This book examines signal processing techniques for cognitive radios. The book is divided into three parts: Part I, is an introduction to cognitive radios and presents a history of the cognitive radio (CR), and introduce their architecture, functionalities, ideal aspects, hardware platforms, and state-of-the-art developments. Dr. Jayaweera also introduces the specific type of CR that has gained the most research attention in recent years: the CR for Dynamic Spectrum Access (DSA). Part II of the book, Theoretical Foundations, guides the reader from classical to modern theories on statistical signal processing and inference. The author addresses detection and estimation theory, power spectrum estimation, classification, adaptive algorithms (machine learning), and inference and decision processes. Applications to the signal processing, inference and learning problems encountered in cognitive radios are interspersed throughout with concrete and accessible examples. Part III of the book, Signal Processing in Radios, identifies the key signal processing, inference, and learning tasks to be performed by wideband autonomous cognitive radios. The author provides signal processing solutions to each task by relating the tasks to materials covered in Part II. Specialized chapters then discuss specific signal processing algorithms required for DSA and DSS cognitive radios.

This book provides an introduction to software-defined radio and cognitive radio, along with methodologies for applying knowledge representation, semantic web, logic reasoning and artificial intelligence to cognitive radio, enabling autonomous adaptation and flexible signaling. Readers from the wireless communications and software-defined radio communities will use this book as a reference to extend software-defined radio to cognitive radio, using the semantic technology described.

Expert authors draw on fundamental theory to explain the core principles and key design considerations for developing cognitive radio systems.

This book describes a communication paradigm that could shape the future of wireless communication networks, Opportunistic Spectrum Access (OSA) in Cognitive Radio Networks (CRN). While several theoretical OSA approaches have been proposed, they are challenged by the practical limitations of cognitive radios: the key enabling technology of OSA. This book presents an unprecedented formulation of the OSA problem in CNR that takes into account the practical limitations encountered due to existing technologies. Based on such a problem formulation, this book presents a framework and protocol details implementing the analytically-optimized solution of this problem. Unlike the state-of-the-art of CRN implementations that typically target software define radios which are not suitable for real systems, this book describes the implementation of distributed OSA, using practical radio transceiver technologies. It provides a thorough characterization of the gains available to theoretical OSA approaches if the practical limitations are taken into consideration. Tackles the cognitive radio networks performance optimization problem, taking into account the practical limitations of today’s technologies; Provides thorough performance evaluation in arbitrary, large-scale networks, as well as microscopic, small-scale performance evaluation, using realistic hardware implementation; Presents an empirical study of the gains available over existing techniques by adopting practical approaches; Tackles the cognitive radio networks performance optimization problem, taking into account the practical limitations of today’s technologies; Provides thorough performance evaluation in arbitrary, large-scale networks, as well as microscopic, small-scale performance evaluation, using realistic hardware implementation; Presents an empirical study of the gains available over existing techniques by adopting practical approaches;

A comprehensive treatment of cognitive radio networks and the specialized techniques used to improve wireless communications The human brain, as exemplified by cognitive radar, cognitive radio, and cognitive computing, inspires the field of Cognitive Dynamic Systems. In particular, cognitive radio is growing at an exponential rate. Fundamentals of Cognitive Radio details different aspects of the human brain and provides examples of how it can be mimicked by cognitive dynamic systems. The text offers a communication-theoretic background, including information on resource allocation in wireless networks and the concept of robustness. The authors provide a thorough mathematical background with data on game theory, variational inequalities, and projected dynamic systems. They then delve more deeply into resource allocation in cognitive radio networks. The text investigates the dynamics of cognitive radio networks from the perspectives of information theory, optimization, and control theory. It also provides a vision for the new world of wireless communications by integration of cellular and cognitive radio networks. This groundbreaking book: Shows how wireless communication systems increasingly use cognition to enhance their networks Explores how cognitive radio networks can be viewed as spectrum supply chain networks Derives analytic models for two complementary regimes for spectrum sharing (open-access and market-driven) to study both equilibrium and disequilibrium behaviors of networks Studies cognitive heterogeneous networks with emphasis on economic provisioning for resource sharing Introduces a framework that addresses the issue of spectrum sharing across licensed and unlicensed bands aimed for Pareto optimality Written for students of cognition, communication engineers, telecommunications professionals, and others, Fundamentals of Cognitive Radio offers a new generation of ideas and provides a fresh way of thinking about cognitive techniques in order to improve radio networks.

This book examines signal processing techniques for cognitive radios. The book is divided into three parts: Part I, is an introduction to cognitive radios and presents a history of the cognitive radio (CR), and introduce their architecture, functionalities, ideal aspects, hardware platforms, and state-of-the-art developments. Dr. Jayaweera also introduces the specific type of CR that has gained the most research attention in recent years: the CR for Dynamic Spectrum Access (DSA). Part II of the book, Theoretical Foundations, guides the reader from classical to modern theories on statistical signal processing and inference. The author addresses detection and estimation theory, power spectrum estimation, classification, adaptive algorithms (machine learning), and inference and decision processes. Applications to the signal processing, inference and learning problems encountered in cognitive radios are interspersed throughout with concrete and accessible examples. Part III of the book, Signal Processing in Radios, identifies the key signal processing, inference, and learning tasks to be performed by wideband autonomous cognitive radios. The author provides signal processing solutions to each task by relating the tasks to materials covered in Part II. Specialized chapters then discuss specific signal processing algorithms required for DSA and DSS cognitive radios.

This book focuses on the architecture and circuit design for cognitive radio receiver front-ends. The authors first provide a holistic explanation of RF circuits for cognitive radio systems. This is followed by an in-depth exploration of existing techniques that can be utilized by circuit designers. Coverage also includes novel circuit techniques and architectures that can be invaluable for designers for cognitive radio systems.