Advanced Wireless Communications and Internet: Future Evolving Technologies, 3rd Edition
In the evolution of wireless communications, the dominant challenges are in the areas of networking and their integration with the Future Internet. Even the classical concept of cellular networks is changing and new technologies are evolving to replace it. To reflect these new trends,Advanced Wireless Communications & INTERNET builds upon the previous volumes, enhancing the existing chapters, and including a number of new topics. Systematically guiding readers from the fundamentals through to advanced areas, each chapter begins with an introductory explanation of the basic problems and solutions followed with an analytical treatment in greater detail.
The most important aspects of new emerging technologies in wireless communications are comprehensively covered including: next generation Internet; cloud computing and network virtualization; economics of utility computing and wireless grids and clouds. This gives readers an essential understanding of the overall environment in which future wireless networks will be operating. Furthermore, a number of methodologies for maintaining the network connectivity, by using tools ranging from genetic algorithms to stochastic geometry and random graphs theory, and a discussion on percolation and connectivity, are also offered. The book includes a chapter on network formation games, covering the general models, knowledge based network formation games, and coalition games in wireless ad hoc networks.
- Illustrates points throughout using real-life case studies drawn from the author's extensive international experience in the field of telecommunications
- Fully updated to include the latest developments, key topics covered include: Advanced routing and network coding; Network stability control; Relay-assisted Wireless Networks; Multicommodity flow optimization problems, flow optimization in heterogeneous networks, and dynamic resource allocation in computing clouds
- Methodically guides readers through each topic from basic to advanced areas
- Focuses on system elements that provide adaptability and re-configurability, and discusses how these features can improve wireless communications system performance
1.1 4G and the Book Layout.
1.2 General Structure of 4G Signals.
1.3 Next Generation Internet.
1.4 Cloud Computing and Network Virtualization.
1.5 Economics of Utility Computing.
1.6 Drawbacks of Cloud Computing.
1.7 Wireless Grids and Clouds.
2 Adaptive Coding.
2.1 Adaptive and Reconfigurable Block Coding.
2.2 Adaptive and Reconfigurable Convolutional Codes.
2.3 Concatenated Codes with Interleavers.
2.4 Adaptive Coding, Practice and Prospects.
2.5 Distributed Source Coding.
Appendix 2.1 Maximum a Posteriori Detection.
3 Adaptive and Reconfigurable Modulation.
3.1 Coded Modulation.
3.2 Adaptive Coded Modulation for Fading Channels.
4 Space–Time Coding.
4.1 Diversity Gain.
4.2 Space–Time Coding.
4.3 Space–Time Block Codes from Orthogonal Designs.
4.4 Channel Estimation Imperfections.
4.5 Quasi-Orthogonal Space–Time Block Codes.
4.6 Space–Time Convolutional Codes.
4.7 Algebraic Space–Time Codes.
4.8 Differential Space–Time Modulation.
4.9 Multiple Transmit Antenna Differential Detection from Generalized Orthogonal Designs.
4.10 Layered Space–Time Coding.
4.11 Concatenated Space–Time Block Coding.
4.12 Estimation of MIMO Channel.
4.13 Space–Time Codes for Frequency Selective Channels.
4.14 Optimization of a MIMO System.
4.15 MIMO Systems with Constellation Rotation.
4.16 Diagonal Algebraic Space–Time Block Codes.
Appendix 4.1 QR Factorization.
Appendix 4.2 Lattice Code Decoder for Space–Time Codes.
Appendix 4.3 MIMO Channel Capacity.
5 Multiuser Communication.
5.1 Pseudorandom Sequences.
5.2 Multiuser CDMA Receivers.
5.3 Minimum Mean Square Error (MMSE) Linear Multiuser Detection.
5.4 Single User LMMSE Receivers for Frequency Selective Fading Channels.
5.5 Signal Subspace-Based Channel Estimation for CDMA Systems.
5.6 Iterative Receivers for Layered Space–Time Coding.
Appendix 5.1 Linear and Matrix Algebra.
6 Channel Estimation and Equalization.
6.1 Equalization in the Digital Data Transmission System.
6.2 LMS Equalizer.
6.3 Detection for a Statistically Known, Time Varying Channel.
6.4 LMS-Adaptive MLSE Equalization on Multipath Fading Channels.
6.5 Adaptive Channel Identification and Data Demodulation.
6.6 Turbo Equalization.
6.7 Kalman Filter Based Joint Channel Estimation and Data Detection Over Fading Channels.
6.8 Equalization Using Higher Order Signal Statistics.
7 Orthogonal Frequency Division Multiplexing – OFDM and Multicarrier CDMA.
7.1 Timing and Frequency Offset in OFDM.
7.2 Fading Channel Estimation for OFDM Systems.
7.3 64 DAPSK and 64 QAM Modulated OFDM Signals.
