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)
Autorentext
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.
Inhalt
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 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 …