Decision Trees-based Demodulation in Gridless Nyquist-WDM Systems to Minimize ICI Effects
Author:
Affiliation:
1. Universidad de Antioquia,Facultad de Ingeniería. GITA Lab,Medellín,Colombia
Funder
Universidad de Antioquia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10360489/10360472/10360622.pdf?arnumber=10360622
Reference7 articles.
1. DeepRMSA: A Deep Reinforcement Learning Framework for Routing, Modulation and Spectrum Assignment in Elastic Optical Networks
2. A review of advancements in DP-QPSK WDM systems
3. Optical Mitigation of Interchannel Crosstalk for Multiple Spectrally Overlapped 20-GBd QPSK/16-QAM WDM Channels Using Nonlinear Wave Mixing
4. Mitigation of time-varying distortions in Nyquist-WDM systems using machine learning
5. Training Approaches in Supervised Learning for ICI Mitigation in Gridless Nyquist-WDM
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