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Full 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.
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.
