GenAI and LLMs for Beyond 5G Networks
Description
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.
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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 University (SJSU), California, USA. She received her Ph.D. degree from the University of Trento, Italy. She has co-authored one book; filed two patents and published one International book chapter on 6G; more than 90 Intl. journals and many Intl. conferences, with more than 4,000 citations (Google Scholar). She also serves as a guest editor in different Intl. journals, Technical Program Committee (TPC) Chair/member in many Intl. conferences.
Dr. Ashok Kumar Reddy Chavva (Senior Member, IEEE) received the B.Tech. degree in electronics and communications engineering from Jawaharlal Nehru Technological University, Hyderabad, India, in 2003, and the M.E. and PhD degrees in Electrical Communication Engineering from the Indian Institute of Science, Bengaluru, India, in 2005 and 2025, respectively. In June 2005, he joined Beceem Communications, which later became part of Broadcom. At Broadcom, he contributed to the development of physical layer algorithms for early 4G systems based on WiMAX and LTE, and worked there until November 2013. Since then, he has been with the Samsung R&D Institute, Bangalore, India, where he currently leads a research and development team working on 6G technologies. His research interests include physical layer algorithm design, performance evaluation of wireless communication systems, 5G and 6G systems, X-MIMO, millimetre-wave systems, and the use of AI in communications. He received the Best Paper Award from IEEE CCNC in Las Vegas, USA, in 2016, the third Best Paper Award from the IEEE World 5G Forum in 2020, and four awards from the ITU AI and ML 5G Challenge in 2022, 2023, and 2025.
Prof. Ali Kashif Bashir holds the position of Professor of Computer Networks and Cybersecurity at the Manchester Metropolitan University in the United Kingdom. He received his PhD from Korea University, South Korea in 2012. Throughout his career, Ali has presented more than 45 keynote speeches at international conferences, produced over 300 research articles, and successfully overseen multimillion-dollar projects worldwide. He was listed as IEEE Featured Author in 2021, highly cited 2% researchers by Stanford University 2021 and 2022, shortlisted for Clarivate Highly Cited award 2023.
Content
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.