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With remarkable clarity, Drs. Bernard Sklar and fred harris introduce every digital communication technology at the heart of todays wireless and Internet revolutions, with completely new chapters on synchronisation, OFDM, and MIMO.
Building on the fields classic, best-selling introduction, the authors provide a unified structure and context for helping students and professional engineers understand each technology, without sacrificing mathematical precision. They illuminate the big picture and details of modulation, coding, and signal processing, tracing signals and processing steps from information source through sink. Throughout, readers will find numeric examples, step-by-step implementation guidance, and diagrams that place key concepts in clear context.
- Understand signals, spectra, modulation, demodulation, detection, communication links, system link budgets, synchronisation, fading, and other key concepts
- Apply channel coding techniques, including advanced turbo coding and LDPC
- Explore multiplexing, multiple access, and spread spectrum concepts and techniques
- Learn about source coding: amplitude quantising, differential PCM, and adaptive prediction
- Discover the essentials and applications of synchronisation, OFDM, and MIMO technology
With remarkable clarity, Drs. Bernard Sklar and fred harris introduce every digital communication technology at the heart of todays wireless and Internet revolutions, with completely new chapters on synchronisation, OFDM, and MIMO.
Building on the fields classic, best-selling introduction, the authors provide a unified structure and context for helping students and professional engineers understand each technology, without sacrificing mathematical precision. They illuminate the big picture and details of modulation, coding, and signal processing, tracing signals and processing steps from information source through sink. Throughout, readers will find numeric examples, step-by-step implementation guidance, and diagrams that place key concepts in clear context.
- Understand signals, spectra, modulation, demodulation, detection, communication links, system link budgets, synchronisation, fading, and other key concepts
- Apply channel coding techniques, including advanced turbo coding and LDPC
- Explore multiplexing, multiple access, and spread spectrum concepts and techniques
- Learn about source coding: amplitude quantising, differential PCM, and adaptive prediction
- Discover the essentials and applications of synchronisation, OFDM, and MIMO technology
Über den Autor
Dr. Bernard Sklar has over 40 years of experience in technical design and management positions at Republic Aviation, Hughes Aircraft, Litton Industries, and The Aerospace Corporation, where he helped develop the MILSTAR satellite system. He is now head of advanced systems at Communications Engineering Services, a consulting company he founded in 1984. He has taught engineering courses at several universities, including UCLA and USC, and has trained professional engineers worldwide.
Dr. Fredric J. Harris is a professor of electrical engineering and the CUBIC signal processing chair at San Diego State University and an internationally renowned expert on DSP and communication systems. He is also the co-inventor of the BlackmanHarris filter. He has extensively published many technical papers, the most famous being the seminal 1978 paper On the Use of Windows for Harmonic Analysis with the Discrete Fourier Transform. He is also the author of the textbook Multi-Rate Signal Processing for Communication Systems and the source coding chapter in the previous edition of this book.
Inhaltsverzeichnis
Preface xxiii
Chapter 1 SIGNALS AND SPECTRA 1
1.1 Digital Communication Signal Processing 2
1.1.1 Why Digital? 2
1.1.2 Typical Block Diagram and Transformations 4
1.1.3 Basic Digital Communication Nomenclature 7
1.1.4 Digital Versus Analog Performance Criteria 9
1.2 Classification of Signals 10
1.2.1 Deterministic and Random Signals 10
1.2.2 Periodic and Nonperiodic Signals 10
1.2.3 Analog and Discrete Signals 10
1.2.4 Energy and Power Signals 11
1.2.5 The Unit Impulse Function 12
1.3 Spectral Density 13
1.3.1 Energy Spectral Density 13
1.3.2 Power Spectral Density 14
1.4 Autocorrelation 15
1.4.1 Autocorrelation of an Energy Signal 10
