Radio over Fiber (RoF) technology has been realized in different forms ranging from analog
to more complex forms [1-6]. The enhancement of capacity and wireless coverage has …

Today's telecommunication networks have become sources of enormous amounts of widely
heterogeneous data. This information can be retrieved from network traffic traces, network …

Abstract Machine learning (ML) has revolutionized a number of science and engineering
disciplines over the past few years. It is also being considered as a new direction of …

Abstract Machine learning (ML) is being hailed as a new direction of innovation to transform
future optical communication systems. Signal processing paradigms based on ML are being …

Machine learning (ML) has disrupted a wide range of science and engineering disciplines in
recent years. ML applications in optical communications and networking are also gaining …

Global demand for internet traffic is growing at a rapid rate, driven by the adoption of new
technologies and increased demand from consumers. This continued growth is exerting …

Machine Learning for Future Fiber-Optic Communication Systems provides a
comprehensive and in-depth treatment of machine learning concepts and techniques …

Virtually all technologies have experienced a digital transformation as a result of technical
advances in our daily lives and their convergence improvements in the communication …

It's feasible that today's telecommunications networks may benefit greatly from the use of
machine learning (ML) methods to contemporary optical communication systems. Since our …

Optical communication systems are expected to find use in new applications that require
more intelligent and automated functionality. Optical networks are needed to address the …