Problem-Based Learning in Communication Systems Using MATLAB and Simulink

ISBN-13: 9781119060345 / Angielski / Twarda / 2016 / 400 str.

Choi, Kwonhue; Liu, Huaping

Opis

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

Spis treści

Preface xiii

Acknowledgments xvii

Notation and List of Symbols xix

List of Acronyms xxi

Content–Mapping Table with Major Existing Textbooks xxiii

Lab Class Assignment Guide xxv

About the Companion Website xxvii

1 MATLAB and Simulink Basics 1

1.1 Operating on Variables and Plotting Graphs in MATLAB, 1

1.2 Using Symbolic Math, 3

1.3 Creating and Using a Script File (m–File), 4

1.4 [A]User–Defined MATLAB Function, 7

1.5 Designing a Simple Simulink File, 8

1.6 Creating a Subsystem Block, 12

2 Numerical Integration and Orthogonal Expansion 16

2.1 Simple Numerical Integration, 16

2.2 Orthogonal Expansion, 18

References, 23

3 Fourier Series and Frequency Transfer Function 24

3.1 Designing the Extended Fourier Series System, 24

3.2 Frequency Transfer Function of Linear Systems, 25

3.3 Verification of the Frequency Transfer Function of Linear Systems in Simulink, 27

3.4 Steady–State Response of a Linear Filter to a Periodic Input Signal, 29

References, 31

4 Fourier Transform 33

4.1 The Spectrum of Sinusoidal Signals, 33

4.2 The Spectrum of Any General Periodic Functions, 36

4.3 Analysis and Test of the Spectra of Periodic Functions, 37

4.4 Spectrum of a Nonperiodic Audio Signal, 40

References, 44

5 Convolution 45

5.1 Sampled Time–Limited Functions, 45

5.2 Time–Domain View of Convolution, 48

5.3 Convolution with the Impulse Function, 50

5.4 Frequency–Domain View of Convolution, 51

Reference, 54

6 Low Pass Filter and Band Pass Filter Design 55

6.1 [T]Analysis of the Spectrum of Sample Audio Signals, 55

6.2 Low Pass Filter Design, 57

6.3 LPF Operation, 61

6.4 [A]Band Pass Filter Design, 63

Reference, 65

7 Sampling and Reconstruction 66

7.1 Customizing the Analog Filter Design Block to Design an LPF, 66

7.2 Storing and Playing Sound Data, 67

7.3 Sampling and Signal Reconstruction Systems, 68

7.4 Frequency Up–Conversion without Resorting to Mixing with a Sinusoid, 75

References, 77

8 Correlation and Spectral Density 78

8.1 Generation of Pulse Signals, 78

8.2 Correlation Function, 79

8.3 Energy Spectral Density, 87

References, 89

9 Amplitude Modulation 90

9.1 Modulation and Demodulation of Double Sideband–Suppressed Carrier Signals, 90

9.2 Effects of the Local Carrier Phase and Frequency Errors on Demodulation Performance, 95

9.3 [A]Design of an AM Transmitter and Receiver without Using an Oscillator to Generate the Sinusoidal Signal, 98

Reference, 100

10 Quadrature Multiplexing and Frequency Division Multiplexing 101

10.1 Quadrature Multiplexing and Frequency Division Multiplexing Signals and Their Spectra, 101

10.2 Demodulator Design, 104

10.3 Effects of Phase and Frequency Errors in QM Systems, 105

Reference, 108

11 Hilbert Transform, Analytic Signal, and SSB Modulation 109

11.1 Hilbert Transform, Analytic Signal, and Single–Side Band Modulation, 109

11.2 Generation of Analytic Signals Using the Hilbert Transform, 111

11.3 Generation and Spectra of Analytic and Single–Side Band Modulated Signals, 114

11.4 Implementation of an SSB Modulation and Demodulation System Using a Band Pass Filter, 117

References, 122

12 Voltage–Controlled Oscillator and Frequency Modulation 123

12.1 [A]Impact of Signal Clipping in Amplitude Modulation Systems, 123

12.2 Operation of the Voltage–Controlled Oscillator and Its Use in an FM Transmitter, 126

12.3 Implementation of Narrowband FM, 130

References, 134

13 Phase–Locked Loop and Synchronization 135

13.1 Phase–Locked Loop Design, 135

13.2 FM Receiver Design Using the PLL, 142

13.3 [A]Data Transmission from a Mobile Phone to a PC over the Near–Ultrasonic Wireless Channel, 146

