This title begins by presenting the theoretical framework governing the technology, and economics of spectrum. Examples derived from practices around the world are given to illustrate the underlying principles. Future technologies that enable effective use of spectrum are documented along with the accompanying economic rationale and policy prescriptions. The significant addition in this book is the illustration of the migration from the command and control regime of spectrum allocation to flexible methods and further towards the spectrum of the commons.

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.

The book describes how interference can be managed so that radio systems co-exist, without harmful mutual effects, within a finite amount of spectrum. This is timely in view of the increasing proliferation of wireless systems. It covers both the processes, such as regional or international coordination, as well as the engineering principles. Written by an author with extensive experience in the industry, it describes in detail the main methodologies for calculating or computing the interference between radio systems of the same type, and also between radio systems of different types

In 2003, the Department of Commerce's Spectrum Policy Initiative was established with the objective of promoting a more efficient and beneficial use of the spectrum. As part of that Initiative, a series of public forums about spectrum management policy was held. The Computer Science and Telecommunications Board was asked to organize one of these forums, a public forum to gather the views of a variety of government and private sector stakeholders about the impact of spectrum policy on their activities. This report presents a summary of those views. Among those included are those representing national defense, homeland security, aviation, science, public safety, amateur radio, cellular voice and data, and terrestrial broadcast uses of the spectrum. Although prepared by the NRC, the report does not present NRC findings or recommendations. A broader study of spectrum policy, including findings and recommendations, will be issued in early 2005.

This title begins by presenting the theoretical framework governing the technology, and economics of spectrum. Examples derived from practices around the world are given to illustrate the underlying principles. Future technologies that enable effective use of spectrum are documented along with the accompanying economic rationale and policy prescriptions. The significant addition in this book is the illustration of the migration from the command and control regime of spectrum allocation to flexible methods and further towards the spectrum of the commons.

A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.

Cognitive Radio Communications and Networks gives comprehensive and balanced coverage of the principles of cognitive radio communications, cognitive networks, and details of their implementation, including the latest developments in the standards and spectrum policy. Case studies, end-of-chapter questions, and descriptions of various platforms and test beds, together with sample code, give hands-on knowledge of how cognitive radio systems can be implemented in practice. Extensive treatment is given to several standards, including IEEE 802.22 for TV White Spaces and IEEE SCC41 Written by leading people in the field, both at universities and major industrial research laboratories, this tutorial text gives communications engineers, R&D engineers, researchers, undergraduate and post graduate students a complete reference on the application of wireless communications and network theory for the design and implementation of cognitive radio systems and networks - Each chapter is written by internationally renowned experts, giving complete and balanced treatment of the fundamentals of both cognitive radio communications and cognitive networks, together with implementation details - Extensive treatment of the latest standards and spectrum policy developments enables the development of compliant cognitive systems - Strong practical orientation – through case studies and descriptions of cognitive radio platforms and testbeds – shows how real world cognitive radio systems and network architectures have been built Alexander M. Wyglinski is an Assistant Professor of Electrical and Computer Engineering at Worcester Polytechnic Institute (WPI), Director of the WPI Limerick Project Center, and Director of the Wireless Innovation Laboratory (WI Lab) - Each chapter is written by internationally renowned experts, giving complete and balanced treatment of the fundamentals of both cognitive radio communications and cognitive networks, together with implementation details - Extensive treatment of the latest standards and spectrum policy developments enables the development of compliant cognitive systems - Strong practical orientation – through case studies and descriptions of cognitive radio platforms and testbeds – shows how "real world" cognitive radio systems and network architectures have been built