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

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Problem-Based Learning in Communication Systems Using MATLAB and SimulinkSuurem pilt
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This book is designed for students, as well as engineers to learn communication theories and systems through active learning, rather than the traditional way of passive learning.  All communication concepts and algorithms are explained using simulation projects (Matlab/Simulink).  For each topic, a summary of the theory/algorithm is provided first, followed by many simulation examples and projects. These projects aim to enable readers to see how each abstract algorithm works, such as algorithm execution sequence.  Step-by-step code-construction instructions where readers can check the results of each intermediate step and compare the various parameter choices and their effects are provided.  Consequently, readers are led to build up the algorithms in simulation themselves, all while gaining a thorough understanding of the concepts.

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(15)
1.1 Operating on Variables and Plotting Graphs in Matlab
1(2)
1.2 Using Symbolic Math
3(1)
1.3 Creating and Using a Script File (m-File)
4(3)
1.4 [ A]User-Defined Matlab Function
7(1)
1.5 Designing a Simple Simulink File
8(4)
1.6 Creating a Subsystem Block
12(4)
2 Numerical Integration and Orthogonal Expansion
16(8)
2.1 Simple Numerical Integration
16(2)
2.2 Orthogonal Expansion
18(6)
References
23(1)
3 Fourier Series and Frequency Transfer Function
24(9)
3.1 Designing the Extended Fourier Series System
24(1)
3.2 Frequency Transfer Function of Linear Systems
25(2)
3.3 Verification of the Frequency Transfer Function of Linear Systems in Simulink
27(2)
3.4 Steady-State Response of a Linear Filter to a Periodic Input Signal
29(4)
References
31(2)
4 Fourier Transform
33(12)
4.1 The Spectrum of Sinusoidal Signals
33(3)
4.2 The Spectrum of Any General Periodic Functions
36(1)
4.3 Analysis and Test of the Spectra of Periodic Functions
37(3)
4.4 Spectrum of a Nonperiodic Audio Signal
40(5)
References
44(1)
5 Convolution
45(10)
5.1 Sampled Time-Limited Functions
45(3)
5.2 Time-Domain View of Convolution
48(2)
5.3 Convolution with the Impulse Function
50(1)
5.4 Frequency-Domain View of Convolution
51(4)
Reference
54(1)
6 Low Pass Filter and Band Pass Filter Design
55(11)
6.1 [ T] Analysis of the Spectrum of Sample Audio Signals
55(2)
6.2 Low Pass Filter Design
57(4)
6.3 LPF Operation
61(2)
6.4 [ A] Band Pass Filter Design
63(3)
Reference
65(1)
7 Sampling and Reconstruction
66(12)
7.1 Customizing the Analog Filter Design Block to Design an LPF
66(1)
7.2 Storing and Playing Sound Data
67(1)
7.3 Sampling and Signal Reconstruction Systems
68(7)
7.4 Frequency Up-Conversion without Resorting to Mixing with a Sinusoid
75(3)
References
77(1)
8 Correlation and Spectral Density
78(12)
8.1 Generation of Pulse Signals
78(1)
8.2 Correlation Function
79(8)
8.3 Energy Spectral Density
87(3)
References
89(1)
9 Amplitude Modulation
90(11)
9.1 Modulation and Demodulation of Double Sideband-Suppressed Carrier Signals
90(5)
9.2 Effects of the Local Carrier Phase and Frequency Errors on Demodulation Performance
95(3)
9.3 `Design of an AM Transmitter and Receiver without Using an Oscillator to Generate the Sinusoidal Signal
98(3)
Reference
100(1)
