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AI-Enabled 6G Networks and Applications

   Author: Baturi   |   22 December 2022   |   Comments icon: 0

AI-Enabled 6G Networks and Applications
AI-Enabled 6G Networks and Applications
by Gupta, Deepak;Ragab, Mahmoud;Mansour, Romany Fouad;Khamparia, Aditya;Khanna, Ashish;

English | 2022 | ISBN: 111981264X | 179 pages | True PDF | 10.48 MB


AI-ENABLED 6G NETWORKS AND APPLICATIONSProvides authoritative guidance on utilizing AI techniques in 6G network design and optimization
Written and edited by active researchers, this book covers hypotheses and practical considerations and provides insights into the design of evolutionary AI algorithms for 6G networks, with focus on network transparency, interpretability and simulatability for vehicular networks, space systems, surveillance systems and their usages in different emerging engineering fields.
AI-Enabled 6G Networks and Applicationsincludes a review of AI techniques for 6G Networks and will focus on deployment of AI techniques to efficiently and effectively optimize the network performance, including AI-empowered mobile edge computing, intelligent mobility and handover management, and smart spectrum management. This book includes the design of a set of evolutionary AI hybrid algorithms with communication protocols, showing how to use them in practice to solve problems relating to vehicular networks, aerial networks, and communication networks.
Reviews various types of AI techniques such as AI-empowered mobile edge computing, intelligent handover management, and smart spectrum management Describes how AI techniques manage computation efficiency, algorithm robustness, hardware development, and energy management Identifies and provides solutions to problems in current 4G/5G networks and emergent 6G architectures Discusses privacy and security issues in IoT-enabled 6G Networks Examines the use of machine learning to achieve closed-loop optimization and intelligent wireless communication
AI-Enabled 6G Networks and Applicationsis an essential reference guide to advanced hybrid computational intelligence methods for 6G supportive networks and protocols, suitable for graduate students and researchers in network forensics and optimization, computer science, and engineering.



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