Reprint
Machine Learning in Communication Systems and Networks, 2nd Edition
Edited by
September 2026
306 pages
- ISBN 978-3-7258-8819-1 (Hardback)
- ISBN 978-3-7258-8820-7 (PDF)
https://doi.org/10.3390/books978-3-7258-8820-7 (registering)
Print copies available soon
This is a Reprint of the Topic Machine Learning in Communication Systems and Networks, 2nd Edition that was published in
Engineering
Summary
Recent advances in machine learning, including in relation to the availability of powerful computing platforms, have received huge attention from related academic, research, and industry communities. Machine learning is considered a promising tool to tackle the challenges related to increasingly complex, heterogeneous, and dynamic communication environments. Machine learning is able to contribute to the intelligent management and optimization of communication systems and networks by enabling them to predict changes, find patterns in uncertainties in the communication environment, and make data-driven decisions.
This Topic is focused on machine learning-based solutions aimed at managing complex issues in communication systems and networks across various layers and ranges of communication applications. The objective of the Topic is to share and discuss the recent advances in and future trends of machine learning for intelligent communication.