Problem-Based Learning in Communication Systems Using MATLAB and Simulink E-Book

Kwonhue Choi

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Serie: IEEE Press Series on Digital & Mobile Communication
• Sprache: Englisch

Seitenzahl: 564

Veröffentlichungsjahr: 2016

Beschreibung

Designed to help teach and understand communication systems using a classroom-tested, active learning approach.

• Discusses communication concepts and algorithms, which are explained using simulation projects, accompanied by MATLAB and Simulink
• Provides step-by-step code exercises and instructions to implement execution sequences
• Includes a companion website that has MATLAB and Simulink model samples and templates (password: matlab) 

Leseprobe

IEEE Press

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Piscataway, NJ 08854

IEEE Press Editorial Board

Tariq Samad, Editor in Chief

George W. Arnold

Xiaoou Li

Ray Perez

Giancarlo Fortino

Vladimir Lumelsky

Linda Shafer

Dmitry Goldgof

Pui-In Mak

Zidong Wang

Ekram Hossain

Jeffrey Nanzer

MengChu Zhou

Kenneth Moore, Director of IEEE Book and Information Services (BIS)

Technical Reviewer

Nirwan Ansari, New Jersey Institute of Technology, USA

PROBLEM-BASED LEARNING IN COMMUNICATION SYSTEMS USING MATLAB AND SIMULINK

KWONHUE CHOI

Yeungnam University, Gyeongsan, Korea

HUAPING LIU

Oregon State University, Corvallis

Copyright © 2016 by The Institute of Electrical and Electronics Engineers, Inc.

Published by John Wiley & Sons, Inc., Hoboken, New Jersey. All rights reserved. Published simultaneously in Canada.

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Library of Congress Cataloging-in-Publication Data is available.

ISBN: 978-1-119-06034-5

CONTENTS

PREFACE

THE CHALLENGES OF LEARNING AND TEACHING COMMUNICATIONS

UNIQUE FEATURES OF THIS BOOK

THE STRUCTURE OF THIS BOOK

HOW TO EFFICIENTLY USE THIS BOOK

SUPPLEMENTS

ACKNOWLEDGMENTS

NOTATION AND LIST OF SYMBOLS

LIST OF ACRONYMS

CONTENT-MAPPING TABLE WITH MAJOR EXISTING TEXTBOOKS

PART I. COMMUNICATION SYSTEM

PART II. DIGITAL COMMUNICATION

LAB CLASS ASSIGNMENT GUIDE

ABOUT THE COMPANION WEBSITE

1 MATLAB AND SIMULINK BASICS

1.1 OPERATING ON VARIABLES AND PLOTTING GRAPHS IN MATLAB

1.2 USING SYMBOLIC MATH

1.3 CREATING AND USING A SCRIPT FILE (m-FILE)

1.4

[A]

USER-DEFINED MATLAB FUNCTION

1.5 DESIGNING A SIMPLE SIMULINK FILE

1.6 CREATING A SUBSYSTEM BLOCK

2 NUMERICAL INTEGRATION AND ORTHOGONAL EXPANSION

2.1 SIMPLE NUMERICAL INTEGRATION

2.2 ORTHOGONAL EXPANSION

REFERENCES

3 FOURIER SERIES AND FREQUENCY TRANSFER FUNCTION

3.1 DESIGNING THE EXTENDED FOURIER SERIES SYSTEM

3.2 FREQUENCY TRANSFER FUNCTION OF LINEAR SYSTEMS

3.3 VERIFICATION OF THE FREQUENCY TRANSFER FUNCTION OF LINEAR SYSTEMS IN SIMULINK

3.4 STEADY-STATE RESPONSE OF A LINEAR FILTER TO A PERIODIC INPUT SIGNAL

REFERENCES

4 FOURIER TRANSFORM

4.1 THE SPECTRUM OF SINUSOIDAL SIGNALS

4.2 THE SPECTRUM OF ANY GENERAL PERIODIC FUNCTIONS

4.3 ANALYSIS AND TEST OF THE SPECTRA OF PERIODIC FUNCTIONS

4.4 SPECTRUM OF A NONPERIODIC AUDIO SIGNAL

REFERENCES

5 CONVOLUTION

5.1 SAMPLED TIME-LIMITED FUNCTIONS

5.2 TIME-DOMAIN VIEW OF CONVOLUTION

5.3 CONVOLUTION WITH THE IMPULSE FUNCTION

5.4 FREQUENCY-DOMAIN VIEW OF CONVOLUTION

REFERENCE

6 LOW PASS FILTER AND BAND PASS FILTER DESIGN

6.1

[T]