10 Quadrature Multiplexing and Frequency Division Multiplexing
101(8)
10.1 Quadrature Multiplexing and Frequency Division Multiplexing Signals and Their Spectra
101(3)
10.2 Demodulator Design
104(1)
10.3 Effects of Phase and Frequency Errors in QM Systems
105(4)
Reference
108(1)
11 Hilbert Transform, Analytic Signal, and SSB Modulation
109(14)
11.1 Hilbert Transform, Analytic Signal, and Single-Side Band Modulation
109(2)
11.2 Generation of Analytic Signals Using the Hilbert Transform
111(3)
11.3 Generation and Spectra of Analytic and Single-Side Band Modulated Signals
114(3)
11.4 Implementation of an SSB Modulation and Demodulation System Using a Band Pass Filter
117(6)
References
122(1)
12 Voltage-Controlled Oscillator and Frequency Modulation
123(12)
12.1 [ A] Impact of Signal Clipping in Amplitude Modulation Systems
123(3)
12.2 Operation of the Voltage-Controlled Oscillator and Its Use in an FM Transmitter
126(4)
12.3 Implementation of Narrowband FM
130(5)
References
134(1)
13 Phase-Locked Loop and Synchronization
135(16)
13.1 Phase-Locked Loop Design
135(7)
13.2 FM Receiver Design Using the PLL
142(4)
13.3 [ A]Data Transmission from a Mobile Phone to a PC over the Near-Ultrasonic Wireless Channel
146(5)
References
150(1)
14 Probability and Random Variables
151(9)
14.1 Empirical Probability Density Function of Uniform Random Variables
151(1)
14.2 Theoretical PDF of Gaussian Random Variables
152(1)
14.3 Empirical PDF of Gaussian RVs
153(2)
14.4 Generating Gaussian RVs with Any Mean and Variance
155(1)
14.5 Verifying the Mean and Variance of the RV Represented by Matlab Function randn()
155(1)
14.6 Calculation of Mean and Variance Using Numerical Integration
156(2)
14.7 [ A]Rayleigh Distribution
158(2)
References
159(1)
15 Random Signals
160(14)
15.1 Integration of Gaussian Distribution and the Q-Function
160(2)
15.2 Properties of Independent Random Variables and Characteristics of Gaussian Variables
162(3)
15.3 Central Limit Theory
165(3)
15.4 Gaussian Random Process and Autocorrelation Function
168(6)
References
173(1)
16 Maximum Likelihood Detection for Binary Transmission
174(10)
16.1 Likelihood Function and Maximum Likelihood Detection over an Additive White Gaussian Noise Channel
174(4)
16.2 BER Simulation of Binary Communications over an AWGN Channel
178(4)
16.3 [ AML Detection in Non-Gaussian Noise Environments
182(2)
References
183(1)
17 Signal Vector Space and Maximum Likelihood Detection I
184(8)
17.1 [ T]Orthogonal Signal Set
184(1)
17.2 Maximum Likelihood Detection in the Vector Space
185(2)
17.3 Matlab Coding for MLD in the Vector Space
187(2)
17.4 MLD in the Waveform Domain
189(3)
References
191(1)
18 Signal Vector Space and Maximum Likelihood Detection II
192(8)
18.1 Analyzing How the Received Signal Samples Are Generated
192(3)
18.2 Observing the Waveforms of 4-Ary Symbols and the Received Signal
195(1)
18.3 Maximum Likelihood Detection in the Vector Space
196(4)
19 Correlator-Based Maximum Likelihood Detection
200(9)
19.1 Statistical Characteristics of Additive White Gaussian Noise in the Vector Space
200(5)
19.2 Correlation-Based Maximum Likelihood Detection
205(4)
Reference
208(1)
20 Pulse Shaping and Matched Filter
209(15)
20.1 [ T]Raised Cosine Pulses
209(1)
20.2 Pulse Shaping and Eye Diagram
210(6)
20.3 Eye Diagram after Matched Filtering
216(2)
20.4 Generating an Actual Electric Signal and Viewing the Eye Diagram in an Oscilloscope
218(6)
References
223(1)
