Fiber-length agnostic all-optical equalisation using silicon photonics neural networks

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Authors: Ruben van Assche, Sarah Masaad, Emmanuel Gooskens, Stijn Sackesyn, Joris Van Kerrebrouck, Xin Yin, Peter Bienstman
Cited by: 0
References: 15

Abstract

Signal integrity in high-speed intensity-modulation direct-detection (IM/DD) fibre links is limited by chromatic dispersion, Kerr-induced nonlinearities, and the frequency-dependent response of the transmitter–receiver chain. We demonstrate an integrated photonic reservoir with a programmable optical readout for pre-detection equalisation of a 28 Gbps on–off keying (OOK) signal. Using a fixed reservoir architecture and delay configuration, experimental bit-error rates as low as 4×10-7 are achieved, remaining below the generic forward-error-correction (GFEC) threshold of 5.8×10-5 for fibre lengths up to 50 km at a launch power of 10 dBm and launch powers up to 17 dBm at a fiber length of 25 km. Numerical simulations are used to assess the impact of data-rate mismatch relative to the reservoir design point. Robust performance is obtained without reconfiguration of the photonic hardware, requiring only optimisation of the readout weights for different operating conditions.

Fields of Study & Subjects

Neural Networks and Reservoir Computing Optical Network Technologies Advanced Photonic Communication Systems

Publication details

Journal / source
AI and Optical Data Sciences
Pages
43–43
Publication date
4 March 2026
Language
EN