Radio Resource Allocation and Dynamic Spectrum Access


Book Description

We are currently witnessing an increase in telecommunications norms and standards given the recent advances in this field. The increasing number of normalized standards paves the way for an increase in the range of services available for each consumer. Moreover, the majority of available radio frequencies have already been allocated. This explains the emergence of cognitive radio (CR) – the sharing of the spectrum between a primary user and a secondary user. In this book, we will present the state of the art of the different techniques for spectrum access using cooperation and competition to solve the problem of spectrum allocation and ensure better management of radio resources in a radio cognitive context. The different aspects of research explored up until now on the applications of multi-agent systems (MAS) in the field of cognitive radio are analyzed in this book. The first chapter begins with an insight into wireless networks and mobiles, with special focus on the IEEE 802.22 norm, which is a norm dedicated to CR. Chapter 2 goes into detail about CR, which is a technical field at the boundary between telecommunications and Artificial Intelligence (AI). In Chapter 3, the concept of the “agent” from AI is expanded to MAS and associated applications. Finally, Chapter 4 establishes an overview of the use of AI techniques, in particular MAS, for its allocation of radio resources and dynamic access to the spectrum in CR. Contents 1. Wireless and Mobile Networks. 2. Cognitive Radio. 3. Multi-agent Systems. 4. Dynamic Spectrum Access. About the Authors Badr Benmammar has been Associate Professor at UABT (University Abou Bekr Belkaïd Tlemcen), Algeria since 2010 and was a research fellow at CNRS LaBRI Laboratory of the University of Bordeaux 1 until 2007. He is currently carrying out research at the Laboratory of Telecommunications of Tlemcen (LTT), UABT, Algeria. His main research activities concern the cognitive radio network, Quality of Service on mobile and wireless networks, end-to-end signaling protocols and agent technology. His work on Quality of Service has led to many publications in journals and conference proceedings. Asma Amraoui is currently a PhD candidate; she is preparing a doctoral thesis on a topic of research that explores the use of artificial intelligence techniques in cognitive radio networks. She is attached to the Laboratory of Telecommunications of Tlemcen (LTT) in Algeria.




Dynamic Spectrum Access and Management in Cognitive Radio Networks


Book Description

An all-inclusive introduction to this revolutionary technology, presenting the key research issues and state-of-the-art design, analysis, and optimization techniques.




Resource Allocation in Next-Generation Broadband Wireless Access Networks


Book Description

With the growing popularity of wireless networks in recent years, the need to increase network capacity and efficiency has become more prominent in society. This has led to the development and implementation of heterogeneous networks. Resource Allocation in Next-Generation Broadband Wireless Access Networks is a comprehensive reference source for the latest scholarly research on upcoming 5G technologies for next generation mobile networks, examining the various features, solutions, and challenges associated with such advances. Highlighting relevant coverage across topics such as energy efficiency, user support, and adaptive multimedia services, this book is ideally designed for academics, professionals, graduate students, and professionals interested in novel research for wireless innovations.




Potential Game Theory


Book Description

This book offers a thorough examination of potential game theory and its applications in radio resource management for wireless communications systems and networking. The book addresses two major research goals: how to identify a given game as a potential game, and how to design the utility functions and the potential functions with certain special properties in order to formulate a potential game. After proposing a unifying mathematical framework for the identification of potential games, the text surveys existing applications of this technique within wireless communications and networking problems found in OFDMA 3G/4G/WiFi networks, as well as next-generation systems such as cognitive radios and dynamic spectrum access networks. Professionals interested in understanding the theoretical aspect of this specialized field will find Potential Game Theory a valuable resource, as will advanced-level engineering students. It paves the way for extensive and rigorous research exploration on a topic whose capacity for practical applications is vast but not yet fully exploited.




