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Publication Detail
Deep intelligent spectral labelling and receiver signal distribution for optical links
  • Publication Type:
    Journal article
  • Authors:
    Xu T, Xu T, Darwazeh I
  • Publication date:
  • Journal:
    Optics Express
  • Volume:
  • Issue:
  • Article number:
  • Status:
  • Language:
  • Notes:
    © 2021. Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/).
A unique automatic receiver signal distribution strategy is proposed for private optical networks based on the concept of non-orthogonality. A non-orthogonal signal waveform can compress the spectral bandwidth, which not only fits a signal in a bandwidth limited scenario, but also enables the compression ratio information for labelling. Depending on a unique value of spectral compression, an end user destination can be correlated. A network edge node will rely on deep learning to intelligently identify each raw signal and forward it to corresponding end users with no sophisticated digital signal pre-processing. In this case, signal identification and distribution are faster while computationally intensive signal compensation and detection will be shifted to each end user since the receiver is highly dynamic and user-defined in private optical networks. An intelligent signal classifier will be trained considering various fiber transmission factors such as transmission distance, training dataset size and launch power. At the end, a universal classifier is obtained, which can be used to identify signals in a system for any fiber transmission distance and launch power.
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