ANALYSIS OF THE SPECTRUM OF SAMPLE AUDIO SIGNALS

6.2 LOW PASS FILTER DESIGN

6.3 LPF OPERATION

6.4

[A]

BAND PASS FILTER DESIGN

REFERENCE

7 SAMPLING AND RECONSTRUCTION

7.1 CUSTOMIZING THE

ANALOG FILTER DESIGN

BLOCK TO DESIGN AN LPF

7.2 STORING AND PLAYING SOUND DATA

7.3 SAMPLING AND SIGNAL RECONSTRUCTION SYSTEMS

7.4 FREQUENCY UP-CONVERSION WITHOUT RESORTING TO MIXING WITH A SINUSOID

REFERENCES

8 CORRELATION AND SPECTRAL DENSITY

8.1 GENERATION OF PULSE SIGNALS

8.2 CORRELATION FUNCTION

8.3 ENERGY SPECTRAL DENSITY

REFERENCES

9 AMPLITUDE MODULATION

9.1 MODULATION AND DEMODULATION OF DOUBLE SIDEBAND-SUPPRESSED CARRIER SIGNALS

9.2 EFFECTS OF THE LOCAL CARRIER PHASE AND FREQUENCY ERRORS ON DEMODULATION PERFORMANCE

9.3

[A]

DESIGN OF AN AM TRANSMITTER AND RECEIVER WITHOUT USING AN OSCILLATOR TO GENERATE THE SINUSOIDAL SIGNAL

REFERENCE

10 QUADRATURE MULTIPLEXING AND FREQUENCY DIVISION MULTIPLEXING

10.1 QUADRATURE MULTIPLEXING AND FREQUENCY DIVISION MULTIPLEXING SIGNALS AND THEIR SPECTRA

10.2 DEMODULATOR DESIGN

10.3 EFFECTS OF PHASE AND FREQUENCY ERRORS IN QM SYSTEMS

REFERENCE

11 HILBERT TRANSFORM, ANALYTIC SIGNAL, AND SSB MODULATION

11.1 HILBERT TRANSFORM, ANALYTIC SIGNAL, AND SINGLE-SIDE BAND MODULATION

11.2 GENERATION OF ANALYTIC SIGNALS USING THE HILBERT TRANSFORM

11.3 GENERATION AND SPECTRA OF ANALYTIC AND SINGLE-SIDE BAND MODULATED SIGNALS

11.4 IMPLEMENTATION OF AN SSB MODULATION AND DEMODULATION SYSTEM USING A BAND PASS FILTER

REFERENCES

12 VOLTAGE-CONTROLLED OSCILLATOR AND FREQUENCY MODULATION

12.1

[A]

IMPACT OF SIGNAL CLIPPING IN AMPLITUDE MODULATION SYSTEMS

12.2 OPERATION OF THE VOLTAGE-CONTROLLED OSCILLATOR AND ITS USE IN AN FM TRANSMITTER

12.3 IMPLEMENTATION OF NARROWBAND FM

REFERENCES

13 PHASE-LOCKED LOOP AND SYNCHRONIZATION

13.1 PHASE-LOCKED LOOP DESIGN

13.2 FM RECEIVER DESIGN USING THE PLL

13.3

[A]

DATA TRANSMISSION FROM A MOBILE PHONE TO A PC OVER THE NEAR-ULTRASONIC WIRELESS CHANNEL

REFERENCES

14 PROBABILITY AND RANDOM VARIABLES

14.1 EMPIRICAL PROBABILITY DENSITY FUNCTION OF UNIFORM RANDOM VARIABLES

14.2 THEORETICAL PDF OF GAUSSIAN RANDOM VARIABLES

14.3 EMPIRICAL PDF OF GAUSSIAN RVs

14.4 GENERATING GAUSSIAN RVs WITH ANY MEAN AND VARIANCE

14.5 VERIFYING THE MEAN AND VARIANCE OF THE RV REPRESENTED BY MATLAB FUNCTION

RANDN()

14.6 CALCULATION OF

MEAN

AND

VARIANCE

USING NUMERICAL INTEGRATION

14.7

[A]

