this limit? To answer these questions, we will first develop accurate channel models for the nonlinear optical channel in the high-power regime. Novel coded modulation transceivers tailored to the nonlinear optical channel will then be designed. Techniques that will be considered in this project include (but not limited to):
• Signal (constellation) shaping: geometrical and probabilistic shaping;
• Error control coding (FEC), coded modulation, and maximum likelihood detection;
• Asymptotic analysis and mismatched decoding theory;
• Nonlinear compensation techniques, such as digital back-propagation and Volterra equalizers;
• Novel signaling techniques: nonlinear Fourier transform and eigenvalue communications.
Our Partners
Project Related Publications
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Caio Santos,Vinícius Oliari,Helder Roberto O. de Rocha,Maria José Pontes,Marcelo E.V. Segatto,Chigo M. Okonkwo,Alex Alvarado,Jair A.L. Silva
Experimental Demonstration of Constant-Envelope OFDM to Reduce Intermodulation Impairments and Increase Robustness Against Fiber Nonlinearities
Journal of Lightwave Technology (2022) -
Alex Alvarado,Kaiquan Wu,Alexios Balatsoukas-Stimming
Reducing the Error Floor of the Sign-Preserving Min-Sum LDPC Decoder via Message Weighting of Low-Degree Variable Nodes
arXiv (2022) -
Kaiquan Wu,Gabriele Liga,Alireza Sheikh,Yunus Can Gültekin,Frans M.J. Willems,Alex Alvarado
List-encoding CCDM: A Nonlinearity-tolerant Shaper Aided by Energy Dispersion Index
Journal of Lightwave Technology (2022) -
Vinícius Oliari Couto Dias
Channel Modeling and Machine Learning for Nonlinear Fiber Optics
(2022) -
Vinícius Oliari,Boris Karanov,Sebastiaan Goossens,Gabriele Liga,Olga Vassilieva,Inwoong Kim,Paparao Palacharla,Chigo Okonkwo,Alex Alvarado
High-Cardinality Hybrid Shaping for 4D Modulation Formats in Optical Communications Optimized via End-to-End Learning
arXiv (2021)
Researchers involved in this project
Project Related Publications
-
Caio Santos,Vinícius Oliari,Helder Roberto O. de Rocha,Maria José Pontes,Marcelo E.V. Segatto,Chigo M. Okonkwo,Alex Alvarado,Jair A.L. Silva
Experimental Demonstration of Constant-Envelope OFDM to Reduce Intermodulation Impairments and Increase Robustness Against Fiber Nonlinearities
Journal of Lightwave Technology (2022) -
Alex Alvarado,Kaiquan Wu,Alexios Balatsoukas-Stimming
Reducing the Error Floor of the Sign-Preserving Min-Sum LDPC Decoder via Message Weighting of Low-Degree Variable Nodes
arXiv (2022) -
Kaiquan Wu,Gabriele Liga,Alireza Sheikh,Yunus Can Gültekin,Frans M.J. Willems,Alex Alvarado
List-encoding CCDM: A Nonlinearity-tolerant Shaper Aided by Energy Dispersion Index
Journal of Lightwave Technology (2022) -
Vinícius Oliari Couto Dias
Channel Modeling and Machine Learning for Nonlinear Fiber Optics
(2022) -
Vinícius Oliari,Boris Karanov,Sebastiaan Goossens,Gabriele Liga,Olga Vassilieva,Inwoong Kim,Paparao Palacharla,Chigo Okonkwo,Alex Alvarado
High-Cardinality Hybrid Shaping for 4D Modulation Formats in Optical Communications Optimized via End-to-End Learning
arXiv (2021)