This Springer Brief focuses on the current state-of-the-art research on spectrum sensing by using energy detection, a low-complexity and low-cost technique. It includes a comprehensive summary of recent research, fundamental theories, possible architectures, useful performance measurements of energy detection and applications of energy detection. Concise, practical chapters explore conventional energy detectors, alternative forms of energy detectors, performance measurements, diversity techniques and cooperative networks. The careful analysis enables reader to identify the most efficient techniques for improving energy detection performance. Energy Detection for Spectrum Sensing in Cognitive Radio is a valuable tool for researchers and practitioners interested in spectrum sensing and cognitive radio networks. Advanced-level students studying wireless communication will also benefit from this brief.

Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.

This comprehensive reference text discusses concepts of cognitive radio and the advances in the field of spectrum sensing. This text discusses the concept of cognitive radio for next generation wireless communication and a very critical aspect of cognitive radio – that is, spectrum sensing – in detail. It covers important topics including narrowband spectrum sensing, wideband spectrum sensing, cooperative spectrum sensing, system and channel models, detection algorithms, approximation of decision statistics, and theoretical analysis of detection algorithms in detail. Separate chapters are dedicated to discussing the analysis and use of detection algorithms for narrowband spectrum sensing, wideband spectrum sensing, and cooperative wideband spectrum sensing. Aimed at graduate students and academic researchers in the fields of electrical engineering and electronics and communication engineering, this text: Discusses concepts of cognitive radio and research in spectrum sensing. Presents mathematical analysis of algorithms considering practical environment. Explains novel wideband spectrum sensing algorithms with detailed analysis. Provides mathematical derivations to help readers. Discusses basic spectrum sensing algorithms, from narrowband spectrum sensing to the more advanced wideband spectrum sensing.

This open access book, authored by a world-leading researcher in this field, describes fundamentals of dynamic spectrum management, provides a systematic overview on the enabling technologies covering cognitive radio, blockchain, and artificial intelligence, and offers valuable guidance for designing advanced wireless communications systems. This book is intended for a broad range of readers, including students and professionals in this field, as well as radio spectrum policy makers.

Fueled by ongoing and increasing consumer demand, the explosive growth in spectrum-based communications continues to tax the finite resources of the available spectrum. One possible solution, Cognitive Radio Network (CRN), allows unlicensed users opportunistic access to licensed bands without interfering with existing users. Although some initial s

The first book to provide a detailed discussion of the application of wavelets in wireless communications, this is an invaluable source of information for graduate students, researchers, and telecommunications engineers, managers and strategists. It overviews applications, explains how to design new wavelets and compares wavelet technology with existing OFDM technology. • Addresses the applications and challenges of wavelet technology for a range of wireless communication domains • Aids in the understanding of Wavelet Packet Modulation and compares it with OFDM • Includes tutorials on convex optimisation, spectral factorisation and the design of wavelets • Explains design methods for new wavelet technologies for wireless communications, addressing many challenges, such as peak-to-average power ratio reduction, interference mitigation, reduction of sensitivity to time, frequency and phase offsets, and efficient usage of wireless resources • Describes the application of wavelet radio in spectrum sensing of cognitive radio systems.