RAYLEIGH DISTRIBUTION

REFERENCES

15 RANDOM SIGNALS

15.1 INTEGRATION OF GAUSSIAN DISTRIBUTION AND THE Q-FUNCTION

15.2 PROPERTIES OF INDEPENDENT RANDOM VARIABLES AND CHARACTERISTICS OF GAUSSIAN VARIABLES

15.3 CENTRAL LIMIT THEORY

15.4 GAUSSIAN RANDOM PROCESS AND AUTOCORRELATION FUNCTION

REFERENCES

16 MAXIMUM LIKELIHOOD DETECTION FOR BINARY TRANSMISSION

16.1 LIKELIHOOD FUNCTION AND MAXIMUM LIKELIHOOD DETECTION OVER AN ADDITIVE WHITE GAUSSIAN NOISE CHANNEL

16.2 BER SIMULATION OF BINARY COMMUNICATIONS OVER AN AWGN CHANNEL

16.3

[A]

ML DETECTION IN NON-GAUSSIAN NOISE ENVIRONMENTS

REFERENCES

17 SIGNAL VECTOR SPACE AND MAXIMUM LIKELIHOOD DETECTION I

17.1

[T]

ORTHOGONAL SIGNAL SET

17.2

[T]

MAXIMUM LIKELIHOOD DETECTION IN THE VECTOR SPACE

17.3 MATLAB CODING FOR MLD IN THE VECTOR SPACE

17.4 MLD IN THE WAVEFORM DOMAIN

REFERENCES

18 SIGNAL VECTOR SPACE AND MAXIMUM LIKELIHOOD DETECTION II

18.1 ANALYZING HOW THE RECEIVED SIGNAL SAMPLES ARE GENERATED

18.2 OBSERVING THE WAVEFORMS OF 4-ARY SYMBOLS AND THE RECEIVED SIGNAL

18.3 MAXIMUM LIKELIHOOD DETECTION IN THE VECTOR SPACE

19 CORRELATOR-BASED MAXIMUM LIKELIHOOD DETECTION

19.1 STATISTICAL CHARACTERISTICS OF ADDITIVE WHITE GAUSSIAN NOISE IN THE VECTOR SPACE

19.2 CORRELATION-BASED MAXIMUM LIKELIHOOD DETECTION

REFERENCE

20 PULSE SHAPING AND MATCHED FILTER

20.1

[T]

RAISED COSINE PULSES

20.2 PULSE SHAPING AND EYE DIAGRAM

20.3 EYE DIAGRAM AFTER MATCHED FILTERING

20.4 GENERATING AN ACTUAL ELECTRIC SIGNAL AND VIEWING THE EYE DIAGRAM IN AN OSCILLOSCOPE

REFERENCES

21 BER SIMULATION AT THE WAVEFORM LEVEL

21.1

E

B

/N

0

SETTING IN BASEBAND BPSK SIMULATION

21.2 MATCHED FILTER AND DECISION VARIABLES

21.3 COMPLETING THE LOOP FOR BER SIMULATION

21.4

[A]

EFFECTS OF THE ROLL-OFF FACTOR ON BER PERFORMANCE WHEN THERE IS A SYMBOL TIMING ERROR

21.5 PASSBAND BPSK BER SIMULATION AND EFFECTS OF CARRIER PHASE ERRORS

REFERENCE

22 QPSK AND OFFSET QPSK IN SIMULINK

22.1 CHARACTERISTICS OF QPSK SIGNALS

22.2 IMPLEMENTATION OF THE QPSK TRANSMITTER

22.3 IMPLEMENTATION OF THE QPSK RECEIVER

22.4 SNR SETTING, CONSTELLATION DIAGRAM, AND PHASE ERROR

22.5 BER SIMULATION IN SIMULINK USING A BUILT-IN FUNCTION

SIM( )

