Details

Advanced Wireless Networks

Technology and Business Models
3. Aufl.

von: Savo G. Glisic
127,99 €
Verlag:	Wiley
Format:	PDF
Veröffentl.:	22.07.2016
ISBN/EAN:	9781119096870
Sprache:	englisch
Anzahl Seiten:	864

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Titelbeschreibung

The third edition of this popular reference covers enabling technologies for building up 5G wireless networks. Due to extensive research and complexity of the incoming solutions for the next generation of wireless networks it is anticipated that the industry will select a subset of these results and leave some advanced technologies to be implemented later,. This new edition presents a carefully chosen combination of the candidate network architectures and the required tools for their analysis. Due to the complexity of the technology, the discussion on 5G will be extensive and it will be difficult to reach consensus on the new global standard. The discussion will have to include the vendors, operators, regulators as well as the research and academic community in the field. Having a comprehensive book will help many participants to join actively the discussion and make meaningful contribution to shaping the new standard.

Inhaltsverzeichnis

Preface xv 1 Introduction: Generalized Model of Advanced Wireless Networks 1 1.1 Network Model 3 1.2 Network Connectivity 5 1.3 Wireless Network Design with Small World Properties 7 1.4 Frequency Channels Backup 11 1.5 Generalized Network Model 13 1.6 Routing Protocols Over s-Lattice Network 14 1.7 Network Performance 16 1.8 Node, Route, Topology, and Network Robustness 19 1.9 Power Consumption 20 1.10 Protocol Complexity 20 1.11 Performance Evaluation 21 1.12 Book Layout 27 Appendix A.1 33 References 34 2 Adaptive Network Layer 35 2.1 Graphs and Routing Protocols 35 2.2 Graph Theory 54 2.3 Routing with Topology Aggregation 56 References 60 3 Mobility Management 65 3.1 Cellular Networks 65 3.2 Cellular Systems with Prioritized Handoff 89 3.3 Cell Residing Time Distribution 100 3.4 Mobility Prediction in Pico- and Micro-Cellular Networks 105 Appendix A.3 Distance Calculation in an Intermediate Cell 116 References 122 4 Ad Hoc Networks 126 4.1 Routing Protocols 126 4.2 Hybrid Routing Protocol 146 4.3 Scalable Routing Strategies 152 4.4 Multipath Routing 160 4.5 Clustering Protocols 162 4.6 Cashing Schemes for Routing 175 4.7 Distributed QoS Routing 181 References 190 5 Sensor Networks 194 5.1 Introduction 194 5.2 Sensor Network Parameters 196 5.3 Sensor Network Architecture 199 5.4 Mobile Sensor Network Deployment 209 5.5 Directed Diffusion 212 5.6 Aggregation in Wireless Sensor Networks 216 5.7 Boundary Estimation 220 5.8 Optimal Transmission Radius in Sensor Networks 227 5.9 Data Funneling 233 5.10 Equivalent Transport Control Protocol in Sensor Networks 236 References 237 6 Security 244 6.1 Authentication 244 6.2 Security Architecture 253 6.3 Key Management 257 6.4 Security in Ad Hoc Networks 261 6.5 Security in Sensor Networks 268 References 269 7 Network Economics 272 7.1 Fundamentals of Network Economics 272 7.2 Wireless Network Microeconomics: Data Sponsoring 286 7.3 Spectrum Pricing for Market Equilibrium 291 7.4 Sequential Spectrum Sharing 300 7.5 Data Plan Trading 308 References 315 8 Multi-Hop Cellular Networks 318 8.1 Modeling Multi-Hop Multi-Operator Multi-Technology Wireless Networks 318 8.2 Technology Background 319 8.3 System Model and Notation 321 8.4 m3 Route Discovery Protocols 323 8.5 Performance of m3 Route Discovery Protocols 327 8.6 Protocol Complexity 329 8.7 Traffic Offloading Incentives 330 8.8 Performance Illustrations 335 References 344 9 Cognitive Networks 346 9.1 Technology Background 346 9.2 Spectrum Auctions for Multi-hop Cognitive Networks 350 9.3 Compound Auctioning in Multi-hop Cognitive Cellular Networks 363 References 388 10 Stochastic Geometry 391 10.1 Background Theory 391 References 398 11 Heterogeneous Networks 402 11.1 Preliminaries 402 11.2 Self-Organized Small Cell Networks 404 11.3 Dynamic Network Architecture 411 11.4 Economics of Heterogeneous Networks 434 References 443 12 Access Point Selection 446 12.1 Background Technology 446 12.2 Network Selection Game 449 12.3 Joint Access Point Selection and Power