Multi-Span Optical Power Spectrum Evolution Modeling using ML-based Multi-Decoder Attention Framework
Agastya Raj, Zehao Wang, Frank Slyne, Tingjun Chen, Dan Kilper, Marco Ruffini
TL;DR
A ML-based attention framework with component-specific decoders, improving optical power spectrum prediction in multi-span networks by reducing the need for in-depth training on each component, making it suitable for brown-field scenarios.
Abstract
We implement a ML-based attention framework with component-specific decoders, improving optical power spectrum prediction in multi-span networks. By reducing the need for in-depth training on each component, the framework can be scaled to multi-span topologies with minimal data collection, making it suitable for brown-field scenarios.