22.6 PULSE SHAPING AND INSTANTANEOUS SIGNAL AMPLITUDE

22.7 OFFSET QPSK

REFERENCES

23 QUADRATURE AMPLITUDE MODULATION IN SIMULINK

23.1 CHECKING THE BIT MAPPING OF SIMULINK QAM MODULATOR

23.2 RECEIVED QAM SIGNAL IN AWGN

23.3 DESIGN OF QAM DEMODULATOR

23.4 BER SIMULATION

23.5 OBSERVING QAM SIGNAL TRAJECTORY USING AN OSCILLOSCOPE

REFERENCES

24 CONVOLUTIONAL CODE

24.1 ENCODING ALGORITHM

24.2 IMPLEMENTATION OF MAXIMUM LIKELIHOOD DECODING BASED ON EXHAUSTIVE SEARCH

24.3 VITERBI DECODING (TRELLIS-BASED ML DECODING)

24.4 BER SIMULATION OF CODED SYSTEMS

REFERENCES

25 FADING, DIVERSITY, AND COMBINING

25.1 RAYLEIGH FADING CHANNEL MODEL AND THE AVERAGE BER

25.2 BER SIMULATION IN THE RAYLEIGH FADING ENVIRONMENT

25.3 DIVERSITY

25.4 COMBINING METHODS

REFERENCES

26 ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING IN AWGN CHANNELS

26.1 ORTHOGONAL COMPLEX SINUSOID

26.2 GENERATION OF ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING SIGNALS

26.3 BANDWIDTH EFFICIENCY OF OFDM SIGNALS

26.4 DEMODULATION OF OFDM SIGNALS

26.5 BER SIMULATION OF OFDM SYSTEMS

REFERENCES

27 ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING OVER MULTIPATH FADING CHANNELS

27.1 MULTIPATH FADING CHANNELS

27.2 GUARD INTERVAL, CP, AND CHANNEL ESTIMATION

27.3 BER SIMULATION OF OFDM SYSTEMS OVER MULTIPATH FADING CHANNELS

REFERENCES

28 MIMO SYSTEM—PART I: SPACE TIME CODE

28.1 SYSTEM MODEL

28.2 ALAMOUTI CODE

28.3 SIMPLE DETECTION OF ALAMOUTI CODE

28.4

[A]

VARIOUS STBCs, THEIR DIVERSITY ORDERS, AND THEIR RATES

REFERENCES

29 MIMO SYSTEM—PART II: SPATIAL MULTIPLEXING

29.1 MIMO FOR SPATIAL MULTIPLEXING

29.2 MLD BASED ON EXHAUSTIVE SEARCH FOR SM MIMO

29.3 ZERO FORCING DETECTION

29.4 NOISE ENHANCEMENT OF ZF DETECTION

29.5 SUCCESSIVE INTERFERENCE CANCELLATION DETECTION

29.6 BER SIMULATION OF ZF, SIC, OSIC, AND ML DETECTION SCHEMES

29.7 RELATIONSHIP AMONG THE NUMBER OF ANTENNAS, DIVERSITY, AND DATA RATE

REFERENCES

30 NEAR-ULTRASONIC WIRELESS ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING MODEM DESIGN

30.1 IMAGE FILE TRANSMISSION OVER A NEAR-ULTRASONIC WIRELESS CHANNEL

30.2 ANALYSIS OF OFDM TRANSMITTER ALGORITHMS AND THE TRANSMITTED SIGNALS

30.3 ANALYSIS OF OFDM RECEIVER ALGORITHMS AND THE RECEIVED SIGNALS

30.4 EFFECTS OF SYSTEM PARAMETERS ON THE PERFORMANCE

INDEX

IEEE PRESS SERIES ON DIGITAL AND MOBILE COMMUNICATION

EULA

List of Tables

Chapter 2

Table 2.1

Chapter 3

Table 3.1

Table 3.2

Chapter 6

Table 6.1

Chapter 7

Table 7.1

Chapter 10

Table 10.1

Chapter 11

Table 11.1

Table 11.2

Table 11.3

Table 11.4

Chapter 12

Table 12.1

Table 12.2

Table 12.3

Chapter 13

Table 13.1

Chapter 17

Table 17.1

Chapter 18

Table 18.1

Chapter 21

Table 21.1

Chapter 22

Table 22.1

Table 22.2

Chapter 23

Table 23.1

Chapter 28

Table 28.1

Table 28.2

Table 28.3

Table 28.4

Chapter 29

Table 29.1

List of Illustrations

Chapter 1

Figure 1.1

Periodic function

f

(

t

).

Figure 1.2

Adding blocks to a new design.

Figure 1.3

A test design for sine waveform generation and observation.

Figure 1.4

Design for the subsystem named

Sound Source

.

Figure 1.5

Creating a subsystem

Sound Source

.

Figure 1.6

Design for the subsystem named

Spectrum Viewer

.

Figure 1.7

Design for testing the user-defined blocks

Sound Source

and

Spectrum Viewer

.

Chapter 3

Figure 3.1

Design for a partial-sum approximation of

f

T

(

t

).

Figure 3.2

RC low pass filter.

Figure 3.3

Simulink design for RC low pass filter shown in Fig. 3.2.

Chapter 4

Figure 4.1

System to observe the spectra of sinusoids.

