Optical Network
Optical networks are communication systems using light to transmit data, aiming for high-speed, long-distance, and reliable data transfer. Current research heavily emphasizes using machine learning, particularly convolutional neural networks (CNNs), recurrent neural networks (RNNs, including LSTMs), and transformers, to improve network performance, optimize resource allocation, and enhance fault detection and management. These advancements are crucial for addressing the increasing demands of high-bandwidth applications like 5G and beyond, improving network efficiency, and reducing operational costs through predictive maintenance and automated control.
Papers
Convolutional Neural Networks for Reflective Event Detection and Characterization in Fiber Optical Links Given Noisy OTDR Signals
Khouloud Abdelli, Helmut Griesser, Stephan Pachnicke
Machine Learning-based Anomaly Detection in Optical Fiber Monitoring
Khouloud Abdelli, Joo Yeon Cho, Florian Azendorf, Helmut Griesser, Carsten Tropschug, Stephan Pachnicke
Reflective Fiber Faults Detection and Characterization Using Long-Short-Term Memory
Khouloud Abdelli, Helmut Griesser, Peter Ehrle, Carsten Tropschug, Stephan Pachnicke