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Providing an extensive overview of the radio resource management problem in femtocell networks, this invaluable book considers both code division multiple access femtocells and orthogonal frequency-division multiple access femtocells. In addition to incorporating current research on this topic, the book also covers technical challenges in femtocell deployment, provides readers with a variety of approaches to resource allocation and a comparison of their effectiveness, explains how to model various networks using Stochastic geometry and shot noise theory, and much more.
Following the pattern of the Internet growth in popularity, started in the early 1990s, the current unprecedented expansion of wireless technology promises to have an even greater effect on how people communicate and interact, with considerable socio-economic impact all over the world. The driving force behind this growth is the remarkable progress in component miniaturization, integration, and also devel- ments in waveforms, coding, and communication protocols. Besides established infrastructurebased wireless networks (cellular, WLAN, sat- lite) ad-hoc wireless networks emerge as a new platform for distributed applications and for personal communication in scenarios where deploying infrastructure is not feasible. In ad-hoc wireless networks, each node is capable of forwarding packets on behalf of other nodes, so that multi-hop paths provide end-to-end connectivity. The increased flexibility and mobility of ad-hoc wireless networks are favored for appli- tions in law enforcement, homeland defense and military. In a world where wireless networks become increasingly interoperable with each other and with the high-speed wired Internet, personal communication systems will transform into universal terminals with instant access to variate content and able of handle demanding tasks, such as multimedia and real-time video. With users roaming between networks, and with wide variation in wireless link quality even in a single domain, the communications terminal must continue to provide a level of Quality of Service that is acceptable to the user and conforms to a contracted Service Level Agreement.
Do you need to design efficient wireless communications systems? This unique text provides detailed coverage of radio resource allocation problems in wireless networks and the techniques that can be used to solve them. Covering basic principles and mathematical algorithms, and with a particular focus on power control and channel allocation, you will learn how to model, analyze, and optimize the allocation of resources in both physical and data link layers, and for a range of different network types. Both established and emerging networks are considered, including CDMA and OFDMA wireless networks, relay-based wireless networks, and cognitive radio networks. Numerous exercises help you put knowledge into practice, and provide the tools needed to address some of the current research problems in the field. This is an essential reference whether you are a graduate student, researcher or industry professional working in the field of wireless communication networks.
Deep Reinforcement Learning for Wireless Communications and Networking Comprehensive guide to Deep Reinforcement Learning (DRL) as applied to wireless communication systems Deep Reinforcement Learning for Wireless Communications and Networking presents an overview of the development of DRL while providing fundamental knowledge about theories, formulation, design, learning models, algorithms and implementation of DRL together with a particular case study to practice. The book also covers diverse applications of DRL to address various problems in wireless networks, such as caching, offloading, resource sharing, and security. The authors discuss open issues by introducing some advanced DRL approaches to address emerging issues in wireless communications and networking. Covering new advanced models of DRL, e.g., deep dueling architecture and generative adversarial networks, as well as emerging problems considered in wireless networks, e.g., ambient backscatter communication, intelligent reflecting surfaces and edge intelligence, this is the first comprehensive book studying applications of DRL for wireless networks that presents the state-of-the-art research in architecture, protocol, and application design. Deep Reinforcement Learning for Wireless Communications and Networking covers specific topics such as: Deep reinforcement learning models, covering deep learning, deep reinforcement learning, and models of deep reinforcement learning Physical layer applications covering signal detection, decoding, and beamforming, power and rate control, and physical-layer security Medium access control (MAC) layer applications, covering resource allocation, channel access, and user/cell association Network layer applications, covering traffic routing, network classification, and network slicing With comprehensive coverage of an exciting and noteworthy new technology, Deep Reinforcement Learning for Wireless Communications and Networking is an essential learning resource for researchers and communications engineers, along with developers and entrepreneurs in autonomous systems, who wish to harness this technology in practical applications.
Metaverse Communication and Computing Networks Understand the future of the Internet with this wide-ranging analysis “Metaverse” is the term for applications that allow users to assume digital avatars to interact with other humans and software functions in a three-dimensional virtual space. These applications and the spaces they create constitute an exciting and challenging new frontier in digital communication. Surmounting the technological and conceptual barriers to creating the Metaverse will require researchers and engineers familiar with its underlying theories and a wide range of technologies and techniques. Metaverse Communication and Computing Networks provides a comprehensive treatment of Metaverse theory and the technologies that can be brought to bear on this new pursuit. It begins by describing the Metaverse’s underlying architecture and infrastructure, physical and digital, before addressing how existing technologies are being adapted to its use. It concludes with an overview of the challenges facing the Metaverse. The result is a thorough introduction to a subject that may define the future of the internet. Metaverse Communication and Computing Networks readers will also find: Detailed treatment of technologies, including artificial intelligence, Virtual Reality, Extended Reality, and more Analysis of issues including data security, ethics, privacy, and social impact A real-world prototype for Metaverse applications Metaverse Communication and Computing Networks is a must-own for researchers and engineers looking to understand this growing area of technology, and entrepreneurs interested in establishing Metaverse businesses.
