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This article is cited in 2 scientific papers (total in 2 papers)
Selection of reports presented at the 8th All-Russian conference on fibre optics (5-8 October 2021, Perm) (compiled and edited by S.L.Semjonov)
Application of complex fully connected neural networks to compensate for nonlinearity in fibre-optic communication lines with polarisation division multiplexing
S. A. Bogdanov, O. S. Sidelnikov, A. A. Redyuk Novosibirsk State University
Abstract:
A scheme is proposed to compensate for nonlinear distortions in extended fibre-optic communication lines with polarisation division multiplexing, based on fully connected neural networks with complex-valued arithmetic. The activation function of the developed scheme makes it possible to take into account the nonlinear interaction of signals from different polarisation components. This scheme is compared with a linear one and a neural network that processes signals of different polarisations independently, and the superiority of the proposed neural network architecture is demonstrated.
Keywords:
fibre-optic communication systems, nonlinearity of optical fibre, fully connected neural networks, polarisation division multiplexing, compensation of nonlinear distortions.
Received: 26.10.2021
Citation:
S. A. Bogdanov, O. S. Sidelnikov, A. A. Redyuk, “Application of complex fully connected neural networks to compensate for nonlinearity in fibre-optic communication lines with polarisation division multiplexing”, Kvantovaya Elektronika, 51:12 (2021), 1076–1080 [Quantum Electron., 51:12 (2021), 1076–1080]
Linking options:
https://www.mathnet.ru/eng/qe17947 https://www.mathnet.ru/eng/qe/v51/i12/p1076
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Statistics & downloads: |
Abstract page: | 118 | Full-text PDF : | 20 | References: | 17 | First page: | 7 |
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