[TuP-A] Poster Session 1

[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 (1. China University of Geosciences, Wuhan (China), 2. Zhongrui Sulian (Wuhan) Science and Technology Co., Ltd, Wuhan, China (China), 3. University of Cambridge, Cambridge, UK (UK))

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.