Artificial Intelligence-Based 6G Networking

Auteur

Radhika Ranjan Roy is an electronics engineer, US Army Research, Development, and Engineering Command (RDECOM), CommunicationsElectronics Research, Development, and Engineering Center (CERDEC), Space and Terrestrial Communications Directorate (S&TCD) Laboratories, Aberdeen Proving Ground (APG), Maryland, since 2009. Before joining to US Army Research, he worked in various capacities in CACI, SAIC, AT&T/Bell Laboratories, CSC, and PDB since his graduation. He earned his PhD in electrical engineering with major in computer communications from the City University of New York, New York, in 1984, and MS in electrical engineering from the Northeastern University, Boston, Massachusetts, in 1978. He received his BS in electrical engineering from the Bangladesh University of Engineering and Technology, Dhaka, Bangladesh, in 1967. He has published more than 50 technical papers. He is holding and/or submitted over 30 patents. He authored a book titled Handbook of Mobile Ad Hoc Networks on Mobility Models in 2010.

Texte du rabat

This book deals with the emerging 6G networking and services, which are expected to be implemented in 2030. With 6G, there will be a deep convergence of computing and communication with AI. This book provides a unified framework for the convergence of computing and communications that can be optimized as a single integrated system using AI.

Résumé

Artificial Intelligence-Based 6G Networking focuses exclusively on the upcoming sixth generation (6G) network and services slated for implementation by 2030. It explores the paradigm shift that is 6G. It discusses the deep integration of computing and communication, supported by artificial intelligence (AI) across network elements like cloud, edge, and terminals. It also examines how AI-native interfaces will permeate various network components, from radio access networks to application servers and databases.

Proposing a unified AI-enabled framework for optimizing networks and applications as a single integrated system, the book covers how network service providers can tailor network baselines, reduce noise, and accurately identify issues. The book delves into the potential of AI-driven networks to self-correct, predict, and rectify service degradations proactively, enhancing uptime and troubleshooting efficiency. It outlines the "Connection, Communication, Collaboration, Curation, and Community" framework to enhance network effects, aiding operators in automation, cost reduction, and providing optimal user experiences.

Covering topics from MIMO and massive MIMO to cybersecurity and quantum communications, the book explores cutting-edge technologies shaping the future of 6G networks. It anticipates a future where AI, along with machine learning and deep learning, enables continuous learning, self-optimization, and predictive maintenance, even with full automation, that will be the hallmark of a new era in network connectivity and innovation.

Contenu

1. Overview 2. MIMO 3. Massive MIMO 4. Ultra-Massive MIMO 5. Vehicle-to-Everything Ultra-Massive MIMO Communications 7. Cell-Free Communications 8. Non-Terrestrial Communications 9. Massive MIMO Radar 10. Massive MIMO Radar for Target Detection 11. Massive MIMO Radar Scaling 12. Ultra-Massive MIMO Radar Sensors and Multi-User Communications 13. Device-to-Device Communications with Mesh Networking 14. Vehicle-to-Vehicle and Vehicle-to-Everything Communications 15. V2V Communications Network 16. Peer-to-Peer V2V Communication 17. V2V Massive MIMO Channels 18. V2X Communications Network 19. V2X Millimeter Wave MIMO Radar Communications 20. Robotics and Autonomous System Communications 21. Virtual, Augmented, Mixed Reality and Extended Reality 22. Unmanned Aerial Vehicles Communication Systems 23. Unmanned Robot Network with Swarm Capabilities 24. Digital Twins 25. Quantum Communications 26. 6G Cybersecurity