21 BER Simulation at the Waveform Level
224(15)
21.1 EB/No Setting in Baseband BPSK Simulation
224(4)
21.2 Matched Filter and Decision Variables
228(2)
21.3 Completing the Loop for BER Simulation
230(4)
21.4 [ A]Effects of the Roll-off Factor on BER Performance When There Is a Symbol Timing Error
234(1)
21.5 Passband BPSK BER Simulation and Effects of Carrier Phase Errors
235(4)
Reference
238(1)
22 QPSK and Offset QPSK in Simulink
239(15)
22.1 Characteristics of QPSK Signals
239(2)
22.2 Implementation of the QPSK Transmitter
241(2)
22.3 Implementation of the QPSK Receiver
243(2)
22.4 SNR Setting, Constellation Diagram, and Phase Error
245(2)
22.5 BER Simulation in Simulink Using a Built-in Function sim()
247(2)
22.6 Pulse Shaping and Instantaneous Signal Amplitude
249(3)
22.7 Offset QPSK
252(2)
References
253(1)
23 Quadrature Amplitude Modulation in Simulink
254(15)
23.1 Checking the Bit Mapping of Simulink QAM Modulator
254(4)
23.2 Received QAM Signal in AWGN
258(2)
23.3 Design of QAM Demodulator
260(2)
23.4 BER Simulation
262(4)
23.5 Observing QAM Signal Trajectory Using an Oscilloscope
266(3)
References
268(1)
24 Convolutional Code
269(20)
24.1 Encoding Algorithm
269(4)
24.2 Implementation of Maximum Likelihood Decoding Based on Exhaustive Search
273(4)
24.3 Viterbi Decoding (Trellis-Based ML Decoding)
277(7)
24.4 BER Simulation of Coded Systems
284(5)
References
287(2)
25 Fading, Diversity, and Combining
289(13)
25.1 Rayleigh Fading Channel Model and the Average BER
289(3)
25.2 BER Simulation in the Rayleigh Fading Environment
292(3)
25.3 Diversity
295(1)
25.4 Combining Methods
296(6)
References
300(2)
26 Orthogonal Frequency Division Multiplexing in AWGN Channels
302(9)
26.1 Orthogonal Complex Sinusoid
302(1)
26.2 Generation of Orthogonal Frequency Division Multiplexing Signals
303(3)
26.3 Bandwidth Efficiency of OFDM Signals
306(1)
26.4 Demodulation of OFDM Signals
307(1)
26.5 BER Simulation of OFDM Systems
307(4)
References
310(1)
27 Orthogonal Frequency Division Multiplexing over Multipath Fading Channels
311(13)
27.1 Multipath Fading Channels
311(3)
27.2 Guard Interval, CP, and Channel Estimation
314(5)
27.3 BER Simulation of OFDM Systems over Multipath Fading Channels
319(5)
References
323(1)
28 MIMO System---Part I: Space Time Code
324(12)
28.1 System Model
324(3)
28.2 Alamouti Code
327(3)
28.3 Simple Detection of Alamouti Code
330(4)
28.4 [ A]Various STBCs, Their Diversity Orders, and Their Rates
334(2)
References
335(1)
29 MIMO System---Part II: Spatial Multiplexing
336(17)
29.1 MIMO for Spatial Multiplexing
336(1)
29.2 MLD Based on Exhaustive Search for SM MIMO
337(3)
29.3 Zero Forcing Detection
340(1)
29.4 Noise Enhancement of ZF Detection
341(2)
29.5 Successive Interference Cancellation Detection
343(4)
29.6 BER Simulation of ZF, SIC, OSIC, and ML Detection Schemes
347(3)
29.7 Relationship among the Number of Antennas, Diversity, and Data Rate
350(3)
References
352(1)
30 Near-Ultrasonic Wireless Orthogonal Frequency Division Multiplexing Modem Design
353(10)
30.1 Image File Transmission over a Near-Ultrasonic Wireless Channel
353(2)
30.2 Analysis of OFDM Transmitter Algorithms and the Transmitted Signals
355(2)
30.3 Analysis of OFDM Receiver Algorithms and the Received Signals
357(4)
30.4 Effects of System Parameters on the Performance
361(2)
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.
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