References, 89

9 Amplitude Modulation 90

9.1 Modulation and Demodulation of Double Sideband–Suppressed Carrier Signals, 90

9.2 Effects of the Local Carrier Phase and Frequency Errors on Demodulation Performance, 95

9.3 [A]Design of an AM Transmitter and Receiver without Using an

Oscillator to Generate the Sinusoidal Signal, 98

Reference, 100

10 Quadrature Multiplexing and Frequency Division Multiplexing 101

10.1 Quadrature Multiplexing and Frequency Division Multiplexing Signals and Their Spectra, 101

10.2 Demodulator Design, 104

10.3 Effects of Phase and Frequency Errors in QM Systems, 105

Reference, 108

11 Hilbert Transform, Analytic Signal, and SSB Modulation 109

11.1 Hilbert Transform, Analytic Signal, and Single–Side Band Modulation, 109

11.2 Generation of Analytic Signals Using the Hilbert Transform, 111

11.3 Generation and Spectra of Analytic and Single–Side Band Modulated Signals, 114

11.4 Implementation of an SSB Modulation and Demodulation System Using a Band Pass Filter, 117

References, 122

12 Voltage–Controlled Oscillator and Frequency Modulation 123

12.1 [A]Impact of Signal Clipping in Amplitude Modulation Systems, 123

12.2 Operation of the Voltage–Controlled Oscillator and Its Use in an FM Transmitter, 126

12.3 Implementation of Narrowband FM, 130

References, 134

13 Phase–Locked Loop and Synchronization 135

13.1 Phase–Locked Loop Design, 135

13.2 FM Receiver Design Using the PLL, 142

13.3 [A]Data Transmission from a Mobile Phone to a PC over the Near–Ultrasonic Wireless Channel, 146

References, 150

14 Probability and Random Variables 151

14.1 Empirical Probability Density Function of Uniform Random Variables, 151

14.2 Theoretical PDF of Gaussian Random Variables, 152

14.3 Empirical PDF of Gaussian RVs, 153

14.4 Generating Gaussian RVs with Any Mean and Variance, 155

14.5 Verifying the Mean and Variance of the RV Represented by MATLAB Function randn(), 155

14.6 Calculation of Mean and Variance Using Numerical Integration, 156

14.7 [A]Rayleigh Distribution, 158

References, 159

15 Random Signals 160

15.1 Integration of Gaussian Distribution and the Q–Function, 160

15.2 Properties of Independent Random Variables and Characteristics of Gaussian Variables, 162

15.3 Central Limit Theory, 165

15.4 Gaussian Random Process and Autocorrelation Function, 168

References, 173

16 Maximum Likelihood Detection for Binary Transmission 174

16.1 Likelihood Function and Maximum Likelihood Detection over an Additive White Gaussian Noise Channel, 174

16.2 BER Simulation of Binary Communications over an AWGN Channel, 178

16.3 [A]ML Detection in Non–Gaussian Noise Environments, 182

References, 183

17 Signal Vector Space and Maximum Likelihood Detection I 184

17.1 [T]Orthogonal Signal Set, 184

17.2 [T]Maximum Likelihood Detection in the Vector Space, 185

17.3 MATLAB Coding for MLD in the Vector Space, 187

17.4 MLD in the Waveform Domain, 189

References, 191

18 Signal Vector Space and Maximum Likelihood Detection II 192

18.1 Analyzing How the Received Signal Samples Are Generated, 192

18.2 Observing the Waveforms of 4–Ary Symbols and the Received Signal, 195

18.3 Maximum Likelihood Detection in the Vector Space, 196

19 Correlator–Based Maximum Likelihood Detection 200

19.1 Statistical Characteristics of Additive White Gaussian Noise in the Vector Space, 200

19.2 Correlation–Based Maximum Likelihood Detection, 205

Reference, 208

20 Pulse Shaping and Matched Filter 209

20.1 [T]Raised Cosine Pulses, 209

20.2 Pulse Shaping and Eye Diagram, 210

20.3 Eye Diagram after Matched Filtering, 216

20.4 Generating an Actual Electric Signal and Viewing the Eye Diagram in an Oscilloscope, 218

References, 223

21 BER Simulation at theWaveform Level 224

21.1 EB/N0 Setting in Baseband BPSK Simulation, 224

21.2 Matched Filter and Decision Variables, 228

21.3 Completing the Loop for BER Simulation, 230

21.4 [A]Effects of the Roll–off Factor on BER Performance When There Is a Symbol Timing Error, 234