Figure 4.2

Periodic signal

f

T

(

t

).

Figure 4.3

System to observe the waveforms and spectra of the periodic signals.

Figure 4.4

Spectrum of a desired periodic signal.

Figure 4.5

Desired line spectrum.

Figure 4.6

System for generating a desired line spectrum.

Chapter 5

Figure 5.1

A sample function

f

1

(

t

).

Figure 5.2

A sample function

f

2

(

t

).

Chapter 6

Figure 6.1

Frequency response of an ideal band pass filter.

Chapter 7

Figure 7.1

Test system for

Analog Filter Design

block.

Figure 7.2

Test system for the subsystem

Sound Source

.

Figure 7.3

Sampling and signal reconstruction system.

Figure 7.4

Spectrum of the sound signal

x

(

t

).

Figure 7.5

Sampling signal

p

(

t

).

Figure 7.6

Simulink design of a sampling and signal reconstruction system.

Figure 7.7

Definitions of the parameters of the

Analog Filter Design

block for the BPF design.

Figure 7.8

Design of frequency up-conversion through sampling and filtering.

Chapter 9

Figure 9.1

Simulink design of a DSB-SC AM system.

Figure 9.2

AM without using the sinusoidal signal.

Chapter 10

Figure 10.1

Demodulation of QM and FDM signals.

Figure 10.2

Mono receiver for QM modulated stereo sounds.

Chapter 11

Figure 11.1

Fourier transform of

f

(

t

).

Figure 11.2

Simulink design to generate the analytic signal.

Figure 11.3

Simulink design for generating an SSB signal.

Figure 11.4

USSB modulator using a BPF and the spectra at each stage.

Figure 11.5

Simulink design for SSB signal generation with a BPF.

Chapter 12

Figure 12.1

Simulink design for AM in an additive white Gaussian noise channel.

Figure 12.2

Simulink design for an AM system in the presence of amplitude clipping.

Figure 12.3

A VCO test system.

Figure 12.4

VCO

test system II.

Figure 12.5

Simulink design for NBFM.

Figure 12.6

Simulink design for the FM system.

Chapter 13

Figure 13.1

PLL system under construction.

Figure 13.2

Closed-loop connection in the PLL.

Figure 13.3

PLL structure for the case with frequency error.

Figure 13.4

Making a subsystem PLL.

Figure 13.5

FM signal generation using a PLL.

Figure 13.6

FM system in the presence of amplitude clipping.

Figure 13.7

Demodulation of the information signal from the digitized received FM signal.

Chapter 16

Figure 16.1

Basic demodulation/detection steps.

Chapter 17

Figure 17.1

Block diagram of the two-stage MLD in a vector space.

Chapter 20

Figure 20.1

Triangular pulse

p

(

t

).

Figure 20.2

Signal

x

1

(

t

) and pulse

p

(

t

).

Figure 20.3

Signal

x

2

(

t

) and pulse

p

(

t

).

Figure 20.4

Signal

x

3

(

t

) and pulse

p

(

t

).

Figure 20.5

General signal

x

(

t

) and the pulse

p

(

t

).

Figure 20.6

Incorrect sketch of

x

(

t

) pulsed-shaped by

p

(

t

).

Figure 20.7

Audio cable after sheath removed (left) and connection to the audio out port of a PC (right).

Figure 20.8

Connection to the ground clips of two probes (left) and the connection of the stereo audio signal wires to the probes (right).

Figure 20.9

Captured oscilloscope screen.

Figure 20.10

Oscilloscope screen still cut.

Figure 20.11

Illustration of eye diagram.

Chapter 21

Figure 21.1

Noise rejection and matched filter.

Figure 21.2

PSD and signal power before and after passing through the noise rejection filter.

Chapter 22

Figure 22.1

QPSK transmitter design.

Figure 22.2

Correlation step to extract the in-phase component.

Figure 22.3

QPSK receiver design with a constellation diagram scope.

Figure 22.4

Model of the received QPSK signal over an AWGN channel.

Figure 22.5

Completed mdl/slx file for QPSK BER simulation.

Figure 22.6

Pulse-shaped QPSK system with signal trajectory and eye diagram observation blocks.

Figure 22.7

Offset QPSK transmitter.

Chapter 23

Figure 23.1

Test system for checking the 16-QAM bit mapping.

Figure 23.2

Bit mapping of the Rectangular QAM block.

Figure 23.3

Block diagram of

16QAM_AWGN

for generating the received QAM signal over an AWGN channel.

