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.

This reference text discusses advances in wireless communication, design challenges, and future research directions to design reliable wireless communication. The text discusses emerging technologies including wireless sensor networks, Internet of Things (IoT), cloud computing, mm-Wave, Massive MIMO, cognitive radios (CR), visible light communication (VLC), wireless optical communication, signal processing, and channel modeling. The text covers artificial intelligence-based applications in wireless communication, machine learning techniques and challenges in wireless sensor networks, and deep learning for channel and bandwidth estimation during optical wireless communication. The text will be useful for senior undergraduate, graduate students, and professionals in the fields of electrical engineering, and electronics and communication engineering.

This cutting-edge resource offers practical overview of cognitive radio, a paradigm for wireless communications in which a network or a wireless node changes its transmission or reception parameters. The alteration of parameters is based on the active monitoring of several factors in the external and internal radio environment. This book offers a detailed description of cognitive radio and its individual parts. Practitioners learn how the basic processing elements and their capabilities are implemented as modular components. Moreover, the book explains how each component can be developed and tested independently, before integration with the rest of the engine. Practitioners discover how cognitive radio uses artificial intelligence to achieve radio optimization. The book also provides an in-depth working example of the developed cognitive engine and an experimental scenario to help engineers understand its performance and behavior.

This book offers the latest advances and results in the fields of Machine Learning and Deep Learning for Wireless Communication and provides positive and critical discussions on the challenges and prospects. It provides a broad spectrum in understanding the improvements in Machine Learning and Deep Learning that are motivating by the specific constraints posed by wireless networking systems. The book offers an extensive overview on intelligent Wireless Communication systems and its underlying technologies, research challenges, solutions, and case studies. It provides information on intelligent wireless communication systems and its models, algorithms and applications. The book is written as a reference that offers the latest technologies and research results to various industry problems.

Aimed at researchers, engineers and scientists involved in the design and development of protocols and AI applications for wireless communication devices and networks, this edited book presents recent research and innovations in emerging AI methods and AI-powered mechanisms, and future perspectives in this field.

Covers details on wireless communication problems, conducive for data-driven solutions Provides a comprehensive account of programming languages, tools, techniques, and good practices Provides an introduction to data-driven techniques applied to wireless communication systems Examines data-driven techniques, performance, and design issues in wireless networks Includes several case studies that examine data-driven solution for QoS in heterogeneous wireless networks

The application of artificial intelligence technology to 5G wireless communications is now appropriate to address the design of optimized physical layers, complicated decision-making, network management, and resource optimization tasks within networks. In exploring 5G wireless technologies and communication systems, artificial intelligence is a powerful tool and a research topic with numerous potential fields of application that require further study. Applications of Artificial Intelligence in Wireless Communication Systems explores the applications of artificial intelligence for the optimization of wireless communication systems, including channel models, channel state estimation, beamforming, codebook design, signal processing, and more. Covering key topics such as neural networks, deep learning, and wireless systems, this reference work is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.