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GenAI and LLMs for Beyond 5G Networks / edited by Sukhdeep Singh, Madhan Raj Kanagarathinam, Mohan Rao GNS, Yulei Wu, Navrati Saxena, Ashok Kumar Reddy Chavva, Ali Kashif Bashir.

Springer Nature - Springer Computer Science eBooks 2026 English International Available online

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Format:
Book
Author/Creator:
Singh, Sukhdeep.
Contributor:
Singh, Sukhdeep., Editor.
Kanagarathinam, Madhan Raj., Editor.
Rao GNS, Mohan., Editor.
Wu, Yulei., Editor.
Saxena, Navrati., Editor.
Chavva, Ashok Kumar Reddy., Editor.
Bashir, Ali Kashif., Editor.
Series:
Computer Science Series
Language:
English
Subjects (All):
Mobile computing.
Artificial intelligence.
Computer networks.
Mobile Computing.
Artificial Intelligence.
Computer Communication Networks.
Local Subjects:
Mobile Computing.
Artificial Intelligence.
Computer Communication Networks.
Physical Description:
1 online resource (VIII, 378 p. 33 illus., 1 illus. in color.)
Edition:
1st ed. 2026.
Place of Publication:
Cham : Springer Nature Switzerland : Imprint: Springer, 2026.
Summary:
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.
Contents:
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.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
3-032-06418-X

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