7.4 Space–Time Coding with OFDM Signals.
7.5 Layered Space–Time Coding for MIMO OFDM.
7.6 Space–Time Coded TDMA/OFDM Reconfiguration Efficiency.
7.7 Multicarrier CDMA System.
7.8 Multicarrier DS-CDMA Broadcast Systems.
7.9 Frame By Frame Adaptive Rate Coded Multicarrier DS-CDMA System.
7.10 Intermodulation Interference Suppression in Multicarrier CDMA Systems.
7.11 Successive Interference Cancellation in Multicarrier DS-CDMA Systems.
7.12 MMSE Detection of Multicarrier CDMA.
7.13 Approximation of Optimum Multiuser Receiver for Space–Time Coded Multicarrier CDMA Systems.
7.14 Parallel Interference Cancellation in OFDM Systems in Time-Varying Multipath Fading Channels.
7.15 Zero Forcing OFDM Equalizer in Time-Varying Multipath Fading Channels.
7.16 Channel Estimation for OFDM Systems Using Multiple Receive Antennas.
7.17 Turbo Processing for an OFDM-Based MIMO System.
7.18 PAPR Reduction of OFDM Signals.
8 UltraWide Band Radio.
8.1 UWB Multiple Access in a Gaussian Channel.
8.2 The UWB Channel.
8.3 UWB System with M-ary Modulation.
8.4 M-ary PPM UWB Multiple Access.
8.5 Coded UWB Schemes.
8.6 Multiuser Detection in UWB Radio.
8.7 UWB with Space–Time Processing.
8.8 Beamforming for UWB Radio.
9 Linear Precoding for MIMO Channels.
9.1 Space–Time Precoders and Equalizers for MIMO Channels.
9.2 Linear Precoding Based on Convex Optimization Theory.
9.3 Convex Optimization-Theory-Based Beamforming.
10 Cognitive Networks.
10.1 Optimal Channel Sensing in Cognitive Wireless Networks.
10.2 Optimal Sequential Channel Sensing.
10.3 Optimal Parallel Multiband Channel Sensing.
10.4 Collaborative Spectrum Sensing.
10.5 Multichannel Cognitive MAC.
11 Relay-Assisted Wireless Networks (A. Agustin, J. Vidal,O.Muñoz, and S. Glisic).
11.2 Background and Related Work.
11.3 Cooperative Communications.
11.4 Relay-Assisted Communications.
11.5 Two-Way Relay-Assisted Communications.
11.6 Relay-Assisted Communications With Reuse of Resources.
12 Biologically Inspired Paradigms in Wireless Networks.
12.1 Biologically Inspired Model for Securing Hybrid Mobile Ad Hoc Networks.
12.2 Biologically Inspired Routing in Ad Hoc Networks.
12.3 Analytical Modeling of AntNet as Adaptive Mobile Agent Based Routing.
12.4 Biologically Inspired Algorithm for Optimum Multicasting.
12.5 Biologically Inspired (BI) Distributed Topology Control.
12.6 Optimization of Mobile Agent Routing in Sensor Networks.
12.7 Epidemic Routing.
12.9 Genetic Algorithm Based Dynamic Topology Reconfiguration in Cellular Multihop Wireless Networks.
13 Positioning in Wireless Networks.
13.1 Mobile Station Location in Cellular Networks.
13.2 Relative Positioning in Wireless Sensor Networks.
13.3 Average Performance of Circular and Hyperbolic Geolocation.
14 Wireless Networks Connectivity.
14.1 Survivable Wireless Networks Design.
14.2 Survivability of Wireless Ad Hoc Networks.
14.3 Network Dimensioning.
14.4 Survivable Network Under General Traffic.
14.5 Stochastic Geometry and Random Graphs Theory.
15 Advanced Routing and Network Coding.
15.1 Conventional Routing Versus Network Coding.
15.2 A Max-Flow Min-Cut Theorem.
15.3 Algebraic Formulation of Network Coding.
15.4 Random Network Coding.
15.5 Gossip Based Protocol and Network Coding.
15.6 Network Coding With Reduced Complexity.
15.7 Multisource Multicast Network Switching.
15.8 Optimization of Wireless Multicast Ad-Hoc Networks.
15.9 Optimization of Multicast Wireless Ad-Hoc Network Using Soft Graph Coloring and Non-Linear Cubic Games.
15.10 Joint Optimization of Routing and Medium Contention in Multihop Multicast Wireless Network.
15.11 Routing and Network Stability.
15.12 Lagrangian Decomposition of the Multicomodity Flow Optimization Problem.
15.13 Flow Optimization in Heterogeneous Networks.
15.14 Dynamic Resource Allocation in Computing Clouds.
16 Network Formation Games.
16.1 General Model of Network Formation Games.
16.2 Knowledge Based Network Formation Games.
16.3 Coalition Games in Wireless Ad Hoc Networks.
16.4 HD Game Based TCP Selection.
Professor Glisic obtained his PhD from Cranfield Institute of Technology, UK, before pursuing post doctoral studies at the University of California at San Diego, USA. His areas of interest include radio resource management in wireless mobile IP networks, network management, symbol synchronization in digital communications, automatic decision threshold level control (ADTLC) and frequency hopping modulation for wireless ad hoc networks. He has vast international experience in the field of telecommunications and has published prolifically on the subject, including three previous books with Wiley.