End-to-end Autoencoder for Superchannel Transceivers with Hardware Impairment

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Mar 29, 2021
Jinxiang Song, Christian Häger, Jochen Schröder, Alexandre Graell i Amat, Henk Wymeersch
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We propose an end-to-end learning-based approach for superchannel systems impaired by non-ideal hardware component. Our system achieves up to 60% SER reduction and up to 50% guard band reduction compared with the considered baseline scheme.

* Accepted for oral presentation on the Optical Networking and Communication Conference & Exhibition (OFC 2021)  
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