Suchen und Finden
Preface
6
Salient Features
7
Acknowledgements
9
Contents
10
Chapter1 Preview and Introduction
15
1.1 Process of Communication
15
1.2 General Definition of Signal
17
1.3 Time-Value Definition of SignalsAnalog and Digital
20
1.3.1 Continuous Time Continuous Valued Signal
21
1.3.2 Discrete Time Continuous Valued Signal
21
1.3.3 Discrete Time Discrete Valued Signal
21
1.4 Analog and Digital Communication Systems
22
1.5 Elements of Digital Communication System
24
1.6 MATLAB Programs
25
1.6.1 Time and Frequency Domain Representation of Signals
25
1.6.2 CTSV, DTCV, DTDV Signals
26
References
27
Chapter2 Waveform Encoding
28
2.1 Introduction
28
2.2 Pulse Code Modulation (PCM)
28
2.2.1 Process of Sampling
29
2.2.1.1 Sampling Theorem
31
Case I
32
Case II
33
Case III
33
2.2.1.2 Aliasing
34
2.2.2 Process of Quantization
35
2.2.3 PCM Transmitter and Receiver
37
2.2.3.1 PCM Transmitter
37
2.2.3.2 PCM Receiver
39
2.2.4 Quantization Error
40
2.2.5 Signal to Noise Ratio (SNR) for Quantized Pulses
42
2.2.6 Non-uniform Quantization: Companding
43
2.2.6.1 -Law
45
2.2.6.2 A-Law
47
2.3 Differential Pulse Code Modulation (DPCM)
48
2.3.1 Cumulative Error in PCM
48
2.3.2 Prevention of Cumulative Error by Applying Feedback
49
2.3.3 How We Can Predict the Future?
51
2.3.4 Analysis of DPCM
53
2.4 Delta Modulation
54
2.4.1 Drawbacks of Delta Modulation
56
2.4.1.1 Slope Overloading
56
2.4.1.2 Granular Noise
57
2.5 Adaptive Delta Modulation
57
2.5.1 Song Algorithm
57
2.5.2 Space-Shuttle Algorithm
59
2.6 Sigma-Delta Modulation (SDM)
60
2.6.1 Noise Performance
61
2.7 Linear Predictive Coder (LPC)
62
2.7.1 Concept
62
2.7.2 Genetic Algorithm Based Approach
63
2.8 MATLAB Programs
66
2.8.1 Aliasing
66
References
67
Chapter3 Digital Baseband Signal Receivers
68
3.1 Introduction
68
3.2 Integrate and Dump Type Filter
69
3.2.1 Noise Power and Variance
72
3.2.2 Figure of Merit
74
3.2.3 Probability of Error
74
3.3 The Optimum Filter
76
3.4 The Matched Filter
80
3.4.1 Impulse Response
80
3.4.2 Probability of Error
80
3.4.3 Properties of Matched Filter
83
3.5 The Correlator
85
3.6 Simulink Communication Block Set Example
87
Integrate and Dump
87
Library
87
Description
87
Dialog Box
87
Examples
88
References
88
Chapter4 Digital Baseband Signal Transmitter
89
4.1 Introduction
89
4.2 Elements of Digital Baseband Communication System
89
4.2.1 Formatting
90
4.2.2 Regenerative Repeater
90
4.3 Properties and Choice of Digital Formats
92
4.4 Line Coding
93
4.5 Power Spectrum Density of Different Digital Formats
95
4.5.1 Unipolar-NRZ
98
4.5.2 Unipolar-RZ
99
4.5.3 Polar-NRZ
100
4.5.4 Polar-RZ
101
4.5.5 Bipolar-NRZ
102
4.5.6 Split-Phase (Manchester)
103
References
105
Chapter5 Equalization
106
5.1 Inter-Symbol Interference (ISI)
106
5.2 Nyquist Criterion for Distortion Less Transmission (Zero ISI)
108
5.2.1 Criteria in Frequency Domain
109
5.2.2 Concept of Ideal Nyquist Channel
111
5.2.3 Limitations of Ideal Solution: Raised Cosine Spectrum
112
5.3 Eye Pattern
114
5.3.1 Information Obtained from Eye Pattern
115
5.4 System Design for Known Channel
115
5.5 Linear Equalizer
117
5.5.1 Linear Transversal Filter
117
5.6 Adaptive Equalizer
119
References
121
Chapter6 Digital Modulation Techniques
122
6.1 Introduction
122
6.2 Amplitude Shift Keying (ASK)
123
6.2.1 Mathematical Model
124
6.2.1.1 On-0Off Keying ( OOK)
125
6.2.2 ASK Modulator
126
6.2.3 Binary ASK Demodulator
128
6.3 Frequency Shift Keying (FSK)
129
6.3.1 Mathematical Model
129
6.3.2 BFSK Modulator
130
6.3.3 FSK Demodulator
132
6.4 Binary Phase Shift Keying (BPSK)
133
6.4.1 Mathematical Model
134
6.4.2 BPSK Modulator
135
6.4.3 BPSK Demodulator
136
6.5 Differential Phase Shift Keying (DPSK)
136
6.5.1 DPSK Modulator
136
6.5.2 DPSK Demodulator
138
6.6 Quadrature Phase Shift Keying (QPSK)
138
6.6.1 Mathematical Model
138
6.6.2 QPSK Modulator
142
6.6.3 QPSK Demodulator
142
6.6.4 Offset QPSK (OQPSK)
143
6.7 Minimum Shift Keying (MSK)
145
6.8 Probability of Error for Different Modulation Schemes
147
