ComEx-4 Optical Communication: Signal Processing, Coding and Networks

Description of the theme

Optical fiber communication systems (OFC) are the central topic of ComEx-4 for which we are developing solutions to increase their capacity and their availability time while decreasing their energy consumption. The studied solutions include applying automatic learning algorithms, exploiting spectral and spatial parallel channels, and using novel integrated optical components. Automatic learning and artificial intelligence solutions are leveraged to enhance the design of optical transmission systems and to allow them to operate in the best possible conditions. Enhanced monitoring schemes of the optical telecom infrastructure are required to reduce allocated power margins by maintaining an up-to-date channel state information. Some other topics relating to OFC are also studied including: tailoring modulations and coding for the optical channel, mitigation of non-linear effects as well as the employment of the telecom fiber infrastructure to sense the surrounding environment.

On the other hand, optical wireless communications (OWC) has witnessed a revival recently among researchers in both academia and industry. The motivation behind the interest in OWC include relatively simple deployment, unlicensed bandwidth and high data rate. Practical outdoor applications include free-space optical communication (FSO) for backhaul links between base stations, for ground-to-satellite/satellite-to-ground and inter-satellite communication. Indoor applications include visible-light communication to establish Light-Fidelity (LiFi) access and positioning, and enable combining illumination and communication functionalities. We are interested in studying theoretical and practical perspectives of OWC and demonstrate the capability of this technology to achieve high data rates.

Hot topics

Some hot research topics of the theme

OFC: Monitoring the physical & network layers

Summary/main goals

Machine learning (ML) and artificial intelligence (AI) techniques are being praised as a new innovation direction to transform future optical communication systems. Signal processing paradigms based on conventional processing and ML (reinforcement learning, artificial neural networks,…) are being considered to solve critical problems. Recent applications include nonlinear transmission systems to mitigate non-linear interference resulting from Kerr effect in the fiber, network planning and performance prediction, cross-layer network optimizations for software-defined networks, autonomous and reliable self-healing networks, or even sensing using the optical telecom infrastructure.

Machine learning, autonomous optical fiber networks, dynamic networks, self-healing networks, network planning, performance prediction, optical fiber sensing

Researchers involved or interested

A few references

  • A May, E Awwad, P Ciblat, P Ramantanis, “Receiver-Based Localization and Estimation of Polarization Dependent Loss”, OptoElectronics and Communications Conference 2022
  • S Guerrier, K Benyahya, C Dorize, E Awwad, H Mardoyan J Renaudier, “Vibration Detection and Localization in Buried Fiber Cable after 80km of SSMF using Digital Coherent Sensing System with Co-Propagating 600Gb/s WDM Channels”, Optical Fiber Communication Conference 2022
  • J Darweesh, N Costa, A Napoli, B Spinnler, Y Jaouen, M Yousefi, “Few-bit quantization of neural networks for nonlinearity mitigation in a fiber transmission experiment”, European Conference on Optical Communications 2022
  • M. Freire, S. Mansfeld, D. Amar, F. Gillet, A. Lavignotte, C. Lepers, “Predicting optical power excursions in erbium doped fiber amplifiers using neural networks”, 2018 Asia Communications and Photonics Conference (ACP)
  • Danish Rafique and Luis Velasco, “Machine Learning for Network Automation: Overview, Architecture, and Applications [Invited Tutorial],” J. Opt. Commun. Netw. 10, 2018
  • F. Musumeci et al., “An Overview on Application of Machine Learning Techniques in Optical Networks,” in IEEE Communications Surveys & Tutorials, vol. 21, no. 2, pp. 1383-1408, 2019
  • B. Karanov et al., “End-to-End Deep Learning of Optical Fiber Communications,” in Journal of Lightwave Technology, vol. 36, no. 20, pp. 4843-4855, 15 Oct.15, 2018,
  • Faisal Nadeem Khan et al., “Chapter 21 – Machine learning methods for optical communication systems and networks,” Optical Fiber Telecommunications VII, Academic Press (2020), pp. 921-978.

OWC: Free-space and visible light communications

Summary/Main goals

Motivated by simple deployment and high rates compared to RF technologies, FSO communications are expanding rapidly. The capacity of various FSO intensity-modulated direct-detection channel models (SISO, MISO and MIMO) are being studied to define the fundamental limits of communication over these schemes with average and maximum intensity constraints. Practical signaling schemes can also be designed specifically for these channels. Data rate increases of ground-to-satellite and satellite-to-ground communications are required for various applications; for this purpose, coherent-detection based transmission transceiver schemes are investigated with new challenges of a different nature than for coherent optical fiber systems. To name a few, novel laser sources and adaptive optics are needed at the transceiver frontend for power-efficient communications. The channel model should also take into account atmospheric turbulences as well as other fading effects.

Terrestrial FSO, deep-space FSO, visible light communications

Researchers involved or interested

A few references

  • P. Lognone, J.-M. Conan, L. Paillier, N. Vedrenne, G. Rekaya-Ben Othman, “Channel Model of a Ground to Satellite Optical Link Pre-compensated by Adaptive Optics”, Advanced Photonics Congress (SPPCOM) 2022
  • P. Didier, H. Dely, O. Spitz, E. Awwad, T. Bonazzi, E. Rodriguez, C. Sirtori, F. Grillot, “Unipolar quantum technology enabling high-speed free-space communication in the long-wave infrared regime,” Conference on Lasers and Electro-Optics (CLEO), 2022
  • M. Z. Chowhury, M. T. Hossain, A. Islam, and Y. M. Jang, “A Comparative Survey of Optical Wireless Technologies: Architectures and Applications,” IEEE Access, vol. 6, pp. 9819-9840, March 2018.
  • Special Issue on Localisation, Communication and Networking with VLC, IEEE Journal on Selected Areas on Communications, vol. 36, no. 1, January 2018.
  • Special Section on Optical Wireless Technologies for 5G Communications and Beyond, IEEE Access, 2017.

Send us an email if you are interested / want to participate to one of these themes

Nom Prénom E-mail Affiliation
Awwad Elie LTCI, Telecom Paris
Lepers Catherine SAMOVAR, Telecom SudParis