UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Optimization of 125-mu m Heterogeneous Multi-Core Fibre Design Using Artificial Intelligence

Mu, X; Ottino, A; Ferreira, FM; Zervas, G; (2022) Optimization of 125-mu m Heterogeneous Multi-Core Fibre Design Using Artificial Intelligence. IEEE Journal of Selected Topics in Quantum Electronics , 28 (4) , Article 4300113. 10.1109/JSTQE.2021.3104821. Green open access

[thumbnail of Optimization_of_125um_Heterogeneous_Multi-Core_Fibres_Design_using_AI.pdf]
Preview
Text
Optimization_of_125um_Heterogeneous_Multi-Core_Fibres_Design_using_AI.pdf - Accepted Version

Download (1MB) | Preview

Abstract

We propose an automated heterogeneous trench-assisted multi-core fibre (MCF) design method. This method uses neural networks to speed up coating loss estimation by ∼ 10^{6} times and using particle swarm optimization (PSO) algorithm to explore the optimal MCF design under various objectives and properties constraints. The latter reduces the permutation evaluations by ten orders of magnitude compared with the brute force method. The artificial intelligence (AI)-based method is used to design MCFs on two objectives: minimizing crosstalk (XT) and maximizing effective mode area ( A_{eff} ). By optimizing XT with different A_{eff} and cutoff wavelength constraints combinations for 6-core fibres, we achieved −92.1 dB/km ultra-low XT for C+L band fibre and −64 dB/km for E+S+C+L-band fibre. Meanwhile, we explored the upper limit of A_{eff} given different bandwidth constraints resulting in a 6.82 relative core multiplicity factor. We performed capacity analysis of fibres for two transmission lengths. It is shown that bandwidth is the dominant factor while the increase brought by A_{eff} and the penalty caused by XT are relevantly small. Our fibres exceed the cutoff-limited capacity of the 7-core fibre in literature by 35.1% and 84.8% for 1200 km and 6000 km transmission respectively.

Type: Article
Title: Optimization of 125-mu m Heterogeneous Multi-Core Fibre Design Using Artificial Intelligence
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/JSTQE.2021.3104821
Publisher version: https://doi.org/10.1109/JSTQE.2021.3104821
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
Keywords: Space division multiplexing (SDM), Multi-core fibre (MCF), Particle swarm optimization (PSO), crosstalk, wide-band transmission, long-haul transmission
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10132949
Downloads since deposit
241Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item