Dan Kilper works at Trinity College Dublin.
Optical transmission networks require intelligent traffic adaptation and efficient spectrum usage. We present scalable machine learning (ML) methods for network performance modeling, andfield trials of distributed fiber sensing and classic optical network traffic coexistence.
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.
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.
Recent advances in optical fiber sensing have enabled telecom network operators to monitor their fiber infrastructure while generating new revenue in various application scenarios, including data center interconnect, public safety, smart cities, and seismic monitoring. However, given the high utilization of fiber networks for data transmission, it is undesirable to allocate dedicated fiber strands solely for sensing purposes. Therefore, it is crucial to ensure the reliable coexistence of fiber sensing and communication signals that co-propagate on the same fiber. In this paper, we conduct field trials in a reconfigurable optical add-drop multiplexer (ROADM) network enabled by the PAWR COSMOS testbed, utilizing metro area fibers in Manhattan, New York City. We verify the coexistence of real-time constant-amplitude distributed acoustic sensing (DAS), coherent 400 GbE, and analog radio-over-fiber (ARoF) signals. Measurement results obtained from the field trial demonstrate that the quality of transmission (QoT) of the coherent 400 GbE signal remains unaffected during co-propagation with DAS and ARoF signals in adjacent dense wavelength-division multiplexing (DWDM) channels. In addition, we present a use case of this coexistence system supporting preemptive DAS-informed optical path switching before link failure.
Coexistence of real-time constant-amplitude distributed acoustic sensing (DAS) and 400GbE signals is verified by field trial over metro fibers, demonstrating no QoT impact during co-propagation and supporting preemptive DAS-informed optical path switching before link failure