Deep Learning in Wireless Communications
Book information
Description
The book offers a focused examination of deep learning-based wireless communication systems and their applications. While both principles and engineering practice are explored, greater emphasis is placed on the latter. The book offers an in-depth exploration of major topics such as cognitive spectrum intelligence, learning resource allocation optimization, transmission intelligence, learning traffic and mobility prediction, and security in wireless communication. Notably, the book provides a comprehensive and systematic treatment of practical issues related to intelligent wireless communication, making it particularly useful for those seeking to learn about practical solutions in AI-based wireless resource management. This book is a valuable resource for researchers, engineers, and graduate students in the fields of wireless communication, telecommunications, and related areas.
Similar books
Network Slicing for Future Wireless Communication: Theory and Application (Wireless Networks)
2024 · PDF
Neural Computing for Advanced Applications: Third International Conference, NCAA 2022, Jinan, China, July 8–10, 2022, Proceedings, Part II
2022 · PDF
5G NR and Enhancements: From R15 to R16
2021 · PDF
Neural Computing for Advanced Applications: First International Conference, NCAA 2020, Shenzhen, China, July 3–5, 2020, Proceedings
2020 · PDF
4G Femtocells: Resource Allocation and Interference Management
2013 · PDF
5G for Future Wireless Networks: Second EAI International Conference, 5GWN 2019, Changsha, China, February 23-24, 2019, Proceedings
2019 · PDF
Game Theory for Networks: 6th International Conference, GameNets 2016, Kelowna, BC, Canada, May 11-12, 2016, Revised Selected Papers
2017 · PDF
4G Femtocells: Resource Allocation and Interference Management
2013 · PDF