Radio Access Network Slicing and Virtualization for 5G Vertical Industries


Book Description

Learn how radio access network (RAN) slicing allows 5G networks to adapt to a wide range of environments in this masterful resource Radio Access Network Slicing and Virtualization for 5G Vertical Industriesprovides readers with a comprehensive and authoritative examination of crucial topics in the field of radio access network (RAN) slicing. Learn from renowned experts as they detail how this technology supports and applies to various industrial sectors, including manufacturing, entertainment, public safety, public transport, healthcare, financial services, automotive, and energy utilities. Radio Access Network Slicing and Virtualization for 5G Vertical Industries explains how future wireless communication systems must be built to handle high degrees of heterogeneity, including different types of applications, device classes, physical environments, mobility levels, and carrier frequencies. The authors describe how RAN slicing can be utilized to adapt 5G technologies to such wide-ranging circumstances. The book covers a wide range of topics necessary to understand RAN slicing, including: Physical waveforms design Multiple service signals coexistence RAN slicing and virtualization Applications to 5G vertical industries in a variety of environments This book is perfect for telecom engineers and industry actors who wish to identify realistic and cost-effective concepts to support specific 5G verticals. It also belongs on the bookshelves of researchers, professors, doctoral, and postgraduate students who want to identify open issues and conduct further research.




Dynamic Spectrum Management


Book Description

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.




Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks


Book Description

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.




Cognitive Radio and Dynamic Spectrum Access


Book Description

Cognitive Radio for Dynamic Spectrum Access gives a comprehensive overview of the main concepts behind radio spectrum regulation, dynamic spectrum access and cognitive radio. Spectrum measurements are introduced to illustrate the inefficiencies in today’s spectrum usage and the book also discusses enablers for horizontal and vertical spectrum sharing. Among others a game-theory-based approach for spectrum sharing is described and evaluated. Institution and standardisation approaches in academic research and industry are highlighted including IEEE SCC41, 802.11k/n/s/y and 802.22 which lead towards commercial exploitation of cognitive radio. In conclusion, this book looks at the initial steps towards the vision of true cognitive radio and the potential impact on telecommunication business. Introduces the benefits and challenges of cognitive radio Presents cognitive radio in research and industry and covers implications for operators from the perspective of a telecom operator Examines how cognitive radio techniques will considerably change the wireless communication market.




Spectrum Sharing in Cognitive Radio Networks


Book Description

SPECTRUM SHARING IN COGNITIVE RADIO NETWORKS Discover the latest advances in spectrum sharing in wireless networks from two internationally recognized experts in the field Spectrum Sharing in Cognitive Radio Networks: Towards Highly Connected Environments delivers an in-depth and insightful examination of hybrid spectrum access techniques with advanced frame structures designed for efficient spectrum utilization. The accomplished authors present the energy and spectrum efficient frameworks used in high-demand distributed architectures by relying on the self-scheduled medium access control (SMC-MAC) protocol in cognitive radio networks. The book begins with an exploration of the fundamentals of recent advances in spectrum sharing techniques before moving onto advanced frame structures with spectrum accessing approaches and the role of spectrum prediction and spectrum monitoring to eliminate interference. The authors also cover spectrum mobility, interference, and spectrum management for connected environments in substantial detail. Spectrum Sharing in Cognitive Radio Networks: Towards Highly Connected Environments offers readers a recent and rational theoretical mathematical model of spectrum sharing strategies that can be used for practical simulation of future generation wireless communication technologies. It also highlights ongoing trends, revealing fresh research outcomes that will be of interest to active researchers in the area. Readers will also benefit from: An inclusive study of connected environments, 3GPP Releases, and the evolution of wireless communication generations with a discussion of advanced frame structures and access strategies in cognitive radio networks A treatment of cognitive radio networks using spectrum prediction and monitoring techniques An analysis of the effects of imperfect spectrum monitoring on cognitive radio networks An exploration of spectrum mobility in cognitive radio networks using spectrum prediction and monitoring techniques An examination of MIMO-based CR-NOMA communication systems for spectral and interference efficient designs Perfect for senior undergraduate and graduate students in Electrical and Electronics Communication Engineering programs, Spectrum Sharing in Cognitive Radio Networks: Towards Highly Connected Environments will also earn a place in the libraries of professional engineers and researchers working in the field, whether in private industry, government, or academia.




Machine Learning for Future Wireless Communications


Book Description

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.