Solution Manual for Digital and Analog Communication Systems 8th Edition by Couch

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 3BASEBAND 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 4BANDPASS 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 5AM, 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 6RANDOM 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 7PERFORMANCE 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 8WIRE 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/N0Link 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 ofSa(x) _ (sinx)/x

A—10 Tabulation ofQ(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