This book allows readers to gain an in-depth understanding of resource allocation problems in wireless networks and the techniques used to solve them.
Artificial Intelligence for Autonomous Networks introduces the autonomous network by juxtaposing two unique technologies and communities: Networking and AI. The book reviews the technologies behind AI and software-defined network/network function virtualization, highlighting the exciting opportunities to integrate those two worlds. Outlining the new frontiers for autonomous networks, this book highlights their impact and benefits to consumers and enterprise customers. It also explores the potential of the autonomous network for transforming network operation, cyber security, enterprise services, 5G and IoT, infrastructure monitoring and traffic optimization, and finally, customer experience and care. With contributions from leading experts, this book will provide an invaluable resource for network engineers, software engineers, artificial intelligence, and machine learning researchers.
This book brings together a group of visionaries and technical experts from academia to industry to discuss the applications and technologies that will comprise the next set of cellular advancements (5G). In particular, the authors explore usages for future 5G communications, key metrics for these usages with their target requirements, and network architectures and enabling technologies to meet 5G requirements. The objective is to provide a comprehensive guide on the emerging trends in mobile applications, and the challenges of supporting such applications with 4G technologies.
COMMUNICATION NETWORKS AND SERVICE MANAGEMENT IN THE ERA OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Discover the impact that new technologies are having on communication systems with this up-to-date and one-stop resource Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning delivers a comprehensive overview of the impact of artificial intelligence (AI) and machine learning (ML) on service and network management. Beginning with a fulsome description of ML and AI, the book moves on to discuss management models, architectures, and frameworks. The authors also explore how AI and ML can be used in service management functions like the generation of workload profiles, service provisioning, and more. The book includes a handpicked selection of applications and case studies, as well as a treatment of emerging technologies the authors predict could have a significant impact on network and service management in the future. Statistical analysis and data mining are also discussed, particularly with respect to how they allow for an improvement of the management and security of IT systems and networks. Readers will also enjoy topics like: A thorough introduction to network and service management, machine learning, and artificial intelligence An exploration of artificial intelligence and machine learning for management models, including autonomic management, policy-based management, intent based ­management, and network virtualization-based management Discussions of AI and ML for architectures and frameworks, including cloud ­systems, software defined networks, 5G and 6G networks, and Edge/Fog networks An examination of AI and ML for service management, including the automatic ­generation of workload profiles using unsupervised learning Perfect for information and communications technology educators, Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning will also earn a place in the libraries of engineers and professionals who seek a structured reference on how the emergence of artificial intelligence and machine learning techniques is affecting service and network management.
A timely publication providing coverage of radio resourcemanagement, mobility management and standardization inheterogeneous cellular networks The topic of heterogeneous cellular networks has gained momentumin industry and the research community, attracting the attention ofstandardization bodies such as 3GPP LTE and IEEE 802.16j, whoseobjectives are looking into increasing the capacity and coverage ofthe cellular networks. This book focuses on recentprogresses, covering the related topics including scenariosof heterogeneous network deployment, interference management in theheterogeneous network deployment, carrier aggregation in aheterogeneous network, cognitive radio, cell selection/reselectionand load balancing, mobility and handover management, capacity andcoverage optimization for heterogeneous networks, trafficmanagement and congestion control. This book enables readers to better understand the technicaldetails and performance gains that are madepossible by this state-of-the-art technology. It contains theinformation necessary for researchers and engineers wishing tobuild and deploy highly efficient wireless networks themselves. Toenhance this practical understanding, the book is structured tosystematically lead the reader through a series of case-studies ofreal world scenarios. Key features: Presents this new paradigm in cellular network domain: aheterogeneous network containing network nodes with differentcharacteristics such as transmission power and RF coveragearea Provides a clear approach by containing tables, illustrations,industry case studies, tutorials and examples to cover the relatedtopics Includes new research results and state-of-the-arttechnological developments and implementation issues