EDFA Models describe the behavior of Erbium-Doped Fiber Amplifiers, essential devices in long-distance optical communication that boost signal strength while minimizing noise. Accurate EDFA modeling enables network designers to predict system performance and optimize design for scalability. NECLA’s optical networking researchers use EDFA models to test high-bandwidth communication strategies and to advance fiber systems that support next-generation AI workloads and sensing applications requiring reliability over large geographic areas.

Posts

Multi-span OSNR and GSNR Prediction using Cascaded Learning

We implement a cascaded learning framework leveraging three different EDFA and fiber component models for OSNR and GSNR prediction, achieving MAEs of 0.20 and 0.14 dBover a 5-span network under dynamic channel loading.

Scalable Machine Learning Models for Optical Transmission System Management

Optical transmission systems require accurate modeling and performance estimation for autonomous adaption and reconfiguration. We present efficient and scalable machine learning (ML) methods for modeling optical networks at component- and network-level with minimizeddata collection.