Now showing items 1-6 of 6

    • Improving QoT estimation accuracy with DGE monitoring using machine learning 

      Mahajan, Ankush; Christodoulopoulos, Kostantinos; Martinez, Ricardo; Spadaro, Salvatore; Muñoz, Raul (Institute of Electrical and Electronics Engineers (IEEE), 2020)
      Conference report
      Restricted access - publisher's policy
      In 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 

      Mahajan, Ankush; Christodoulopoulos, Konstantinos; Martínez Rivera, Ricardo Victor; Spadaro, Salvatore; Muñoz González, Raül (The Institution of Engineering and Technology, 2019)
      Conference report
      Open Access
      Wavelength 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.
    • Modeling EDFA gain ripple and filter penalties with machine learning for accurate QoT estimation 

      Mahajan, Ankush; Christodoulopoulos, Konstantinos; Martínez, Ricardo; Spadaro, Salvatore; Muñoz, Raul (Institute of Electrical and Electronics Engineers (IEEE), 2020-05-01)
      Article
      Open Access
      For 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 

      Mahajan, Ankush; Christodoulopoulos, Kostas; Martinez, Ricardo; Spadaro, Salvatore; Muñoz, Raul (2020)
      Conference report
      Open Access
      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 ...
    • Modelling multi-vendor transponders performance and optimizing launch power 

      Mahajan, Ankush; Christodoulopoulos, Konstantinos; Martínez Rivera, Ricardo Victor; Spadaro, Salvatore; Muñoz González, Raül (Institute of Electrical and Electronics Engineers (IEEE), 2020)
      Conference report
      Open Access
      We 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 

      Mahajan, Ankush; Christodoulopoulos, Konstantinos; Martínez Rivera, Ricardo Victor; Muñoz González, Raül; Spadaro, Salvatore (Institute of Electrical and Electronics Engineers (IEEE), 2021-04-01)
      Article
      Restricted access - publisher's policy
      Optical 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 ...