Details

Problem-Based Learning in Communication Systems Using MATLAB and Simulink


Problem-Based Learning in Communication Systems Using MATLAB and Simulink


IEEE Series on Digital & Mobile Communication 1. Aufl.

von: Kwonhue Choi, Huaping Liu

108,99 €

Verlag: Wiley-IEEE Press
Format: PDF
Veröffentl.: 10.02.2016
ISBN/EAN: 9781119060277
Sprache: englisch
Anzahl Seiten: 400

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

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   
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
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.
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.

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