Figure 23.4

Part of the design that generates

z

1

.

Figure 23.5

Connection for the

Constellation diagram

block.

Figure 23.6

Incomplete design that detects only

b4

.

Figure 23.7

System that compares the transmitted bits with the estimated bits.

Figure 23.8

BER simulation-ready Simulink design.

Figure 23.9

Illustration of the signal trajectory observed in an oscilloscope.

Chapter 24

Figure 24.1

Convolutional code considered.

Figure 24.2

Convolutional encoder example 2.

Figure 24.3

Convolutional encoder example 3.

Figure 24.4

State diagram of the encoder in Fig. 24.1

Figure 24.5

Trellis diagram of the encoder in Fig. 24.1.

Chapter 29

Figure 29.1

Fading coefficient diagram for SM MIMO.

Chapter 30

Figure 30.1

Packet structure to transmit one image.

Guide

Cover

Table of Contents

Preface

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PREFACE

THE CHALLENGES OF LEARNING AND TEACHING COMMUNICATIONS

Many digital communication topics taught in the traditional way require understanding mathematical expressions and algorithmic procedures to learn abstract concepts. The majority of existing textbooks facilitate teaching this way with systematic and thorough explanation of communication theories and concepts, mainly via mathematical models and algorithmic procedures. This is the natural outcome when computers and software were not so universally accessible decades ago as they are today. However, most students find such a way of learning digital communications ineffective and often frustrating. And even if they are able to follow the instructors in the classroom, their understanding of the concepts is often superficial. The accessibility of powerful software like MATLAB/Simulink and the Internet to students could be exploited to revolutionize the teaching of math intensive subjects such as digital communications. Through decades of classroom experience, we have learned that students' learning becomes significantly more effective if they are led to “construct” the system themselves and observe waveforms and statistics at various stages of the system or algorithm, a process called “active” learning here.

However, given the tools and texts available on the market to the instructors, implementing this active learning process is by no means easy. First, the majority of the textbooks are optimized for instruction in the traditional way. Some recent textbooks provide problems that involve the use of MATLAB/Simulink or similar software and codes or computer models to perform certain simulation. Readers can replicate these codes/models and conduct simulation, which would certainly reinforce some aspects they have learned. Such an approach is still far short of encouraging active learning by students. Second, there are some existing hardware training kits designed for educational purposes that can be used for labs/experiments of communications classes. However, these training kits are often expensive and cover only a limited number of topics of communications. Additionally, students need to learn hardware design skills such as DSP programming and VHDL to be able to use such a tool.

UNIQUE FEATURES OF THIS BOOK

This book is written to encourage active learning of communication theories and systems by its readers. Toward this goal, major communication concepts and algorithms are examined through carefully designed MATLAB/Simulink projects. Each project implements the simulation construction and execution steps or sequences that match how an actual communications system or algorithm works. These steps progressively explore the intermediate results between steps that students can “see” and comprehend what happens behind theories and mathematical expressions. The bulk of MATLAB simulation codes or Simulink models for these projects are provided. This ensures that students will be able to complete even complex projects such as Viterbi decoding, multiple-input multiple-output (MIMO) detection, and orthogonal frequency division multiplexing (OFDM) demodulation.

However, important parameters and codes lines or model blocks that are critical for learning the algorithm or communications process are left out for students to complete. This makes mechanically executing a certain completed code without understanding the technical details impossible. Step-by-step instructions are designed for each problem. Readers can conveniently check the results of each intermediate step and compare the various parameter choices and their effects and are thus led to actively figure out the intended answers and build up a complete system/algorithm.

Summarizing it, this book is written with the following three main goals in mind:

The framework of the codes/models provided in the book efficiently guides students through the simulation and actively engages students in learning the materials.

The codes/blocks provided minimize the amount of time students need to complete their simulations and ensure that they will be able to complete even complex projects without getting lost in the middle and giving up.

In completing the main algorithm/concept-specific incomplete parts, students will effectively be internalizing the theories.

In Chapters 4, 7, 9, 10, 11, 13, 20, 22, 23, and 30, students will learn how to convert constructed waveforms in simulations into electric signals and then to listen to those signals if they are audio signals, or observe the eye-patterns, scatter plots, or signal trajectories by using an oscilloscope for digitally modulated signals. In Chapters 13 and 30, students are encouraged to complete actual wireless communications in the band near-ultrasonic frequencies, requiring only a mobile phone and a PC with a microphone. We have found that all such present-day projects that embrace student interests can motivate them to explore more intensely how communication systems work.

