Modeling filtering penalties in ROADM-based networks with machine learning for QoT estimation
Document typeConference report
Rights accessOpen Access
European Commission's 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.
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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.
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder