Electrical and computer engineers need to understand the most current technologies in the field. In order to provide the latest information, the sixth edition presents a new chapter that explores the principles of digital data transmission without the complicating factor of performance in noise. It exposes readers to digital data transmission techniques earlier in the book so that they can appreciate the characteristics of digital communication systems before learning about probability and stochastic processes. They’ll also find expanded forward error correction code examples and new MATLAB problems. Electrical and computer engineers will benefit from this completely up-to-date resource.
CHAPTER 1: INTRODUCTION.1.1 The Block Diagram of Communication System.
1.2 Channel Characteristics.
1.3 Summary of Systems Analysis Techniques.
1.4 Probabilistic Approaches to System Optimization.
1.5 Preview of This Book.
Further Reading.
CHAPTER 2: SIGNAL AND LINEAR SYSTEM ANALYSIS.
2.1 Signal Models.
2.2 Signal Classifications.
2.3 Generalized Fourier Series.
2.4 Further Series.
2.5 The Fourier Transform.
2.6 Power Spectral Density and Correlation.
2.7 Signals and Linear Systems.
2.8 Sampling Theory.
2.9 The Hilbert Transform.
2.10 Discrete Fourier Transform and Fast Fourier Transform.
Summary.
Further Reading.
Problems.
Computer Exercises.
CHAPTER 3: BASIC MODULATION TECHNIQUES.
3.1 Linear Modulation.
3.2 Angle Modulation.
3.3 Interference.
3.4 Feedback Demodulators: The Phase-Locked Loop.
3.5 Analog Pulse Modulation.
3.6 Delta Modulation and PCM.
3.7 Multiplexing.
Summary.
Further Reading.
Problems.
Computer Exercises.
CHAPTER 4: PRINCIPLES OF BASEBAND DIGITAL DATA TRANSMISSION.
4.1 Baseband Digital Data Transmission Systems.
4.2 Line Codes and Their Power Spectra.
4.3 Effects of Filtering of Digital Data: ISI.
4.4 Pulse Shaping: Nyquist???s Criterion for Zero ISI.
4.5 Zero-Forcing Equalization.
4.6 Eye Diagrams.
4.7 Synchronization.
4.8 Carrier Modulation of Baseband Digital Signals.
Summary.
Further Reading.
Problems.
Computer Exercises.
CHAPTER 5: OVERVIEW OF PROBABILITY AND RANDOM VARIABLES.
5.1 What is Probability?
5.2 Random Variables and Related Functions.
5.3 Statistical Averages.
5.4 Some Useful pdfs.
Summary.
Further Reading.
Problems.
Computer Exercises.
CHAPTER 6: RANDOM SIGNALS AND NOISE.
6.1 A Relative-Frequency Description of Random Processes.
6.2 Some Terminology of Random Processes.
6.3 Correlation and Power Spectral Density.
6.4 Linear Systems and Random Processes.
6.5 Narrowband Noise.
Summary.
Further Reading.
Problems.
Computer Exercises.
CHAPTER 7: NOISE IN MODULATION SYSTEMS.
7.1 Signal-to-Noise Ratios.
7.2 Noise and Phase Errors in Coherent Systems.
7.3 Noise in Angle Modulation.
7.4 Threshold Effect in FM Demodulation.
7.5 Noise in Pulse-Code Modulation.
Summary.
Further Reading.
Problems.
Computer Exercises.
CHAPTER 8: PRINCIPLES OF DATA TRANSMISSION IN NOISE.
8.1 Baseband Data Transmission in White Gaussian Noise.
8.2 Binary Data Transmission with Arbitrary Signal Shapes.
8.3 Modulation Schemes Not Requiring Coherent References.
8.4 M-ary PAM.
8.5 Comparison of Digital Modulation Systems.
8.6 Performance of Zero-ISI Digital Data Systems.
8.7 Multipath Interference.
8.8 Flat Fading Channels.
8.9 Equalization.
Summary.
Further Reading.
Problem.
Computer Exercises.
CHAPTER 9: ADVANCED DATA COMMUNICATIONS TOPICS.
9.1 M-ary Data Communications Systems.
9.2 Power Spectra for Quandrature Modulation Techniques.
9.3 Synchronization.
9.4 Spread-Spectrum Communication Systems.
9.5 Multicarrier Modulation and Orthogonal Frequency Division Multiplexing.
9.6 Satellite Communications.
9.7 Cellular Radio Communication Systems.
Summary.
Further Reading.
Problems.
Computer Exercises.
CHAPTER 10: OPTIMUM RECEIVERS AND SIGNAL SPACE CONCEPTS.
10.1 Bayes Optimization.
10.2 Vector Space Representation of Signals.
10.3 Maximum A Posteriori Receiver for Digital Data Transmission.
10.4 Estimation Theory.
10.5 Applications of Estimation Theory to Communications.
Summary.
Further Reading.
Problems.
Computer Exercises.
CHAPTER 11: INFORMATION THEORY AND CODING.
11.1 Basic Concepts.
11.2 Source Coding.
11.3 Communication in Noisy Environments: Basic Ideas.
11.4 Communication in Noisy Channels: Block Codes.
11.5 Communication in Noisy Channels: Convolutional Codes.
11.6 Communication in Noisy Channels: Other Techniques.
11.7 Modulation and Bandwidth Efficiency.
11.8 Bandwidth and Power Efficient Modulation.
Summary.
Further Reading.
Problems.
Computer Exercises.
APPENDIX A: PHYSICAL NOISE SOURCES.
A.1 Physical Noise Sources.
A.2 Characterization of Noise in Systems.
A.3 Free-Space Propagation Example.
A.4 Further Reading.
A.5 Problems.
APPENDIX B: JOINTLY GAUSSIAN RANDOM VARIABLES.
B.1 The Probability Density Function.
B.2 The Characteristics Function.
B.3 Linear Transformations.
APPENDIX C: PROOF OF THE NARROWBAND NOISE MODEL.
APPENDIX D: ZERO-CROSSING AND ORIGIN ENCIRCLEMENT STATISTICS.
D.1 The Zero-Crossing Problem.
D.2 Average Rate of Zero Crossings.
D.3 Problems.
APPENDIX E: CHI-SQUARE STATISTICS.
APPENDIX F: QUANTIZATION OF RANDOM PROCESSES.
APPENDIX G: MATHEMATICAL AND NUMERICAL TABLES.
G.1 The Gaussian Q-Function.
G.2 Trigonometric Identities.
G.3 Series Expansions.
G.4 Integrals.
G.5 Fourier Transform Pairs.
G.6 Fourier Transform Theorems.
References.
Author Index.
Subject Index.