| Acronym: SELFIE |
| Main Objective: The main objective of SELFIE is to design an integrated self-coherent MCF system that represents a novel solution that can be employed in next generation intra/inter data centres or access networks, and cope with the huge capacity demand experienced by these networks. To achieve this goal, the SELFIE project focuses on: (i) The development of direct-detection (DD) receivers based on self-coherent techniques as the Kramers Kronig (KK) algorithm, to improve the detection linearity, and the Stokes vector (SV) receiver, to exploit other degrees of freedom of the optical signal, to cope with high data rate signals transmission (≥200 Gb/s) while avoiding/mitigating transmission impairments as chromatic dispersion or signal-signal beat interference. (ii) The system performance optimization by testing DD-compatible transmission techniques, as virtual carrier-assisted DD-OFDM, or more complex quadrature amplitude modulation and single sideband modulation, and to evaluate their robustness to the random variation of the ICXT along time. (iii) To design a new MCF with higher core count than current standards and moderate to high crosstalk levels, -30 dB/km @ 1550 nm, still acceptable for short-reach applications. (iv) The proposal of machine learning to improve the robustness of the network performance to the random variation of the ICXT along time. In this context, three scenarios with different requirements on the ML algorithms are addressed: a) Point-to-point DD MCF systems • With |skew|×bit rate<<1, in which, from the ICXT standpoint, the MCF can be viewed as memoryless transmission channel. This is the simplest situation where shallow memoryless neural networks should be able to mitigate the random ICXT. • With |skew|×bit rate>>1, in which, from the ICXT standpoint, the MCF can be viewed as transmission channel with memory. Due to the memory effect of the channel, advanced deep learning algorithms, e. g., recurrent neural networks, must be employed to deal with the random ICXT. b) DD MCF networks with |skew|×bit rate<<1 or |skew|×bit rate>>1. This is the more complex situation as the data signals of the interfering core are not available at the receiver side because signals can be added or dropped from the network at any node. Thus, unsupervised learning is required to perform a blind tracking of the random variation of the ICXT along time. |
| Reference: 2023.16564.ICDT |
| Funding: FCT |
| Start Date: 03-11-2025 |
| End Date: 02-11-2028 |
| Team: Tiago Manuel Ferreira Alves, Adolfo da Visitação Tregeira Cartaxo, João Lopes Rebola, Paulo Miguel Nepomuceno Pereira Monteiro, Isiaka Ajewale Alimi, Bruno Tavares Brandão, Manuel dos Santos Neves, Beatriz Manata de Oliveira |
| Groups: Optical Communication Systems and Networking – Lx, Optical Communication Systems and Networking – Av |
| Partners: Technical University of Denmark, Heraeus Covantics |
| Local Coordinator: Tiago Manuel Ferreira Alves |
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