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Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
|---|---|---|---|---|---|
Searching... | 30000010099426 | TK5103.4 L38 2006 | Open Access Book | Book | Searching... |
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Summary
Summary
This innovative book sets forth two promising wireless approaches that support high-quality, high-speed data and multimedia service-multiple antenna technologies and cross layer transmitter adaptation designs-while highlighting the relationships and interactions between them. The latest advanced technologies of channel adaptation techniques for wireless communication systems with multiple antennas are thoroughly investigated.
The book is divided into three parts, first giving readers a good foundation in underlying theory, then exploring applications as well as advanced topics:
* Part 1 examines theoretical aspects of channel adaptation in wireless communications for point-to-point and multi-user systems with multiple antennas
* Part 2 focuses on the applications of the channel-adaptive technologies in practical systems such as UMTS
* Part 3 delves into topics such as multi-user scheduling for wideband systems, combined queuing theory and information theory, and ad hoc routing
Using a hands-on, practical approach, Channel Adaptive Technologies and Cross Layer Designs for Wireless Systems with Multiple Antennas thoroughly covers detailed design considerations that help readers understand how to apply theory to real-world systems. Emphasis throughout the book is on joint optimization across different layers of a communications system based on an integrated approach. Examples of popular wireless systems, such as TDMA, wideband CDMA (UMTS), and HSDPA, are used throughout as practical illustrations. Each chapter ends with a summary that reviews key points and a set of problems that lets readers test their knowledge and continue to develop their skills as they progress to new topics. Figures and tables are also used extensively to help readers visualize complex theory and systems.
Combining theory, design, and application into one integrated approach, this is a superior reference for advanced communications theory courses.
Author Notes
Vincent K.N. Lau, PhD, is Associate Professor in the Department of Electrical Engineering at the Hong Kong University of Science and Technology. He is also a technology consultant and senior manager of ASTRI, leading the Advanced Technology Team of the Wireless Access Group in wireless LAN systems. Additionally, Dr. Lau was the chief technical officer and co-founder of DAX Group Ltd. He is a Senior IEEE Member, has published more than 42 papers in IEEE Transactions and journals, and has received two best paper awards (IEE and HKIE). Dr. Lau's current research focus is on the cross layer optimization between the wireless MAC (scheduling) layer and adaptive physical layer.
Yu-Kwong Ricky Kwok , PhD, is Associate Professor in the Department of Electrical and Electronic Engineering at the University of Hong Kong. He holds additional positions including Program Director of the Master of Science and Director of the High Performance Computing Research Laboratory. A Senior Member of the IEEE, he has published more than 130 technical papers in various leading journals, research books, and refereed international conference proceedings on topics including parallel and distributed computing research, mobile computing, wireless networking, grid computing infrastructure technologies, and analysis of distributed algorithms.
Table of Contents
| List of Figures |
| List of Tables |
| Preface |
| Acknowledgments |
| Part 1 Theory |
| Chapter 1 Basic Concepts in Wireless Communications |
| 1.1 Overview |
| 1.2 Wireless Channel Models |
| 1.2.1 AWGN Channel Model |
| 1.2.2 Linear Time-Varying Deterministic Spatial Channel |
| 1.2.3 The Random Channels |
| 1.2.4 Frequency-Flat Fading Channels |
| 1.2.5 Frequency-Selective Fading Channels |
