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Introduction to Wireless Digital Communication: A Signal Processing Perspective

Name: Introduction to Wireless Digital Communication: A Signal Processing Perspective
Author: Robert W. Heath
ISBN: 9780134431871

by Robert W. Heath

March 2017

Intermediate to advanced

464 pages

13h 59m

English

Pearson

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Cover Page
About This E-Book
Title Page
Copyright Page
Dedication Page
Contents
Preface
Acknowledgments
About the Author
Chapter 1. Introduction
1.1 Introduction to Wireless Communication1.2 Wireless Systems1.2.1 Broadcast Radio1.2.2 Broadcast Television1.2.3 Cellular Communication Networks1.2.4 Wireless Local Area Networks (WLANs)1.2.5 Personal Area Networks (PANs)1.2.6 Satellite Systems1.2.7 Wireless Ad Hoc Networks1.2.8 Wireless Sensor Networks1.2.9 Underwater Communication1.3 Signal Processing for Wireless Communication1.4 Contributions of This Book1.5 Outline of This Book1.6 Symbols and Common Definitions1.7 SummaryProblems

Chapter 2. An Overview of Digital Communication
2.1 Introduction to Digital Communication2.2 Overview of a Wireless Digital Communication Link2.3 Wireless Channel2.3.1 Additive Noise2.3.2 Interference2.3.3 Path Loss2.3.4 Multipath Propagation2.4 Source Coding and Decoding2.4.1 Lossless Source Coding2.4.2 Lossy Source Coding2.5 Encryption and Decryption2.6 Channel Coding and Decoding2.7 Modulation and Demodulation2.7.1 Baseband Modulation2.7.2 Passband Modulation2.7.3 Demodulation with Noise2.7.4 Demodulation with Channel Impairments2.8 SummaryProblems
Chapter 3. Signal Processing Fundamentals
3.1 Signals and Systems3.1.1 Types of Signals and Notation3.1.2 Linear Time-Invariant Systems3.1.3 The Fourier Transform3.1.4 Bandwidth of a Signal3.1.5 Sampling3.1.6 Discrete-Time Processing of Bandlimited Continuous-Time Signals3.2 Statistical Signal Processing3.2.1 Some Concepts from Probability3.2.2 Random Processes3.2.3 Moments of a Random Process3.2.4 Stationarity3.2.5 Ergodicity3.2.6 Power Spectrum3.2.7 Filtering Random Signals3.2.8 Gaussian Random Processes3.2.9 Random Vectors and Multivariate Random Processes3.3 Signal Processing with Passband Signals3.3.1 Upconversion—Creating a Passband Signal3.3.2 Downconversion—Extracting a Complex Baseband Signal from a Passband Signal3.3.3 Complex Baseband Equivalent Channel3.3.4 Pseudo-baseband Equivalent Channel3.3.5 The Discrete-Time Equivalent Channel3.4 Multirate Signal Processing3.4.1 Downsampling3.4.2 Upsampling3.4.3 Polyphase Decomposition3.4.4 Filtering with Upsampling and Downsampling3.4.5 Changing the Sampling Rate3.5 Linear Estimation3.5.1 Linear Algebra3.5.2 Least Squares Solution to a System of Linear Equations3.5.3 Maximum Likelihood Parameter Estimation in AWGN3.5.4 Linear Minimum Mean Squared Error Estimation3.6 SummaryProblems
Chapter 4. Digital Modulation and Demodulation
4.1 Transmitter for Complex Pulse-Amplitude Modulation4.2 Symbol Mapping and Constellations4.2.1 Common Constellations4.2.2 Symbol Mean4.2.3 Symbol Energy4.3 Computing the Bandwidth and Power of x(t)4.4 Communication in the AWGN Channel4.4.1 Introduction to the AWGN Channel4.4.2 Receiver for Complex Pulse-Amplitude Modulation in AWGN4.4.3 Pulse Shape Design for the AWGN Channel4.4.4 Symbol Detection in the AWGN Channel4.4.5 Probability of Symbol Error Analysis4.5 Digital Implementation of Pulse Shaping4.5.1 Transmit Pulse Shaping4.5.2 Receiver Matched Filtering4.6 SummaryProblems
Chapter 5. Dealing with Impairments
5.1 Frequency-Flat Wireless Channels5.1.1 Discrete-Time Model for Frequency-Flat Fading5.1.2 Symbol Synchronization5.1.3 Frame Synchronization5.1.4 Channel Estimation5.1.5 Equalization5.1.6 Carrier Frequency Offset Synchronization5.2 Equalization of Frequency-Selective Channels5.2.1 Discrete-Time Model for Frequency-Selective Fading5.2.2 Linear Equalizers in the Time Domain5.2.3 Linear Equalization in the Frequency Domain with SC-FDE5.2.4 Linear Equalization in the Frequency Domain with OFDM5.3 Estimating Frequency-Selective Channels5.3.1 Least Squares Channel Estimation in the Time Domain5.3.2 Least Squares Channel Estimation in the Frequency Domain5.3.3 Direct Least Squares Equalizer5.4 Carrier Frequency Offset Correction in Frequency-Selective Channels5.4.1 Model for Frequency Offset in Frequency-Selective Channels5.4.2 Revisiting Single-Frequency Estimation5.4.3 Frequency Offset Estimation and Frame Synchronization Using Periodic Training for Single-Carrier Systems5.4.4 Frequency Offset Estimation and Frame Synchronization Using Periodic Training for OFDM Systems
5.5 Introduction to Wireless Propagation
5.5.1 Mechanisms of Propagation5.5.2 Propagation Modeling5.6 Large-Scale Channel Models5.6.1 Friis Free-Space Model5.6.2 Log-Distance Path-Loss Model5.6.3 LOS/NLOS Path-Loss Model5.6.4 Performance Analysis Including Path Loss5.7 Small-Scale Fading Selectivity5.7.1 Introduction to Selectivity5.7.2 Frequency-Selective Fading5.7.3 Time-Selective Fading5.7.4 Signal Models for Channel Selectivity5.8 Small-Scale Channel Models5.8.1 Flat-Fading Channel Models5.8.2 Frequency-Selective Channel Models5.8.3 Performance Analysis with Fading Channel Models5.9 SummaryProblems
Chapter 6. MIMO Communication
6.1 Introduction to Multi-antenna Communication6.1.1 Single-Input Multiple-Output (SIMO)6.1.2 Multiple-Input Single-Output (MISO)6.1.3 Multiple-Input Multiple-Output (MIMO)6.2 Receiver Diversity for Flat-Fading SIMO Systems6.2.1 SIMO Flat-Fading Channel Models6.2.2 Antenna Selection6.2.3 Maximum Ratio Combining6.3 Transmit Diversity for MISO Systems6.3.1 MISO Flat-Fading Channel Models6.3.2 Why Spatial Repetition Does Not Work6.3.3 Transmit Beamforming6.3.4 Limited Feedback Beamforming6.3.5 Reciprocity-Based Beamforming6.3.6 The Alamouti Code6.3.7 Space-Time Coding6.4 MIMO Transceiver Techniques6.4.1 Spatial Multiplexing6.4.2 MIMO Flat-Fading Channel Models6.4.3 Detection and Equalization for Spatial Multiplexing6.4.4 Linear Precoding6.4.5 Extensions to Limited Feedback6.4.6 Channel Estimation in MIMO Systems6.4.7 Going Beyond the Flat-Fading Channel to Frequency-Selective Channels6.5 MIMO-OFDM Transceiver Techniques6.5.1 System Model6.5.2 Equalization and Detection6.5.3 Precoding6.5.4 Channel Estimation6.5.5 Carrier Frequency Synchronization6.6 SummaryProblems
References
Index

