Modeling filtering penalties in ROADM-based networks with machine learning for QoT estimation
Document typeConference report
Rights accessOpen Access
ProjectONFIRE - Future Optical Networks for Innovation, Research and Experimentation (EC-H2020-765275)
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-to-end filtering penalty for more accurate QoT estimation of future connections.
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CitationMahajan, A. [et al.]. Modeling filtering penalties in ROADM-based networks with machine learning for QoT estimation. A: Optical Fiber Communications Conference and Exposition. "2020 Optical Fiber Communications Conference and Exhibition (OFC 2020): San Diego, California, USA: 8-12 March 2020". 2020, p. 1-3.
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