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- W4328007217 abstract "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." @default.
- W4328007217 created "2023-03-22" @default.
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- W4328007217 date "2023-04-01" @default.
- W4328007217 modified "2023-10-14" @default.
- W4328007217 title "Experimental Demonstration of Linear Inter-Channel Interference Estimation Based on Neural Networks" @default.
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- W4328007217 doi "https://doi.org/10.1109/jphot.2023.3259009" @default.
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