| 1.3 Equivalence of Continuous-Time and Discrete-Time Models |
| 1.3.1 Concepts of Signal Space |
| 1.3.2 Sufficient Statistics |
| 1.3.3 Discrete-Time Signal Model-Flat Fading |
| 1.3.4 Discrete-Time Channel Model-Frequency-Selective Fading |
| 1.4 Fundamentals of Information Theory |
| 1.4.1 Entropy and Mutual Information |
| 1.4.2 Shannon's Channel Coding Theorem |
| 1.4.3 Examples of Channel Capacity |
| 1.5 Summary |
| Exercises |
| Chapter 2 MIMO Link with Perfect Channel State Information |
| 2.1 Overview |
| 2.2 Mathematical Model of the MIMO Link |
| 2.2.1 Probabilistic Channels with States |
| 2.2.2 General Transmission and CSI Feedback Model |
| 2.2.3 Adaptive-Channel Encoding and Decoding |
| 2.2.4 Transmit Power Constraint |
| 2.2.5 Causal Feedback Constraint |
| 2.3 Ergodic and Outage Channel Capacity |
| 2.3.1 Ergodic Capacity |
| 2.3.2 Outage Capacity |
| 2.4 Channel Capacity with No CSIT and No CSIR |
| 2.4.1 Fast Flat Fading MIMO Channels |
| 2.4.2 Block Fading Channels |
| 2.5 Channel Capacity with Perfect CSIR |
| 2.5.1 Block Fading Channels |
| 2.5.2 Fast Flat Fading MIMO Channels |
| 2.5.3 Effect of Antenna Correlation on Ergodic MIMO Capacity |
| 2.5.4 Slow Flat Fading MIMO Channels |
| 2.6 Channel Capacity with Perfect CSIT Only |
| 2.6.1 Discrete Block Fading Channels |
| 2.6.2 Discrete Channel with Three States |
| 2.6.3 Fast Flat Fading MIMO Channels |
| 2.6.4 Slow Flat Fading MIMO Channels |
| 2.7 Channel Capacity with Perfect CSIR and Perfect CSIT |
| 2.7.1 Fast Flat Fading MIMO Channels |
| 2.7.2 Slow Flat Fading MIMO Channels |
| 2.8 Summary |
| Exercises |
| Chapter 3 MIMO Link with Imperfect Channel State Information |
| 3.1 Overview |
| 3.2 Effect of Imperfect CSI Estimation |
| 3.2.1 CSI Estimation for MIMO Channels |
| 3.2.2 Capacity Bounds of MIMO Link |
| 3.3 Effect of Limited Feedback-Optimizing for SNR |
| 3.3.1 Introduction to Optimizing Effective SNR |
| 3.3.2 Grassmannian Line Packing |
| 3.3.3 Grassmannian Precoding for MIMO Systems-Spatial Diversity |
| 3.3.4 Grassmannian Precoding for MIMO Systems-Spatial Multiplexing |
| 3.4 Effect of Limited Feedback-Optimizing for Ergodic Capacity |
| 3.4.1 Channel Capacity with Partial CSIT |
| 3.4.2 Coding Theorem with Partial CSIT |
| 3.4.3 Equivalence with Vector Quantization Problem |
| 3.4.4 Fast Flat Fading MIMO Channels |
| 3.4.5 Lloyd's Algorithm |
| 3.4.6 Approximate Closed-Form Solution for Step 1 |
| 3.4.7 Complexity of the Online Adaptation Strategy |
| 3.4.8 MMSE-SIC Receiver Structure |
| 3.4.9 Numerical Results and Discussion |
| 3.5 Summary |
| Exercises |
| Chapter 4 Spacetime Coding and Layered Spacetime Coding for MIMO with Perfect Channel State Information |
| 4.1 Overview |
| 4.2 Design of MIMO Links with Perfect CSIR |
| 4.2.1 Spacetime Coding-Spatial Diversity |
| 4.2.2 Layered Spacetime Coding-Spatial Multiplexing |
| 4.2.3 Receiver Designs for Layered Spacetime Codes |
| 4.2.4 Optimal Architecture for Fast Flat Fading Channels |
| 4.2.5 Optimal Architecture for Slow Flat Fading Channels |
| 4.2.6 Fundamental Tradeoff between Spatial Diversity and Spatial Multiplexing |
| 4.3 Switching Threshold Design for MIMO Adaptation with Perfect CSIT and Perfect CSIR |
| 4.3.1 MIMO Transmitter and Adaptation Designs |
| 4.3.2 Optimization Problem_Quasistatic Fading Channels |
| 4.3.3 Equivalence to the Classical Vector Quantization Problem |
| 4.3.4 Results and Discussion |
| 4.4 Summary.Exercises |
| Chapter 5 MIMO Constellation Design with Imperfect Channel State Information |
| 5.1 Overview |
| 5.2 Constellation Design for MIMO Channels with Imperfect CSIR |
| 5.2.1 System Model |
| 5.2.2 Design Criteria Based on Kullback-Leibler Distance |
| 5.2.3 Constellation Design Optimization |
| 5.2.4 Single-Transmit Antenna Example |
| 5.2.5 Multitransmit Antenna Example |
| 5.3 Spacetime Coding for MIMO Channels with Imperfect CSIR |
| 5.3.1 Overview of Coded Modulation in AWGN Channels |
| 5.3.2 Coded Modulation Design for MIMO Ch |
