Machine Learning for Fiber-Optic Communication Systems

Machine Learning for Future Fiber-Optic Communication Systems provides a comprehensive and in-depth overview of the latest machine learning (ML) techniques and their applications in future fiber-optic communication systems.This book covers a wide range of topics, including ML-based modulation and coding, ML-based channel estimation and equalization, ML-based resource allocation and scheduling, and ML-based security and privacy.It also presents a detailed overview of the challenges and opportunities of using ML in fiber-optic communication systems, and provides a comprehensive survey of the state-of-the-art ML techniques for fiber-optic communication systems.This book is an essential resource for researchers, engineers, and graduate students in the field of fiber-optic communication systems, as well as for anyone interested in the latest advances in ML.It is also a valuable reference for professionals in the telecommunications industry who want to learn more about the potential of ML in future fiber-optic communication systems.