Self-learned Entropy Loading for Channel-Adaptive Optical Communications

This paper proposes a self-learned entropy recognition scheme for optimizing entropy loading in optical communication systems, leveraging transfer learning to adapt entropy allocation across modulation formats and varying channel conditions for enhanced performance.