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  • Conference on Lasers and Electro-Optics/Europe (CLEO/Europe 2023) and European Quantum Electronics Conference (EQEC 2023)
  • Technical Digest Series (Optica Publishing Group, 2023),
  • paper ci_6_3

Optical Eigenvalue Demodulation Using Neural Network and Estimation of the Number of Eigenvalues in the Preset Region

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Abstract

Optical eigenvalue communication systems use eigenvalues extracted from a matrix calculated by inverse scattering transform (IST) [1]. For on-off encoded eigenvalue modulation schemes, which allocate the on-off state of each eigenvalue to each bit, it is helpful to employ the neural network (NN) method on demodulation [2]. To reduce the time complexity to extract eigenvalues, we have proposed a demodulation scheme employing NN and a complex moment eigenvalue (CME) solver [3]. CME consists of a two-stage algorithm; the first is an estimation method of the number of eigenvalues in the preset arbitrary regions, and the second is the eigenvalue extraction based on the first-stage result. To further reduce complexity, this paper proposes a demodulation scheme using the NN and the estimation the number of eigenvalues, the 1st stage of CME, and the experiments report bit error rate (BER) characteristics compared with the related methods.

© 2023 IEEE

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