21.5 Passband BPSK BER Simulation and Effects of Carrier Phase Errors, 235

Reference, 238

22 QPSK and Offset QPSK in Simulink 239

22.1 Characteristics of QPSK Signals, 239

22.2 Implementation of the QPSK Transmitter, 241

22.3 Implementation of the QPSK Receiver, 243

22.4 SNR Setting, Constellation Diagram, and Phase Error, 245

22.5 BER Simulation in Simulink Using a Built–in Function sim( ), 247

22.6 Pulse Shaping and Instantaneous Signal Amplitude, 249

22.7 Offset QPSK, 252

References, 253

23 Quadrature Amplitude Modulation in Simulink 254

23.1 Checking the Bit Mapping of Simulink QAM Modulator, 254

23.2 Received QAM Signal in AWGN, 258

23.3 Design of QAM Demodulator, 260

23.4 BER Simulation, 262

23.5 Observing QAM Signal Trajectory Using an Oscilloscope, 266

References, 268

24 Convolutional Code 269

24.1 Encoding Algorithm, 269

24.2 Implementation of Maximum Likelihood Decoding Based on

Exhaustive Search, 273

24.3 Viterbi Decoding (Trellis–Based ML Decoding), 277

24.4 BER Simulation of Coded Systems, 284

References, 287

25 Fading, Diversity, and Combining 289

25.1 Rayleigh Fading Channel Model and the Average BER, 289

25.2 BER Simulation in the Rayleigh Fading Environment, 292

25.3 Diversity, 295

25.4 Combining Methods, 296

References, 300

26 Orthogonal Frequency Division Multiplexing in AWGN Channels 302

26.1 Orthogonal Complex Sinusoid, 302

26.2 Generation of Orthogonal Frequency Division Multiplexing Signals, 303

26.3 Bandwidth Efficiency of OFDM Signals, 306

26.4 Demodulation of OFDM Signals, 307

26.5 BER Simulation of OFDM Systems, 307

References, 310

27 Orthogonal Frequency Division Multiplexing over Multipath Fading Channels 311

27.1 Multipath Fading Channels, 311

27.2 Guard Interval, CP, and Channel Estimation, 314

27.3 BER Simulation of OFDM Systems over Multipath Fading Channels, 319

References, 323

28 MIMO System Part I: Space Time Code 324

28.1 System Model, 324

28.2 Alamouti Code, 327

28.3 Simple Detection of Alamouti Code, 330

28.4 [A]Various STBCs, Their Diversity Orders, and Their Rates, 334

References, 335

29 MIMO System Part II: Spatial Multiplexing 336

29.1 MIMO for Spatial Multiplexing, 336

29.2 MLD Based on Exhaustive Search for SM MIMO, 337

29.3 Zero Forcing Detection, 340

29.4 Noise Enhancement of ZF Detection, 341

29.5 Successive Interference Cancellation Detection, 343

29.6 BER Simulation of ZF, SIC, OSIC, and ML Detection Schemes, 347

29.7 Relationship among the Number of Antennas, Diversity, and Data Rate, 350

References, 352

30 Near–Ultrasonic Wireless Orthogonal Frequency Division Multiplexing Modem Design 353

30.1 Image File Transmission over a Near–Ultrasonic Wireless Channel, 353

30.2 Analysis of OFDM Transmitter Algorithms and the Transmitted Signals, 355

30.3 Analysis of OFDM Receiver Algorithms and the Received Signals, 357

30.4 Effects of System Parameters on the Performance, 361

Index 363

O autorze

Kwonhue Choi is a Professor in the Department of Information and Communication Engineering and the Principal Director of Broadband Wireless Communication (BWC) Laboratory at Yeungnam University, Korea. His research areas include efficient multiple access, diversity schemes, and cooperative communications for Fifth–Generation (5G) and beyond systems. He is the inventor of FADAC–OFDM and PSW (Properly scrambled Walsh) codes.

Huaping Liu is a Professor with the School of Electrical Engineering and Computer Science at Oregon State University, USA. He was formerly a cellular network radio frequency systems engineer specializing on modeling, simulating, optimizing, and testing various digital communication systems. Dr. Liu received his PhD in Electrical Engineering at New Jersey Institute of Technology, USA.

Blurb

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

This book covers the basic concepts of signals, and analog and digital communications, to more complex simulations in communication systems.  Problem–Based Learning in Communication Systems Using MATLAB and Simulink begins by introducing MATLAB and Simulink to prepare readers who are unfamiliar with these environments in order to tackle projects and exercises included in this book. Discussions on simulation of signals, filter design, sampling and reconstruction, and analog communications are covered next. The book concludes by covering advanced topics such as Viterbi decoding, OFDM and MIMO. In addition, this book contains examples of how to convert waveforms, constructed in simulation, into electric signals. It also includes problems illustrating how to complete actual wireless communications in the band near ultrasonic frequencies.

A content–mapping table is included in this book to help instructors easily find lab projects for communications, wireless communications, and signal and systems classes.   

Special features of this book: 

• 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 (link provided below)

This book is intended for students and instructors, enrolled in or teaching communications systems, analog and digital communications, and wireless communication courses.

Kwonhue Choi is a Professor in the Department of Information and Communication Engineering and the Principal Director of Broadband Wireless Communication (BWC) Laboratory at Yeungnam University, Korea. His research areas include efficient multiple access, diversity schemes, and cooperative communications for Fifth–Generation (5G) and beyond systems. He is the inventor of FADAC–OFDM and PSW (Properly scrambled Walsh) codes.

Huaping Liu is a Professor with the School of Electrical Engineering and Computer Science at Oregon State University, USA. He was formerly a cellular network radio frequency systems engineer specializing on modeling, simulating, optimizing, and testing various digital communication systems. Dr. Liu received his PhD in Electrical Engineering at New Jersey Institute of Technology, USA.