Cognitive Raman Amplifier Control Using an Evolutionary Optimization Strategy

In this work, a cognitive Raman amplifier controller using an evolutionary optimization strategy for both in-field device calibration and optimal pump power configuration design is presented. The conceived methodology allows to jointly characterize the physical layer properties of the optical fiber span, such as the fiber attenuation profile, the entities of the lumped losses due to mechanical connectors or splices, the polarization coefficients between each Raman pump pair and the Raman efficiency curve. The developed framework expects to work using optical channel monitors (OCMs) as telemetry device and it has been experimentally validated, obtaining outstanding results in terms of precision on a C-band setup.

Automated summary

This work proposes a cognitive Raman amplifier controller that uses an evolutionary optimization strategy to simultaneously calibrate in-field devices and design optimal pump power configurations. The methodology allows for the joint characterization of physical layer properties of the optical fiber span, such as fiber attenuation profile, losses due to mechanical connectors or splices, polarization coefficients between Raman pump pairs, and Raman efficiency curve. The framework has been experimentally validated using optical channel monitors (OCMs) as telemetry devices, and has achieved outstanding precision results in a C-band setup.