Presentation Information
[TuP-A-9]Efficient Power Optimization for C+L+S Band Transmission Using Covariance Matrix Adaptation Evolution Strategy
○Miao Gong1, Min Ran1, Xiao Xiao2, Tianye Huang1, Xiang Li1, Zelin Gan3 (1China Univ. of Geosciences, 2Zhongrui Sulian (Wuhan) Science and Technology Co., Ltd, 3Univ. of Cambridge)
Keywords:
Artificial intelligence and machine learning for optical network design,control,and management
We propose using a covariance matrix adaptation evolution strategy (CMA-ES) to optimize launch power in the C+L+S band long-haul system, significantly reducing computation time while maintaining performance, and enabling faster response to channel variations.