Allocation 453 12.4 Joint AP Selection and Beamforming Optimization 463 References 474 13 Self-Organizing Networks 478 13.1 Self-Organizing Network Optimization 478 13.2 System Model 478 13.3 Joint Optimization of Tilts and AP Association 481 References 484 14 Complex Networks 486 14.1 Evolution Towards Large-Scale Networks 486 14.2 Network Characteristics 491 14.3 Random Graphs 494 References 496 15 Massive MIMO 499 15.1 Linearly Precoded Multicellular Downlink System 499 15.2 System Model 503 15.3 Optimization for Perfect Channel State Information 505 15.4 Robust Designs for WSRM Problem 509 Appendix A.15 519 Appendix B.15 519 References 521 16 Network Optimization Theory 523 16.1 Introduction 523 16.2 Layering as Optimization Decomposition 524 16.3 Cross-Layer Optimization 533 16.4 Optimization Problem Decomposition Methods 543 References 554 17 Network Information Theory 557 17.1 Capacity of Ad Hoc Networks 557 17.2 Information Theory and Network Architectures 569 17.3 Cooperative Transmission in Wireless Multihop Ad Hoc Networks 577 References 584 18 Stability of Advanced Network Architectures 585 18.1 Stability of Cooperative Cognitive Wireless Networks 585 18.2 System Model 586 18.4 Optimal Control Policy 592 18.5 Achievable Rates 594 18.6 Stabilizing Transmission Policies 598 References 605 19 Multi-Operator Spectrum Sharing 607 19.1 Business Models for Spectrum Sharing 607 19.2 Spectrum Sharing in Multi-hop Networks 638 References 656 20 Large Scale Networks and Mean Field Theory 659 20.1 MFT for Large Heterogeneous Cellular Networks 659 20.2 Large Scale Network Model Compression 664 20.3 Mean Field Theory Model of Large Scale DTN Networks 668 20.4 Mean Field Modeling of Adaptive Infection Recovery in Multicast DTN Networks 674 20.5 Mean Field Theory for Scale-Free Random Networks 701 20.6 Spectrum Sharing and MFT 709 20.7 Modeling Dynamics of Complex System 711 Appendix A.20 Iterative Algorithm to Solve Systems of Nonlinear ODEs (DiNSE-Algorithm) 721 Appendix B.20 Infection Rate of Destinations for DNCM 722 Appendix C.20 Infection Rate for Basic Epidemic Routing 722 References 722 21 mmWave Networks 726 21.1 mmWave Technology in Subcellular Architecture 726 21.2 Microeconomics of Dynamic mmWave Networks 737 References 747 22 Cloud Computing in Wireless Networks 750 22.1 Technology Background 750 22.2 System Model 752 22.3 System Optimization 756 22.4 Dynamic Control Algorithm 758 22.5 Achievable Rates 761 22.6 Stabilizing Control Policies 763 References 769 23 Wireless Networks and Matching Theory 771 23.1 Background Technology: Matching Markets 772 23.2 Distributed Stable Matching in Multiple Operator Cellular Network with Traffic Offloading 776 23.3 College Admissions Game Model for Cellular Networks with Traffic Offloading 779 23.4 Many to Many Matching Games for Caching in Wireless Networks 783 23.5 Many to One Matching with Externalities in Cellular Networks with Traffic Offloading 787 23.6 Security in Matching of Device to Device Pairs in Cellular Networks 791 References 795 24 Dynamic Wireless Network Infrastructure 797 24.1 Infrastructure Sharing in Multi-Operator Cellular Networks 797 24.2 User Provided Connectivity 802 24.3 Network Virtualization 806 24.4 Software Defined Networks 810 24.5 SDN Security 816 References 819 Index 827

Autorenportrait

Savo Glisic, Professor of Telecommunications, University of Oulu, Finland Head of the Networking Research Group, and Director of Globalcomm Institute for Telecommunications. He was Visiting Scientist at Cranfield Institute of Technology, Cranfield, U.K. (1976-1977) and University of California, San Diego (1986-1987). He has been active in the field of wireless communications for 30 years. His research interest is in the area of network optimization theory, network topology control and graph theory, cognitive networks and game theory, radio resource management, QoS and queuing theory, networks information theory, protocol design, advanced routing and network coding, relaying, cellular, WLAN, ad hoc, sensor, active and bio inspired networks with emphasis on genetic algorithms and stochastic geometry. He runs an extensive doctoral program in the field of wireless networking (www.telecomlab.oulu.fi/kurssit/networks/).