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Beyond 5G and 6G Networks, the AI-Native Revolution explores the transformative convergence of generative artificial intelligence (GenAI), large language models (LLMs), and next-generation telecommunications. This book delves into the architectural innovations enabling AI-driven connectivity, from intelligent edge devices to adaptive radio access networks. It covers the integration of GenAI for real-time network optimization, generative modeling of wireless channels, and advanced analytics for actionable insights. Security frameworks for AI-native systems, orchestration of autonomous networks, and the fusion of AI with signal processing are thoroughly examined, offering practical solutions for researchers, engineers, and policymakers.
The book also addresses the challenges of computational constraints, ethical dilemmas, and regulatory complexities in deploying AI-driven networks. It provides a technical yet accessible roadmap for building equitable, trustworthy, and efficient systems, balancing innovation with responsibility. With insights grounded in rigorous research and real-world applications, this work is a guide for students, practitioners, and visionaries shaping the future of connectivity. It invites readers to reimagine networks as intelligent ecosystems that anticipate needs and empower humanity s highest aspirations.
Chapter 1 Introduction.- Chapter 2 Unlocking One-for-all Generative AI at Edge.- Chapter 3 Legal and Regulatory Frameworks Governing Generative AI for Enterprises.- Chapter 4 Securing GenAI and LLMs in Beyond 5G/6G UE and Networks.- Chapter 5 Designing Guardrails: Ensuring Responsible AI Behavior.- Chapter 6 GENATWIN: Enabling Scalable AI Evaluation in B5G Networks: A GenAI-Powered Digital Twin Framework.- Chapter 7 Large Generative AI Models in Telecom (GenAINet).- Chapter 8 Computational Aspects for Large Language Models (LLMs) in Radio Access Network (RAN).- Chapter 9 GenAI & LLMs for Source and Channel Coding in B5G Networks.- Chapter 10 Modeling Wireless Channels with Generative AI.- Chapter 11 Machine Learning-Based Intelligent Anomaly Detection and Maintenance in RAN.- Chapter 12 Intent-Based Networking and Conflict Resolution in B5G with LLMs and Explainable AI.- Chapter 13 A framework for Intent-Driven Kubernetes configuration generation using Large Language Models.- Chapter 14 Agent Orchestration for Resource Allocation in Self-Healing Networks.- Chapter 15 Leveraging Large Language Models (LLMs) for Service Optimization in Beyond 5G (B5G) Networks.- Chapter 16 AI-based On-Device Traffic Classification for Next Generation Mobile Network.- Chapter 17 Advanced Data Management & Analytics Using Large Language Models for B5G Networks.- Chapter 18 Conclusion.
Dr. Sukhdeep Singh is a General Manager at Samsung R&D Institute India Bangalore. Prior to this he has received his Ph.D. from SKKU South Korea. He has authored 55+ peer-reviewed publications, filed 60+ global patents and co-edited/co-authored 3 pioneering books. Dr. Singh is a recipient of numerous prestigious honors, including the IETE B. V. Baliga Memorial Award 2024, Best Research Paper Award at IEEE ICC 2024 and ICC 2025, 15 Samsung Excellence Awards, 5 Samsung Annual Author Awards, and Samsung Best Paper Award 2018 (Silver) conferred by Samsung CEO in Korea.
Dr. Madhan Raj Kanagarathinam is an Architect at Samsung R&D Institute India Bangalore. Prior to this he has received his Ph.D. from IIT Madras. He is the author of 30 articles, and more than 140 patents. He has more than 12 years of working experience in design and development of TCP/IP protocols, Multipath TCP and UNIX flavored operating systems. He is also the winner of IEEE Bangalore Young Technologist of the Year 2020. He is a senior member of the IEEE, and a member of the ACM.
Mr. Mohan Rao GNS is the Corporate Vice President and Managing Director at Samsung Research & Development Bangalore (SRI-B). Having spent 26 years with Samsung, he has spearheaded All Generations of Mobile and Network Protocol R&D spanning multiple markets and operators. With 25+ patents in Wireless domain, he has received numerous awards including the prestigious "Best Overseas R&D Employee" twice from the President of Samsung Electronics. He was recently conferred Zinnov s Best Global Leader award. He also won the Indian Achiever Award for CTO of the Year in Y2024.
Prof. Yulei Wu is an Associate Professor working across the Faculty of Science and Engineering and the Bristol Digital Futures Institute, University of Bristol, UK. He received his Ph.D. degree in Computing and Mathematics degree in Computer Science from the University of Bradford, UK, in 2010. He has published more than 10 authored/edited monograph books, and over 150 research papers in prestigious international journals and at reputable international conferences. Some of his research results were featured by the IEEE Network Scanning the Literature and the IEEE Xplore Innovation Spotlight.
Prof. Navrati Saxena is an Associate Professor at the Department of Computer Science, San Jose State
