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ALPI

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ALl optical signal recovery by Photonic neural network Integrated in a transceiv...

ALl optical signal recovery by Photonic neural network Integrated in a transceiver module ALPI aims at the integration of a photonic neural network within an optical transceiver to increase the transmission capacity of the optical link. Based on a deep learning approach, the new compact device provides real time compen... ver más

30/04/2022

UNITN

150K€

Presupuesto del proyecto: 150K€

Líder del proyecto

UNIVERSITA DEGLI STUDI DI TRENTO No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 3 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2022-04-30

ERC-2020-POC: Call for proposals for ERC Proof of...

I+D

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

3 Participantes

UNITN

150.00K€ | Lider

CONSTRUCCIONES MECÁNICAS F....

313.16K€ | Participante

HIT

N.D. | Participante

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Duración del proyecto: 19 meses Fecha Inicio: 2020-09-11
Fecha Fin: 2022-04-30

Líder del proyecto

UNIVERSITA DEGLI STUDI DI TRENTO No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 150K€

Descripción del proyecto ALPI aims at the integration of a photonic neural network within an optical transceiver to increase the transmission capacity of the optical link. Based on a deep learning approach, the new compact device provides real time compensation of fiber nonlinearities which degrade optical signals. In fact, the tremendous growth of transmission bandwidth both in optical networks as well as in data centers is baffled by the optical fiber nonlinear Shannon capacity limit. Nowadays, computational intensive approaches based on power hungry software are commonly used to mitigate fiber nonlinearities. Here, we propose to integrate in the optical link the neuromorphic photonic circuits which we are currently developing in the ERC-AdG BACKUP project. Specifically, the proposed error-correction circuit implements a small all-optical complex-valued neural network which is able to recover distortion on the optical transmitted data caused by the Kerr nonlinearities in multiwavelength optical fibers. Network training is realized by means of efficient gradient-free methods using a properly designed data-preamble. A new neuromorphic transceiver demonstrator realized in active hybrid Si/InP technology will be designed, developed and tested on a 100 Gbps 80 km long optical link with multiple-levels symbols. The integrated neural network will mitigate the nonlinearities either by precompensation/autoencoding at the transmitter TX side or by data correction at the receiver RX side or by concurrently acting on both the TX and RX sides. This achievement will bear to the second ALPI’s goal: moving from the demonstrator to the industrialization of the improved transceiver. For this purposes, patents will be filed and a business plan will be developed in partnership with semiconductor, telecom and IT companies where a path to the commercialization will be individuated. The foreseen market is the big volume market of optical interconnection in large data centers or metro networks.

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