Estimating Quality of Transmission in a Live Production Network using Machine Learning
Reviewed by Pithpith:RP2HDSU5open to challenge →
classification
cs.NI
keywords
livenetworkconfigurationdatademonstrateerrorestimatingestimation
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We demonstrate QoT estimation in a live network utilizing neural networks trained on synthetic data spanning a large parameter space. The ML-model predicts the measured lightpath performance with <0.5dB SNR error over a wide configuration range.
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