Digital and Analog Communication Systems – León W. Couch – 8th Edition US

Preface
List of Symbols

Chapter 1. INTRODUCTION
1—1 Historical Perspective
1—2 Digital and Analog Sources and Systems
1—3 Deterministic and Random Waveforms
1—4 Organization of the Book
1—5 Use of a Personal Computer and MATLAB
1—6 Block Diagram of a Communication System
1—7 Frequency Allocations
1—8 Propagation of Electromagnetic Waves
1—9 Information Measure
1—10 Channel Capacity and Ideal Communication Systems
1—11 Coding
Block Codes,
Convolutional Codes,
Code Interleaving,
Code Performance,
Trellis-Coded Modulation,
1—12 Preview
1—13 Study-Aid Examples
Problems

Chapter 2. SIGNALS AND SPECTRA
2—1 Properties of Signals and Noise
Physically Realizable Waveforms
Time Average Operator
DC Value
Power
RMS Value and Normalized Power
Energy and Power Waveforms
Decibel
Phasors
2—2 Fourier Transform and Spectra
Definition
Properties of Fourier Transforms
Parseval’s Theorem and Energy Spectral Density
Dirac Delta Function and Unit Step Function
Rectangular and Triangular Pulses
Convolution
2—3 Power Spectral Density and Autocorrelation Function
Power Spectral Density
Autocorrelation Function
2—4 Orthogonal Series Representation of Signals and Noise
Orthogonal Functions
Orthogonal Series
2—5 Fourier Series
Complex Fourier Series
Quadrature Fourier Series
Polar Fourier Series
Line Spectra for Periodic Waveforms
Power Spectral Density for Periodic Waveforms
2—6 Review of Linear Systems
Linear Time-Invariant Systems
Impulse Response
Transfer Function
Distortionless Transmission
Distortion of Audio, Video, and Data Signals
2—7 Bandlimited Signals and Noise
Bandlimited Waveforms
Sampling Theorem
Impulse Sampling and Digital Signal Processing (DSP)
Dimensionality Theorem
2—8 Discrete Fourier Transform
Using the DFT to Compute the Continuous Fourier Transform
Using the DFT to Compute the Fourier Series0
2—9 Bandwidth of Signals
2—10 Summary
2—11 Study-Aid Examples
Problems

Chapter 3 BASEBAND PULSE AND DIGITAL SIGNALING
3—1 Introduction
3—2 Pulse Amplitude Modulation
Natural Sampling (Gating)
Instantaneous Sampling (Flat-Top PAM)
3—3 Pulse Code Modulation
Sampling, Quantizing, and Encoding
Practical PCM Circuits
Bandwidth of PCM Signals
Effects of Noise
Nonuniform Quantizing: _-Law and A-Law Companding
V.90 56-kb/s PCM Computer Modem
3—4 Digital Signaling
Vector Representation
Bandwidth Estimation
Binary Signaling
Multilevel Signaling
3—5 Line Codes and Spectra
Binary Line Coding
Power Spectra for Binary Line Codes
Differential Coding
Eye Patterns
Regenerative Repeaters
Bit Synchronization
Power Spectra for Multilevel Polar NRZ Signals
Spectral Efficiency
3—6 Intersymbol Interference
Nyquist’s First Method (Zero ISI)
Raised Cosine-Rolloff Nyquist Filtering
Nyquist’s Second and Third Methods for Control of ISI
3—7 Differential Pulse Code Modulation
3—8 Delta Modulation
Granular Noise and Slope Overload Noise
Adaptive Delta Modulation and Continuously Variable Slope
Delta Modulation
Speech Coding
3—9 Time-Division Multiplexing
Frame Synchronization
Synchronous and Asynchronous Lines
TDM Hierarchy
The T1 PCM System
3—10 Packet Transmission System
3—11 Pulse Time Modulation: Pulse Width Modulation and Pulse Position Modulation
3—12 Summary
3—13 Study-Aid Examples
Problems

