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This book provides a comprehensive introduction to the underlying theory, design techniques and analytical results of wireless communication networks, focusing on the core principles of wireless network design. It elaborates the network utility maximization (NUM) theory with applications in resource allocation of wireless networks, with a central aim of design and the QoS guarantee. It presents and discusses state-of-the-art developments in resource allocation and performance optimization in wireless communication networks. It provides an overview of the general background including the basic wireless communication networks and the relevant protocols, architectures, methods and algorithms.
Network Optimization and Control is the ideal starting point for a mature reader with little background on the subject of congestion control to understand the basic concepts underlying network resource allocation.
The purpose of this book is to provide tools for a better understanding of the fundamental tradeo?s and interdependencies in wireless networks, with the goal of designing resource allocation strategies that exploit these int- dependencies to achieve signi?cant performance gains. Two facts prompted us to write it: First, future wireless applications will require a fundamental understanding of the design principles and control mechanisms in wireless networks. Second, the complexity of the network problems simply precludes the use of engineering common sense alone to identify good solutions, and so mathematics becomes the key avenue to cope with central technical problems in the design of wireless networks. In this book, two ?elds of mathematics play a central role: Perron-Frobenius theory for non-negative matrices and optimization theory. This book is a revised and expanded version of the research monograph “Resource Allocation in Wireless Networks” that was published as Lecture Notes in Computer Sciences (LNCS 4000) in 2006. Although the general structure has remained unchanged to a large extent, the book contains - merous additional results and more detailed discussion. For instance, there is a more extensive treatment of general nonnegative matrices and interf- ence functions that are described by an axiomatic model. Additional material on max-min fairness, proportional fairness, utility-based power control with QoS (quality of service) support and stochastic power control has been added.
With the diversification of Internet services and the increase in mobile users, efficient management of network resources has become an extremely important issue in the field of wireless communication networks (WCNs). Adaptive resource management is an effective tool for improving the economic efficiency of WCN systems as well as network design and construction, especially in view of the surge in mobile device demands. This book presents modelling methods based on queueing theory and Markov processes for a wide variety of WCN systems, as well as precise and approximate analytical solution methods for the numerical evaluation of the system performance. This is the first book to provide an overview of the numerical analyses that can be gleaned by applying queueing theory, traffic theory and other analytical methods to various WCN systems. It also discusses the recent advances in the resource management of WCNs, such as broadband wireless access networks, cognitive radio networks, and green cloud computing. It assumes a basic understanding of computer networks and queueing theory, and familiarity with stochastic processes is also recommended. The analysis methods presented in this book are useful for first-year-graduate or senior computer science and communication engineering students. Providing information on network design and management, performance evaluation, queueing theory, game theory, intelligent optimization, and operations research for researchers and engineers, the book is also a valuable reference resource for students, analysts, managers and anyone in the industry interested in WCN system modelling, performance analysis and numerical evaluation.
This book covers issues related to 5G network security. The authors start by providing details on network architecture and key requirements. They then outline the issues concerning security policies and various solutions that can handle these policies. Use of SDN-NFV technologies for security enhancement is also covered. The book includes intelligent solutions by utilizing the features of artificial intelligence and machine learning to improve the performance of the 5G security protocols and models. Optimization of security models is covered as a separate section with a detailed information on the security of 5G-based edge, fog, and osmotic computing. This book provides detailed guidance and reference material for academicians, professionals, and researchers. Presents extensive information and data on research and challenges in 5G networks; Covers basic architectures, models, security frameworks, and software-defined solutions for security issues in 5G networks; Provides solutions that can help in the growth of new startups as well as research directions concerning the future of 5G networks.
This book, building on the authors’ previous work, presents new communication and networking technologies, challenges and opportunities of information/data processing and transmission. It also discusses the development of more intelligent and efficient communication technologies, which are an essential part of current day-to-day life. Information and Communication Technologies (ICTs) have an enormous impact on businesses and our day-to-day lives over the past three decades and continue to do so. Modern methods of business information processing are opening exciting new opportunities for doing business on the basis of information technologies. The book contains research that spans a wide range of communication and networking technologies, including wireless sensor networks, optical and telecommunication networks, storage area networks, error-free transmission and signal processing.
Scientific Study from the year 2016 in the subject Engineering - Communication Technology, Mahalingam College of Engineering and Technology, language: English, abstract: The future Wireless Communication Systems (WCS) are supposed to provide high data rate to support personal and multimedia communications irrespective of the users' mobility and location. These services include heterogeneous classes of traffics such as voice, file transfer, web browsing, wireless multimedia, teleconferencing, and interactive games. In recent years, data and multimedia services have become important in wireless communications. As a result, bandwidth requirement and number of users become delicate problems. To support high data rate requirement for future WCS, it is essential to efficiently allocate the limited resources. The major challenges are the dynamic nature of wireless channel, limited resources such as power, frequency spectrum, and diversified Quality of Service (QoS) requirements. Orthogonal Frequency Division Multiplexing (OFDM) is a special case of multicarrier transmission that supports high data rate operation. OFDM is a modulation and multiplexing technique appropriate for current and future wireless networks. OFDM divides the available bandwidth into a number of parallel independent orthogonal subchannels and their bandwidth is much less than the coherence bandwidth of the channel. The wide band frequency selective fading channel is converted into several narrow band flat fading channels. OFDM is an excellent method to overcome multipath fading effects. One of the goals of WCS is to enhance the capacity of the channel. Multiple Access Technique (MAT) permits several mobile users to share the given bandwidth in an effective way. Basically there are four multiple access techniques available namely, Time Division Multiple Access (TDMA), Frequency Division Multiple access (FDMA), Code Division Multiple Access (CDMA) and Space Division Multiple Access (SDMA). MAT is employ
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.
Information flow in a telecommunication network is accomplished through the interaction of mechanisms at various design layers with the end goal of supporting the information exchange needs of the applications. In wireless networks in particular, the different layers interact in a nontrivial manner in order to support information transfer. In this text we will present abstract models that capture the cross-layer interaction from the physical to transport layer in wireless network architectures including cellular, ad-hoc and sensor networks as well as hybrid wireless-wireline. The model allows for arbitrary network topologies as well as traffic forwarding modes, including datagrams and virtual circuits. Furthermore the time varying nature of a wireless network, due either to fading channels or to changing connectivity due to mobility, is adequately captured in our model to allow for state dependent network control policies. Quantitative performance measures that capture the quality of service requirements in these systems depending on the supported applications are discussed, including throughput maximization, energy consumption minimization, rate utility function maximization as well as general performance functionals. Cross-layer control algorithms with optimal or suboptimal performance with respect to the above measures are presented and analyzed. A detailed exposition of the related analysis and design techniques is provided.
This unified 2001 treatment of game theory focuses on finding state-of-the-art solutions to issues surrounding the next generation of wireless and communications networks. The key results and tools of game theory are covered, as are various real-world technologies and a wide range of techniques for modeling, design and analysis.