Handbook of AI in Wireless Networks by Imoize, Agbotiname Lucky; Musa, Abdulwaheed; Sei, Yuichi;

Short description:

This handbook bridges theory and practice for AI in wireless networks. It covers developing intelligent systems, emerging trends like spectrum management, traffic scheduling, energy efficiency, and security. Written for researchers, professionals, and students in wireless communications and AI.

Long description:

This handbook bridges the gap between theory and practical applications, providing foundational knowledge and actionable insights into the use of AI in future wireless networks. The book is a comprehensive guide to developing, deploying, and managing intelligent wireless systems, contributing to the global push toward a hyper-connected world.

Handbook of AI in Wireless Networks: Foundations, Techniques, and Emerging Applications explores the intersection of artificial intelligence (AI) and wireless communication systems, providing a comprehensive guide to how AI transforms the design, management, and optimisation of wireless networks.  Additionally, the book discusses emerging trends in AI-aided wireless communication systems, including integrated sensing and communications, intelligent spectrum management for dynamic allocation, traffic scheduling for optimal resource allocation, energy efficiency, security and privacy, and ethical considerations. The book offers innovative approaches to solving real-world wireless network challenges related to spectrum management, network optimisation, traffic management, security, and privacy, leveraging cutting-edge AI algorithms.

The book is written for a diverse audience, including researchers, academics, industry professionals, and policymakers in wireless communications, artificial intelligence, and network systems. It is particularly relevant to engineers and practitioners involved in designing, developing, and deploying next-generation wireless networks, as well as to graduate and postgraduate students specializing in AI, telecommunications, and computer networks.

Table of Contents:

Chapter 1 Artificial Intelligence-empowered 6G Wireless Networks: Architectures, Techniques, and Future Directions Chapter 2 Deep Reinforcement Learning for Wireless Networks: Architectures, Algorithms, and Emerging Applications Chapter 3 AI for Spectrum Management in Emerging Wireless Networks Chapter 4 Advanced Machine Learning Algorithms for Emerging Wireless Networks Chapter 5 Exploring the Foundations of Artificial Intelligence in Emerging Wireless Networks Chapter 6 Application of Artificial Intelligence in 6G Wireless Networks and Beyond Chapter 7 AI for Advanced Wireless Security and Privacy Systems Chapter 8 AI for Intelligent IoT Networks and Emerging Computing Devices Chapter 9 Application of AI in 6G Optical Wireless Networks: Development, Opportunities, and Challenges Chapter 10 Intelligent Sensor Network for UAV Monitoring and Control with a Secure Communication Protocol Chapter 11 Artificial Intelligence-based Fault Detection and Self-Healing in Wireless Communication Systems Chapter 12 Quantum Machine Learning-based Adaptive Modulation for Optimizing Wireless Communication Systems Chapter 13 AI-Driven Ultra Massive MIMO Systems and Techniques for 6G and Beyond Chapter 14 Pose2Sound: Generating Instrument Audio from Video via Human Motion Cues Chapter 15 Edge AI for IoT Systems: Architectures and Applications Chapter 16 Examining AI-empowered 5G Wireless Network Optimisation Chapter 17 Ethical Considerations for AI-driven Wireless Networks Chapter 18 AI in Advanced Vehicular Networks: Design Principles and Applications Chapter 19 The Ethics of AI-assisted Wireless Networks: New Frontiers of the New World Chapter 20 AI-enabled Joint Wireless Network Sensing and Communication in 6G Chapter 21 Current Trends and Challenges in the Application of Artificial Intelligence for Network Attack Detection