Overview

The Accessible Guide to Modern Wireless Communication for Undergraduates, Graduates, and Practicing Electrical Engineers

Wireless communication is a critical discipline of electrical engineering and computer science, yet the concepts have remained elusive for students who are not specialists in the area. This text makes digital communication and receiver algorithms for wireless communication broadly accessible to undergraduates, graduates, and practicing electrical engineers. Notably, the book builds on a signal processing foundation and does not require prior courses on analog or digital communication.

Introduction to Wireless Digital Communication establishes the principles of communication, from a digital signal processing perspective, including key mathematical background, transmitter and receiver signal processing algorithms, channel models, and generalizations to multiple antennas. Robert Heath’s “less is more” approach focuses on typical solutions to common problems in wireless engineering.

Heath presents digital communication fundamentals from a signal processing perspective, focusing on the complex pulse amplitude modulation approach used in most commercial wireless systems. He describes specific receiver algorithms for implementing wireless communication links, including synchronization, carrier frequency offset estimation, channel estimation, and equalization. While most concepts are presented for systems with single transmit and receive antennas, Heath concludes by extending those concepts to contemporary MIMO systems.

To promote learning, each chapter includes previews, bullet-point summaries, examples, and numerous homework problems to help readers test their knowledge.

Basics of wireless communication: applications, history, and the central role of signal processing
Digital communication essentials: components, channels, distortion, coding/decoding, encryption, and modulation/demodulation
Signal processing: linear time invariant systems, probability/random processes, Fourier transforms, derivation of complex baseband signal representation and equivalent channels, and multi-rate signal processing
Least-squared estimation techniques that build on the linear algebra typically taught to electrical engineering undergraduates
Complex pulse amplitude modulation: symbol mapping, constellations, signal bandwidth, and noise
Synchronization, including symbol, frame, and carrier frequency offset
Frequency selective channel estimation and equalization
MIMO techniques using multiple transmit and/or receive antennas, including SIMO, MISO, and MIMO-OFDM

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