Artificial Intelligent Techniques for Wireless Communication and Networking

  • 5h 30m
  • K. Ananthajothi, R. Kanthavel, R. Karthik Ganesh, S. Balamurugan
  • John Wiley & Sons (US)
  • 2022

ARTIFICIAL INTELLIGENT TECHNIQUES FOR WIRELESS COMMUNICATION AND NETWORKING

The 20 chapters address AI principles and techniques used in wireless communication and networking and outline their benefit, function, and future role in the field.

Wireless communication and networking based on AI concepts and techniques are explored in this book, specifically focusing on the current research in the field by highlighting empirical results along with theoretical concepts. The possibility of applying AI mechanisms towards security aspects in the communication domain is elaborated; also explored is the application side of integrated technologies that enhance AI-based innovations, insights, intelligent predictions, cost optimization, inventory management, identification processes, classification mechanisms, cooperative spectrum sensing techniques, ad-hoc network architecture, and protocol and simulation-based environments.

Audience

Researchers, industry IT engineers, and graduate students working on and implementing AI-based wireless sensor networks, 5G, IoT, deep learning, reinforcement learning, and robotics in WSN, and related technologies.

About the Author

R. Kanthavel, PhD is a Professor in the Department of Computer Engineering, King Khalid University Abha, Kingdom of Saudi Arabia. He has published more than 150 research articles in reputed journals and international conferences as well as published 10 engineering books. He specializes in communication systems engineering and information and communication engineering.

K. Ananthajothi, PhD is an assistant professor in the Department of Computer Science and Engineering at Misrimal Navajee Munoth Jain Engineering College, Chennai, India. He has published a book on "Theory of Computation and Python Programming" and holds 2 patents.

S. Balamurugan, PhD is the Director of Research and Development, Intelligent Research Consultancy Services (iRCS), Coimbatore, Tamilnadu, India. He is also Director of the Albert Einstein Engineering and Research Labs (AEER Labs), as well as Vice-Chairman, Renewable Energy Society of India (RESI), India. He has published 45 books, 200+ international journals/ conferences, and 35 patents.

R. Karthik Ganesh, PhD is an associate professor in the Department of Computer Science and Engineering, SCAD College of Engineering and Technology, Cheranmahadevi, Tamilnadu, India. His research interests are in wireless communication, video and audio compression, image classification, and ontology techniques.

In this Book

  • Preface
  • Comprehensive and Self-Contained Introduction to Deep Reinforcement Learning
  • Impact of AI in 5G Wireless Technologies and Communication Systems
  • Artificial Intelligence Revolution in Logistics and Supply Chain Management
  • An Empirical Study of Crop Yield Prediction Using Reinforcement Learning
  • Cost Optimization for Inventory Management in Blockchain and Cloud
  • Review of Deep Learning Architectures Used for Identification and Classification of Plant Leaf Diseases
  • Generating Art and Music Using Deep Neural Networks
  • Deep Learning Era for Future 6G Wireless Communications—Theory, Applications, and Challenges
  • Robust Cooperative Spectrum Sensing Techniques for a Practical Framework Employing Cognitive Radios in 5G Networks
  • Natural Language Processing
  • Class Level Multi-Feature Semantic Similarity-Based Efficient Multimedia Big Data Retrieval
  • Supervised Learning Approaches for Underwater Scalar Sensory Data Modeling With Diurnal Changes
  • Multi-Layer UAV Ad Hoc Network Architecture, Protocol and Simulation
  • Artificial Intelligence in Logistics and Supply Chain
  • Hereditary Factor-Based Multi-Featured Algorithm for Early Diabetes Detection Using Machine Learning
  • Adaptive and Intelligent Opportunistic Routing Using Enhanced Feedback Mechanism
  • Enabling Artificial Intelligence and Cyber Security in Smart Manufacturing
  • Deep Learning in 5G Networks
  • EIDR Umpiring Security Models for Wireless Sensor Networks
  • Artificial Intelligence in Wireless Communication
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