Neural-Network-Based Nonlinearity Equalizer for 128 GBaud Coherent Transcievers

Conference Paper (2021)
Author(s)

Vladislav Neskorniuk (Aston University, Nokia Bell Labs)

Fred Buchali (Nokia Bell Labs)

V. Bajaj (TU Delft - Team Sander Wahls, Nokia Bell Labs)

Sergei K. Turitsyn (Aston University)

Jaroslaw E. Prilepsky (Aston University)

Vahid Aref (Nokia Bell Labs)

Research Group
Team Sander Wahls
More Info
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Publication Year
2021
Language
English
Research Group
Team Sander Wahls
ISBN (electronic)
978-1-943580-86-6

Abstract

We propose an efficient neural-network-based equalization jointly compensating fiber and transceiver nonlinearities for high-symbol-rate coherent short-reach links. Providing about 0.9 dB extra SNR gain, it allows achieving experimentally the record single-channel 1.48 Tbps net rate over 240 km G.652 fiber.

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