Cross Layer Resource Allocation In Wireless Communications

Cross-Layer Resource Allocation in Wireless Communications offers practical techniques and models for the design and optimisation of cross-layer resource allocation – one of the hottest topics in wireless communications. Resource allocation in wireless networks is traditionally approached either through information theory or communications networks. To break down the barriers between these distinct approaches, this book bridges the physical and network layers by providing cross-layer resource allocation techniques, models, and methodologies. Its unique approach allows optimisation of network resources and will enable engineers to improve signal quality, enhance network and spectrum utilization, increase throughput, and solve the problem of shadowing. Topics covered include different views of spectral efficiency, the role of spatial diversity, of delay in resource allocation, and possible extensions to OFDMA systems. This will be an ideal reference on cross-layer resource allocation between the PHY and MAC layers for R&D and network design engineers and researchers in universities dealing with sensor networks and cognitive systems. * Gives a full description of the characteristics of the PHY layer that promote efficient resource allocation strategies * Gives special emphasis on cross-layer design for spatial diversity schemes * Provides a framework for interaction between the PHY and MAC layers, their parameters of performance and their relationship * Presents resource allocation as a cross-layer design based on an optimization of MAC layer parameters with an accurate model of the PHY layer

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.

Information .ow 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 di erent layers interact in a nontrivial manner in order to support information transfer. In this paper 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 tra c forwarding modes, including datagrams and virtual cir- cuits. 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.

Adaptive techniques play a key role in modern wireless communication systems. The concept of adaptation is emphasized in the Adaptation in Wireless Communications Series through a unified framework across all layers of the wireless protocol stack ranging from the physical layer to the application layer, and from cellular systems to next-generation wireless networks. Adaptation and Cross Layer Design in Wireless Networks is devoted to adaptation in the data link layer, network layer, and application layer. The book presents state-of-the-art adaptation techniques and methodologies, including cross-layer adaptation, joint signal processing, coding and networking, selfishness in mobile ad hoc networks, cooperative and opportunistic protocols, adaptation techniques for multimedia support, self –organizing routing, and tunable security services. It presents several new theoretical paradigms and analytical findings which are supported with various simulation and experimental results. Adaptation in wireless communications is needed in order to achieve high capacity and ubiquitous communications. The current trend in wireless communication systems is to make adaptation dependent upon the state of the relevant parameters in all layers of the system. Focusing on simplified cross layer design approaches, this volume describes advanced techniques such as adaptive resource management, adaptive modulation and coding, 4G communications, QoS, diversity combining, and energy and mobility aware MAC protocols. The first volume in the series, Adaptive Signal Processing in Wireless Communications (cat no.46012) covers adaptive signal processing at the physical layer.

Do you need to improve wireless system performance? Learn how to maximise the efficient use of resources with this systematic and authoritative account of wireless resource management. Basic concepts, optimization tools and techniques, and application examples, are thoroughly described and analysed, providing a unified framework for cross-layer optimization of wireless networks. State-of-the-art research topics and emerging applications, including dynamic resource allocation, cooperative networks, ad hoc/personal area networks, UWB, and antenna array processing, are examined in depth. If you are involved in the design and development of wireless networks, as a researcher, graduate student or professional engineer, this is a must-have guide to getting the best possible performance from your network.

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.

This book introduces the sources and historic collection campaigns of resource allocation in wireless communication systems. The unique characteristics of MIMO-OFDMA systems are thoroughly studied and summarized. Remarks on resource allocation and spectrum sharing are also presented, which demonstrate the great value of resource allocation techniques, but also introduce distinct challenges of resource allocation in MIMO-OFDMA systems. Novel resource allocation techniques for OFDMA Systems are surveyed from various applications (e.g., for unicast, or multicast with Guaranteed BER and Rate, subcarrier and power allocation with various detectors, low-complexity energyefficient resource allocation, etc.) in this book. Due to the high mobility and low latency requirements of 5G wireless communications, this book discusses how to deal with the imperfect CSI. It also discusses how to deal with e.g., throughput maximization, outage probabilities maximization and guarantee, energy efficiency, physical-layer security issues with feedback channel capacity constraints, in order to characterize and understand the applications of practical scenes. This book will target professionals & researchers working in the fields of Wireless Communications and Networking, Resource Allocation and Transmissions. Advanced-level students in electrical engineering and computer science will also find this book useful as a secondary textbook.