Although, students are not required to know MATLAB/Simulink to use this book, Chapter 1 provides carefully designed projects that enable students to self-learn the MATLAB/Simulink skills needed for the rest of the projects in this book. All that a student needs are access to MATLAB, a headphone and an oscilloscope for some projects.

THE STRUCTURE OF THIS BOOK

The 30 chapters of this book cover MATLAB/Simulink basics (Chapter 1), basic signals and systems (Chapters 2–8), analog communications (Chapters 9–13), probability and random signals (Chapters 14–15), basics of digital communication techniques (Chapters 16–24), and wireless communication techniques (Chapters 25–30).

The majority of these chapters are structured as follows.

Aims:

Summarize the topics and goals of the chapter.

Prelab:

The theoretical background for the topic, if necessary; prerequisite problem sets for students to become familiar with the required MATLAB functions and features for the chapter.

Main lab:

Problems for the main topic.

Further studies:

Problems for advanced topics, if there are any.

A user's guide is provided at the beginning of the book, where the problem numbers corresponding to the prelab, main lab, and further studies of all chapters are tabulated.

To minimize the time students would otherwise have to spend on nonessential (in terms of learning core concepts and algorithms) but necessary and time-consuming tasks, MATLAB code script (incomplete m-files), Simulink models (incomplete .mdl/.slx files), and data files (.mat files) are provided so that students can easily access the core materials.

HOW TO EFFICIENTLY USE THIS BOOK

Teaching with this book:

As a supplementary textbook (mainly for assigning labs and projects) for undergraduate- and junior-level graduate communications and wireless communications classes as well as undergraduate signal and systems classes. A content-mapping table of the sections of this book with the sections of four widely adopted existing textbooks that cover essentially the same materials is provided.

As the main textbook for the aforementioned courses. While this book is not written to compete with existing communications theory and system textbooks, it is all-inclusive in that it covers, all major topics of communications.

With option 1, instructors can conveniently make lab assignments using the content-mapping table to choose appropriate projects from this book to reinforce student's learning experience. Because the projects in this book are designed to guide students step by step toward more complex projects, instructors need only spend minimal time and effort to cover all the material in class.

With option 2, instructors can use their own lecture notes to summarize the theory parts of the chapters/sections of this book that they plan to teach in class. For graduate classes, such class presentations may not be needed, since graduate students should be able to search for additional information, if needed. Students should nevertheless follow through the projects and write reports.

These uses of the book will reduce the amount of work that the instructors need to put into the class presentations, but the students still gain a thorough understanding of each concept through active learning. Instructors can customize the different chapters for different courses. For example, when this book is used for an undergraduate signals and systems class, Chapters 1–7 would be ideal, plus some materials on z-transform (for most curricula, students should have learned Laplace transform before taking signals and systems). In the first two to three weeks, students could complete Chapter 1 by themselves while the instructor focuses on basic signals and system properties. When the instructor is ready to start teaching signals and systems in both time and frequency domains, filter design, and sampling and reconstruction, students will then have all the MATLAB/Simulink skills needed to work on the corresponding projects. For an analog communications class, Chapters 1 and 8–13 should be covered. For a junior-level digital communications course, Chapters 1 and 14–24 may be covered. For a junior-level graduate wireless communications course (provided that students have taken digital communications), some or all of Chapters 1 and 25–30 can be covered.

SUPPLEMENTS

The following supplements are available from the companion website:

All MATLAB code or Simulink model samples and templates (incomplete m-files and incomplete .mdl/.slx models) and data files (.mat files).

Correction table for each edition if found.

Content-mapping table of the sections of this book with the sections of widely adopted existing textbooks if updated.

ACKNOWLEDGMENTS

This book has gone through many revisions over the past 12 years to make it a useful tool for instructors and effective guide for students learning communications systems. The writing of the book would have been impossible without the tremendous help from many of our colleagues and students. In particular, we thank Dr. Bong-seok Kim for checking every technical detail and Ms. Sahar Amini for proofreading the manuscript.

Our editor, Mary Hatcher, has very competently steered us through this project. We especially appreciate her steadfast support of our book and patience in guiding us through the publication process.

Huaping Liu is also extremely grateful to his wife Catherine and sons Frank, Ethan, Raymond, and Andrew for their endurance and not making demands on his time during the writing of this book. He also offers special thanks to two of his sons, Ethan and Raymond, for giving him many useful writing tips and for helping him revise the writing of chapters.