Chapter 4 BANDPASS SIGNALING PRINCIPLES AND CIRCUITS
4—1 Complex Envelope Representation of Bandpass Waveforms
Definitions: Baseband, Bandpass, and Modulation
Complex Envelope Representation
4—2 Representation of Modulated Signals
4—3 Spectrum of Bandpass Signals
4—4 Evaluation of Power
4—5 Bandpass Filtering and Linear Distortion
Equivalent Low-Pass Filter
Linear Distortion
4—6 Bandpass Sampling Theorem
4—7 Received Signal Plus Noise
4—8 Classification of Filters and Amplifiers
Filters
Amplifiers
4—9 Nonlinear Distortion
4—10 Limiters
4—11 Mixers, Up Converters, and Down Converters
4—12 Frequency Multipliers
4—13 Detector Circuits
Envelope Detector
Product Detector
Frequency Modulation Detector
4—14 Phase-Locked Loops and Frequency Synthesizers
4—15 Direct Digital Synthesis
4—16 Transmitters and Receivers
Generalized Transmitters
Generalized Receiver: The Superheterodyne Receiver
Zero-IF Receivers
Interference
4—17 Software Radios
4—18 Summary
4—19 Study-Aid Examples
Problems

Chapter 5 AM, FM, AND DIGITAL MODULATED SYSTEMS
5—1 Amplitude Modulation
5—2 AM Broadcast Technical Standards
Digital AM Braodcasting
5—3 Double-Sideband Suppressed Carrier
5—4 Costas Loop and Squaring Loop
5—5 Asymmetric Sideband Signals
Single Sideband
Vestigial Sideband
5—6 Phase Modulation and Frequency Modulation
Representation of PM and FM Signals
Spectra of Angle-Modulated Signals
Narrowband Angle Modulation
Wideband Frequency Modulation
Preemphasis and Deemphasis in Angle-Modulated Systems
5—7 Frequency-Division Multiplexing and FM Stereo
5—8 FM Broadcast Technical Standards
Digital FM Braodcasting
5—9 Binary Modulated Bandpass Signaling
On-Off Keying (OOK)
Binary Phase-Shift Keying (BPSK)
Differential Phase-Shift Keying (DPSK)
Frequency-Shift Keying (FSK)
5—10 Multilevel Modulated Bandpass Signaling
Quadrature Phase-Shift Keying (QPSK) and M-ary Phase-Shift Keying (MPSK)
Quadrature Amplitude Modulation (QAM)
OQPSK and _/4 QPSK
PSD for MPSK, QAM, QPSK, OQPSK, and _/4 QPSK
Spectral Efficiency for MPSK, QAM, QPSK, OQPSK, and _/4 QPSK
with Raised Cosine Filtering
5—11 Minimum-Shift Keying (MSK) and GMSK
5—12 Orthogonal Frequency Division Multiplexing (OFDM)
5—13 Spread Spectrum Systems
Direct Sequence
Frequency Hopping
SS Frequency Bands
5—14 Summary
5—15 Study-Aid Examples
Problems

Chapter 6 RANDOM PROCESSES AND SPECTRAL ANALYSIS
6—1 Some Basic Definitions
Random Processes
Stationarity and Ergodicity
Correlation Functions and Wide-Sense Stationarity
Complex Random Processes
6—2 Power Spectral Density
Definition
Wiener-Khintchine Theorem
Properties of the PSD
General Formula for the PSD of Digital Signals
White-Noise Processes
Measurement of PSD
6—3 DC and RMS Values for Ergodic Random Processes
6—4 Linear Systems
Input-Output Relationships
6—5 Bandwidth Measures
Equivalent Bandwidth
RMS Bandwidth
6—6 The Gaussian Random Process
Properties of Gaussian Processes
6—7 Bandpass Processes
Bandpass Representations
Properties of WSS Bandpass Processes
Proofs of Some Properties
6—8 Matched Filters
General Results
Results for White Noise
Correlation Processing
Transversal Matched Filter
6—9 Summary
6—10 Appendix: Proof of Schwarz’s Inequality
6—11 Study-Aid Examples
Problems