6.8.1 Probability of Error in ASK
147
6.8.2 Probability of Error in FSK
148
6.8.3 Probability of Error in PSK
149
6.9 MATLAB Programs
150
6.9.1 QPSK Waveform
150
6.9.2 MSK Waveform
151
References
152
Chapter7 Spread Spectrum Modulation
153
7.1 Introduction
153
7.2 Processing Gain
154
7.3 Pseudo-Noise (PN) Sequence
155
7.3.1 Concept: A Hypothetical Experiment
155
7.3.2 Generation of PN Sequence
156
7.3.3 Properties of PN Sequence
157
7.4 Direct Sequence Spread Spectrum (DSSS)
159
7.4.1 Concept
159
7.4.2 DSSS with Coherent BPSK
161
7.4.3 Probability of Error Calculation
162
7.5 Frequency-Hopped Spread Spectrum
165
7.5.1 Concept
165
7.5.2 FHSS with FSK
167
7.5.3 Rate of Hopping: Fast and Slow
169
7.6 Application of Spread Spectrum
169
7.6.1 GPS (Global Positioning System)
169
7.7 CDMA (Code Division Multiple Access)
173
7.7.1 Orthogonal Chip Sequence
173
7.7.2 Gold Sequence
175
7.7.3 Principle of Operation
176
7.7.3.1 MUX
176
7.7.3.2 DMUX
176
References
176
Chapter8 Information Theory
178
8.1 Introduction
178
8.2 Entropy
180
8.3 Rate of Information
182
8.4 Information Sources
182
8.5 Discrete Memoryless Channel (DMC)
185
8.5.1 Channel Representation
185
8.5.2 The Channel Matrix
185
8.6 Special Channels
186
8.6.1 Lossless Channel
186
8.6.2 Deterministic Channel
187
8.6.3 Noise-Less Channel
188
8.6.4 Binary Symmetric Channel (BSC)
188
8.6.4.1 Saturated or Stable Probability of Error for Cascaded BSC Channel
189
8.6.4.2 Probability Model of Erroneous Detection in Cascaded BSC
189
8.7 Mutual Information
191
8.8 Channel Capacity
192
8.8.1 Gaussian Channel: Shanon-Hartley Theorem
192
8.9 Entropy Coding
194
8.9.1 Shanon-Fano Coding
195
8.9.2 Huffman Coding
196
8.10 MATLAB Code
197
8.10.1 Convergence of Pe in Cascaded BSC
197
References
198
Chapter9 Error Control Coding
199
9.1 Introduction
199
9.2 Scope of Coding
200
Forward Error Correction
200
9.3 Linear Block Code
201
9.3.1 Coding Technique Using Generator Matrix
201
9.3.2 Syndrome Decoding
203
9.4 Convolutional Code
204
9.4.1 Encoder
204
9.4.1.1 Operation
205
9.4.1.2 Code Rate
207
9.4.2 State Diagram
207
9.4.3 Code Tree
208
9.4.4 Trellis Diagram
208
9.4.5 Decoding of Convolutional Code by Viterbi
210
9.4.5.1 Metric
210
9.4.5.2 Surviving Path
210
9.4.5.3 Principle of Decoding
210
9.5 Cyclic Code
212
9.5.1 Concept and Properties
212
9.5.2 Encoder and Decoder
214
9.5.3 Meggitt Decoder
215
9.6 BCH Code
215
9.6.1 Simplified BCH Codes
216
9.6.2 General BCH Codes
218
9.6.3 Properties
218
References
219
AppendixAElementary Probability Theory
220
A.1 Concept of Probability
220
A.1.1 Random Experiments and Sample Space
220
A.1.2 Events
221
A.1.3 Probability-Understanding Approaches
221
A.2 Random Variable
221
A.3 Mean, Variance, Skew-ness and Kurtosis
222
A.4 Cumulative Distribution Function (CDF)
224
A.5 Probability Density Function (PDF)
226
A.5.1 Uniform PDF
226
A.5.2 Frequently Used Probability Distribution
227
A.5.2.1. Bernoulli Distribution
227
A.5.2.2 Gaussian Distribution
228
A.5.2.3. Poisson Distribution
228
A.5.2.4 Rayleigh Distribution
228
References
231
Appendix BConvolution and Correlation – Some CaseStudies
232
B.1 Convolution
232
B.1.1 Basic Properties of Convolution
234
B.1.1.1 Commutative Law
234
B.1.1.2 Associative Law
235
B.1.1.3 Distributive Law
235
B.1.1.4 Transformed Domain Simplicity
236
B.1.2 Case 1: Periodicity of Sampled Spectra
237
B.1.3 Case 2: Transmission of Normally Distributed Information
238
B.1.4 Case 3: Long Multiplication Using Convolution
239
B.2 Correlation
239
B.2.1 Case Study: Pattern (Shape Feature) Matching Between Two Objects Using Cross-Correlation
241
References
243
AppendixC Frequently Used MATLAB Functions
244
plot()
244
Description
244
imshow()
244
Description
245
drawnow()
245
Description
246
Remarks
246
Examples
246
stairs()
246
int2str()
246
Description
247
Examples
247
conv()
247
ginput()
248
Interactive Plotting
248
spline()
248
Description
249
Exceptions
250
Example
250
Reference
251
Index
252
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