Using accurate ISRS GN modeling and the fast-converging ASE-NL optimization algorithm, we demonstrate 6.2 Tbit/s throughput improvement in a 2-span ultra-wide-band system thanks to the use of the predicted total and per channel power.
A preemphasis-aware model for SOAs with non-flat WDM inputs yielding a root-mean-square error of less than 0.05 dB is presented. It outperforms generic neural-network models while using a fraction of the training data.
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