Increasing the Capacity of Optical Nonlinear Interfering Channels

Project: Research direct

Project Details

Description

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.

Layman's description

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.
AcronymICONIC
StatusActive
Effective start/end date1/08/1731/07/22

Research Output

  • 17 Article
  • 6 Conference contribution
  • 2 Conference article
  • 1 Poster

Coded modulation for 100G coherent EPON

Gerard, T., Dzieciol, H., Sillekens, E., Wakayama, Y., Alvarado, A., Killey, R. I., Bayvel, P. & Lavery, D., 1 Feb 2020, In : Journal of Lightwave Technology. 38, 3, p. 564-572 9 p., 8831407.

Research output: Contribution to journalArticleAcademicpeer-review

  • 2 Downloads (Pure)

    Regular perturbation on the group-velocity dispersion parameter for nonlinear fibre-optical communications

    Oliari, V., Agrell, E. & Alvarado, A., 1 Dec 2020, In : Nature Communications. 11, 11 p., 933.

    Research output: Contribution to journalArticleAcademicpeer-review

    Open Access
    File
  • 17 Downloads (Pure)

    Revisiting Efficient Multi-Step Nonlinearity Compensation with Machine Learning: An Experimental Demonstration

    Oliari, V., Goossens, S., Häger, C., Liga, G., Bütler, R. M., van den Hout, M., van der Heide, S., Pfister, H. D., Okonkwo, C. M. & Alvarado, A., 15 Jun 2020, In : Journal of Lightwave Technology. 38, 12, p. 3114-3124 11 p., 9091867.

    Research output: Contribution to journalArticleAcademicpeer-review

  • Prizes

    Asia Communications and Photonics Conference(ACP) 2018 Best Paper Award

    Bin Chen (Recipient), Y. Lei (Recipient), Domaniç Lavery (Recipient), C.M. Okonkwo (Recipient) & Alex Alvarado (Recipient), 28 Nov 2018

    Prize: OtherCareer, activity or publication related prizes (lifetime, best paper, poster etc.)Scientific

  • Optoelectronics and Communications Conference (OECC 2019) Best Paper Award

    Sjoerd van der Heide (Recipient), Bin Chen (Recipient), M. van den Hout (Recipient), Gabriele Liga (Recipient), Ton Koonen (Recipient), Hartmut Hafermann (Recipient), Alex Alvarado (Recipient) & Chigo Okonkwo (Recipient), Jul 2019

    Prize: OtherCareer, activity or publication related prizes (lifetime, best paper, poster etc.)Scientific