DOAJ Open Access 2023

Experimental Demonstration of Linear Inter-Channel Interference Estimation Based on Neural Networks

A. Hraghi L. Minelli A. Nespola S. Piciaccia G. Bosco

Abstrak

In this paper, an algorithm for the estimation of the linear inter-channel crosstalk in a dense-WDM polarization-multiplexed 16-QAM transmission scenario is proposed and demonstrated. The algorithm is based on the use of a feed-forward neural network (FFNN) inside the coherent digital receiver. Two types of FFNNs were considered, the first based on a regression algorithm and the second based on a classification algorithm. Both FFNN algorithms are applied to features extracted from the histograms of the in-phase and quadrature components of the equalized digital samples. After a simulative investigation, the performance of the channel spacing estimation algorithms was experimentally validated in a 3 × 52 Gbaud 16-QAM WDM system scenario.

Topik & Kata Kunci

Applied optics. Photonics Optics. Light

Penulis (5)

A. Hraghi

L. Minelli

A. Nespola

S. Piciaccia

G. Bosco

Format Sitasi

APA MLA BibTeX

Hraghi, A., Minelli, L., Nespola, A., Piciaccia, S., Bosco, G. (2023). Experimental Demonstration of Linear Inter-Channel Interference Estimation Based on Neural Networks. https://doi.org/10.1109/JPHOT.2023.3259009

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Informasi Jurnal

Tahun Terbit: 2023
Sumber Database: DOAJ
DOI: 10.1109/JPHOT.2023.3259009
Akses: Open Access ✓