Chapter 7 PERFORMANCE OF COMMUNICATION SYSTEMS CORRUPTED BY NOISE
7—1 Error Probabilities for Binary Signaling
General Results
Results for Gaussian Noise
Results for White Gaussian Noise and Matched-Filter Reception
Results for Colored Gaussian Noise and Matched-Filter Reception
7—2 Performance of Baseband Binary Systems
Unipolar Signaling
Polar Signaling
Bipolar Signaling
7—3 Coherent Detection of Bandpass Binary Signals
On-Off Keying
Binary-Phase-Shift Keying
Frequency-Shift Keying
7—4 Noncoherent Detection of Bandpass Binary Signals
On-Off Keying
Frequency-Shift Keying
Differential Phase-Shift Keying
7—5 Quadrature Phase-Shift Keying and Minimum-Shift Keying
7—6 Comparison of Digital Signaling Systems
Bit-Error Rate and Bandwidth
Symbol Error and Bit Error for Multilevel Signaling
Synchronization
7—7 Output Signal-to-Noise Ratio for PCM Systems
7—8 Output Signal-to-Noise Ratios for Analog Systems
Comparison with Baseband Systems
AM Systems with Product Detection
AM Systems with Envelope Detection
DSB-SC Systems
SSB Systems
PM Systems
FM Systems
FM Systems with Threshold Extension
FM Systems with Deemphasis
7—9 Comparison of Analog Signaling Systems
Ideal System Performance
7—10 Summary
7—11 Study-Aid Examples
Problems

Chapter 8 WIRE AND WIRELESS COMMUNICATION SYSTEMS
8—1 The Explosive Growth of Telecommunications
8—2 Telephone Systems
Historical Basis
Modern Telephone Systems and Remote Terminals
8—3 Digital Subscriber Lines (DSL)
G.DMT and G.Lite Digital Subscriber Lines
Video On Demand (VOD)
Integrated Service Digital Network (ISDN)
8—4 Capacities of Public Switched Telephone Networks
8—5 Satellite Communication Systems
Digital and Analog Television Transmission
Data and Telephone Signal Multiple Access
Satellite Radio Broadcasting
8—6 Link Budget Analysis
Signal Power Received
Thermal Noise Sources
Characterization of Noise Sources
Noise Characterization of Linear Devices
Noise Characterization of Cascaded Linear Devices
Link Budget Evaluation
Eb/N0 Link Budget for Digital Systems
Path Loss for Urban Wireless Environments
8—7 Fiber-Optic Systems
8—8 Cellular Telephone Systems
First Generation (1G)–The AMPS Analog System
Second Generation (2G)–The Digital Systems
The 1,-MHz Band PCS Systems
Status of 2G Networks
Third Generation (3G) Systems
8—9 Television
Black-and-White Television
MTS Stereo Sound
Color Television
Standards for TV and CATV Systems
Digital TV (DTV)
8—10 Cable Data Modems
8—11 Wireless Data Networks
Wi-Fi
Wi-Max
8—12 Summary
8—13 Study-Aid Examples
Problems

Appendix A Mathematical Techniques, Identities, and Tables
A—1 Trigonometry and Complex Numbers
Definitions
Trigonometric Identities and Complex Numbers
A—2 Differential Calculus
Definition
Differentiation Rules
Derivative Table
A—3 Indeterminate Forms
A—4 Integral Calculus
Definition
Integration Techniques
A—5 Integral Tables
Indefinite Integrals
Definite Integrals
A—6 Series Expansions
Finite Series
Infinite Series
A—7 Hilbert Transform Pairs
A—8 The Dirac Delta Function
Properties of Dirac Delta Functions
A—9 Tabulation of Sa(x) _ (sin x)/x
A—10 Tabulation of Q(z )

Appendix B Probability and Random Variables
B—1 Introduction
B—2 Sets
B—3 Probability and Relative Frequency
Simple Probability
Joint Probability
Conditional Probabilities
B—4 Random Variables
B—5 Cumulative Distribution Functions and Probability Density Functions
Properties of CDFs and PDFs
Discrete and Continuous Distributions
B—6 Ensemble Average and Moments
Ensemble Average
Moments
B—7 Examples of Important Distributions
Binomial Distribution
Poisson Distribution
Uniform Distribution
Gaussian Distribution
Sinusoidal Distribution
B—8 Functional Transformations of Random Variables
B—9 Multivariate Statistics
Multivariate CDFs and PDFs
Bivariate Statistics
Gaussian Bivariate Distribution
Multivariate Functional Transformation
Central Limit Theorem
Problems

Appendix C Using MATLAB
C—1 Quick Start for Running M-Files
C—2 Programming in MATLAB

References
Answers to Selected Problems
Index