Exploració per autor "Mahajan, Ankush"
Ara es mostren els items 1-9 de 9
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Adaptive and iterative QoT estimator retraining for launch power optimization
(Institute of Electrical and Electronics Engineers (IEEE), 2021)
Text en actes de congrés
Accés obertWe dynamically optimize the transponders launch powers with iterative closed control loops. We close the loop after an adaptable number of algorithm’s intermediate calculations, to monitor and retrain the QoT estimator ... -
Impact of multi-vendor transponders performance on design margin in optical networks
(Institute of Electrical and Electronics Engineers (IEEE), 2021-01-01)
Article
Accés obertFor reliable and efficient network planning and operation, accurate estimation of Quality of Transmission (QoT) is necessary. In optical networks, a physical layer model (PLM) is typically used as a QoT estimation tool ... -
Improving QoT estimation accuracy with DGE monitoring using machine learning
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
Text en actes de congrés
Accés restringit per política de l'editorialIn optical transport networks, Dynamic Gain Equalizers (DGE) are typically used at each link. A DGE selectively attenuates the channels to compensate the cumulative Erbium Doped Fiber Amplifier (EDFA) gain ripple effect ... -
Machine learning assisted EDFA gain ripple modelling for accurate QoT estimation
(The Institution of Engineering and Technology, 2019)
Text en actes de congrés
Accés obertWavelength dependent EDFA gain ripple has an impact on connection's OSNR performance. We propose a machine learning regression model to estimate the end to end gain ripple penalty and to increase QoT estimation accuracy. -
Machine learning assisted QoT estimation for optical networks optimization
(Universitat Politècnica de Catalunya, 2021-09-28)
Tesi
Accés obertThe tremendous increase in data traffic has spurred a rapid evolution of the optical networks for a reliable, affordable, cost effective and scalable network infrastructure. To meet some of these requirements, network ... -
Modeling EDFA gain ripple and filter penalties with machine learning for accurate QoT estimation
(Institute of Electrical and Electronics Engineers (IEEE), 2020-05-01)
Article
Accés obertFor reliable and efficient network planning and operation, accurate estimation of Quality of Transmission (QoT) before establishing or reconfiguring the connection is necessary. In optical networks, a design margin is ... -
Modeling filtering penalties in ROADM-based networks with machine learning for QoT estimation
(2020)
Text en actes de congrés
Accés obertMonitoring 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 ... -
Modelling multi-vendor transponders performance and optimizing launch power
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
Text en actes de congrés
Accés obertWe propose physical layer model extensions that capture the performance variations of multivendor transponders and use those with appropriate algorithms to optimize connections’ launch powers. We estimated potential SNR ... -
Quality of transmission estimator retraining for dynamic optimization in optical networks
(Institute of Electrical and Electronics Engineers (IEEE), 2021-04-01)
Article
Accés obertOptical network optimization involves an algorithm and a physical layer model (PLM) to estimate the quality of transmission of connections while examining candidate optimization operations. In particular, the algorithm ...
