2 research outputs found
End-to-end Autoencoder for Superchannel Transceivers with Hardware Impairments
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
Over-the-fiber Digital Predistortion Using Reinforcement Learning
We demonstrate, for the first time, experimental over-the-fiber training of
transmitter neural networks (NNs) using reinforcement learning. Optical
back-to-back training of a novel NN-based digital predistorter outperforms
arcsine-based predistortion with up to 60\% bit-error-rate reduction