Conference paper Open Access

Modeling Filtering Penalties in ROADM-based Networks with Machine Learning for QoT Estimation

Mahajan, Ankush; Christodoulopoulos, Kostas; Martínez, Ricardo; Spadaro, Salvatore; Muñoz, Raül

Monitoring 3dB bandwidth and other spectrum related parameters at ROADMs provides information about quality of their filters. We propose a machine-learning model to estimate end-toend filtering penalty for more accurate QoT estimation of future connections.

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