NOTATION AND LIST OF SYMBOLS

[WWW]: Sections or problems that require a data file or problems for which a script-file (m-file) is provided from the companion website (

http://www.wiley.com/go/choi_problembasedlearning

).

[T]: Theory-based sections or problems that do not require MATLAB or Simulink.

[A]: Advanced problems or materials.

m-file: MATLAB script-files

Terms using this style and font

:

MATLAB/Simulink-related terms, for example, variable/parameter/function/block/file name.

LIST OF ACRONYMS

AM

amplitude modulation

AWGN

additive white Gaussian noise

BER

bit error rate

CLT

central limit theory

CNR

carrier-to-noise ratio

CP

cyclic prefix

CSI

channel state information

DSB-LC

double side-band with a large carrier

DSB-SC

double side-band-suppressed carrier

EGC

equal gain combining

ESD

energy spectral density

FDM

frequency division multiplexing

ICI

inter-carrier interference

IFFT

inverse Fast Fourier transform

ISI

inter-symbol interference

LSSB

lower single-side band

MIMO

multiple input multiple output

ML

maximum likelihood

MLD

maximum likelihood detection (or decoding)

MPSK

M-ary phase shift keying

MRC

maximum ratio combining

NBFM

narrowband FM

NUS

near ultrasonic

OFDM

orthogonal frequency division multiplexing

OQPSK

offset QPSK

OSIC

ordered successive interference cancellation

PAM

pulse amplitude modulation

PD

phase detector

PDF

probability density function

PLL

phase locked loop

PSD

power spectral density

QAM

quadrature amplitude modulation

QM

quadrature multiplexing

QPSK

quadrature phase shift keying

SD

spatial diversity

SDC

selection diversity combining

SIC

successive interference cancellation

SM

spatial multiplexing

SRRC

square-root raised cosine

SSB

single-side band

STBC

space time block code

USSB

upper single-side band

VCO

voltage controlled oscillator

WSS

wide-sense stationary

ZF

zero forcing

CONTENT-MAPPING TABLE WITH MAJOR EXISTING TEXTBOOKS

NOTE: Mapping table for newer versions of the major textbooks will be updated on the companion website.

PART I. COMMUNICATION SYSTEM

Corresponding Sections of Widely Adopted Existing Textbooks

Chapter

Introduction to Communication Systems

by Ferrell G. Stremler, 3rd ed. Addison Wesley, 1990.

Introduction to Analog and Digital Communication

by S. Haykin and M. Moher, 2nd ed. John Wiley & Sons, 2007

 2

2.5∼2.7

–

 3

2.12, 2.13, 2.15, 3.3, 3.9

2.1∼2.3, 2.5

 4

3.2, 3.5, 3.6, 3.15, 3.17

2.6

 5

3.5∼3.9

2.3

 6

2.19, 3.11∼3.13

2.7

 7

3.15, 3.16

5.1∼5.2

 8

4.1∼4.7.1

2.8

 9

5.1, 5.2

3.1∼3.3

10

5.3

3.5, 3.9

11

5.4

3.6, 3.8

12

6.1, 6.2

4.1∼4.2, 4.4

13

6.7.2, 6.7.3

4.8

PART II. DIGITAL COMMUNICATION

Corresponding Sections of Widely Adopted Existing Textbooks

Chapter

Digital Communications: Fundamentals and Applications

by B. Sklar, 2nd ed. PHIPE, 2002

Digital Communications

by J. G. Proakis, 5th ed. McGraw-Hill, 2008

14

1.1∼1.5

2.3

15

1.4∼1.5.5

2.3, 2.7-1

16

3.1∼3.2.1

2.3, 4.2-1

17, 18

3.1.3, 3.2.5.3, 4.2.6, 4.3.1

4.2, 5.1∼5.1-1

19

4.3.2

2.2, 2.3, 4.2-2

20

3.2.3, 3.4.2

9.2∼9.2-3

21

4.1∼4.4.2, 4.7.1

3.2-2, 4.2-2

22

4.4.3∼4.8.3, 9.8.1, 9.8.2.1

3.2-2, page 124 (OQPSK)

23

9.8.3, 9.5.1

3.2-3

24

7.1∼7.4

8.1∼8.1-1, 8.2∼8.2-1, 8.3, 8.4

25

15.5.4

13.1, 13.4

26

11.2, 13.6

27

11.2, 13.6

28

15.4

29

15.1∼15.2

30

11.2, 13.6