1.4.2 Autocorrelation of a Periodic (Power) Signal 16
1.5 Random Signals 17
1.5.1 Random Variables 17
1.5.2 Random Processes 19
1.5.3 Time Averaging and Ergodicity 21
1.5.4 Power Spectral Density and Autocorrelation of a Random Process 22
1.5.5 Noise in Communication Systems 27
1.6 Signal Transmission Through Linear Systems 30
1.6.1 Impulse Response 30
1.6.2 Frequency Transfer Function 31
1.6.3 Distortionless Transmission 32
1.6.4 Signals, Circuits, and Spectra 39
1.7 Bandwidth of Digital Data 41
1.7.1 Baseband Versus Bandpass 41`
1.7.2 The Bandwidth Dilemma 44
1.8 Conclusion 47
Chapter 2 FORMATTING AND BASEBAND MODULATION 53
2.1 Baseband Systems 54
2.2 Formatting Textual Data (Character Coding) 55
2.3 Messages, Characters, and Symbols 55
2.3.1 Example of Messages, Characters, and Symbols 56
2.4 Formatting Analog Information 57
2.4.1 The Sampling Theorem 57
2.4.2 Aliasing 64
2.4.3 Why Oversample? 67
2.4.4 Signal Interface for a Digital System 69
2.5 Sources of Corruption 70
2.5.1 Sampling and Quantizing Effects 71
2.5.2 Channel Effects 71
2.5.3 Signal-to-Noise Ratio for Quantized Pulses 72
2.6 Pulse Code Modulation 73
2.7 Uniform and Nonuniform Quantization 75
2.7.1 Statistics of Speech Amplitudes 75
2.7.2 Nonuniform Quantization 77
2.7.3 Companding Characteristics 77
2.8 Baseband Transmission 79
2.8.1 Waveform Representation of Binary Digits 79
2.8.2 PCM Waveform Types 80
2.8.3 Spectral Attributes of PCM Waveforms 83
2.8.4 Bits per PCM Word and Bits per Symbol 84
2.8.5 M-ary Pulse-Modulation Waveforms 86
2.9 Correlative Coding 88
2.9.1 Duobinary Signaling 88
2.9.2 Duobinary Decoding 89
2.9.3 Precoding 90
2.9.4 Duobinary Equivalent Transfer Function 91
2.9.5 Comparison of Binary and Duobinary Signaling 93
2.9.6 Polybinary Signaling 94
2.10 Conclusion 94
Chapter 3 BASEBAND DEMODULATION/DETECTION 99
3.1 Signals and Noise 100
3.1.1 Error-Performance Degradation in Communication Systems 100
3.1.2 Demodulation and Detection 101
3.1.3 A Vectorial View of Signals and Noise 105
3.1.4 The Basic SNR Parameter for Digital Communication Systems 112
3.1.5 Why Eb /N0 Is a Natural Figure of Merit 113
3.2 Detection of Binary Signals in Gaussian Noise 114
3.2.1 Maximum Likelihood Receiver Structure 114
3.2.2 The Matched Filter 117
3.2.3 Correlation Realization of the Matched Filter 119
3.2.4 Optimizing Error Performance 122
3.2.5 Error Probability Performance of Binary Signaling 126
3.3 Intersymbol Interference 130
3.3.1 Pulse Shaping to Reduce ISI 133
3.3.2 Two Types of Error-Performance Degradation 136
3.3.3 Demodulation/Detection of Shaped Pulses 140
3.4 Equalization 144
3.4.1 Channel Characterization 144
3.4.2 Eye Pattern 145
3.4.3 Equalizer Filter Types 146
3.4.4 Preset and Adaptive Equalization 152
3.4.5 Filter Update Rate 155
3.5 Conclusion 156
Chapter 4 BANDPASS MODULATION AND DEMODULATION/DETECTION 161
4.1 Why Modulate? 162
4.2 Digital Bandpass Modulation Techniques 162
4.2.1 Phasor Representation of a Sinusoid 163
4.2.2 Phase-Shift Keying 166
4.2.3 Frequency-Shift Keying 167
4.2.4 Amplitude Shift Keying 167
4.2.5 Amplitude-Phase Keying 168
4.2.6 Waveform Amplitude Coefficient 168
4.3 Detection of Signals in Gaussian Noise 169
4.3.1 Decision Regions 169
4.3.2 Correlation Receiver 170
4.4 Coherent Detection 175
4.4.1 Coherent Detection of PSK 175
4.4.2 Sampled Matched Filter 176
4.4.3 Coherent Detection of Multiple Phase-Shift Keying 181
4.4.4 Coherent Detection of FSK 184
4.5 Noncoherent Detection 187
4.5.1 Detection of Differential PSK 187
4.5.2 Binary Differential PSK Example 188
4.5.3 Noncoherent Detection of FSK 190
4.5.4 Required Tone Spacing for Noncoherent Orthogonal FSK Signaling 192
4.6 Complex Envelope 196
4.6.1 Quadrature Implementation of a Modulator 197
4.6.2 D8PSK Modulator Example 198
4.6.3 D8PSK Demodulator Example 200
4.7 Error Performance for Binary Systems 202
4.7.1 Probability of Bit Error for Coherently Detected BPSK 202
4.7.2 Probability of Bit Error for Coherently Detected, Differentially Encoded Binary PSK 204
4.7.3 Probability of Bit Error for Coherently Detected Binary Orthogonal FSK 204
4.7.4 Probability of Bit Error for Noncoherently Detected Binary Orthogonal FSK 206
4.7.5 Probability of Bit Error for Binary DPSK 208
4.7.6 Comparison of Bit-Error Performance for Various Modulation Types 210
4.8 M-ary Signaling and Performance 211
4.8.1 Ideal Probability of Bit-Error Performance 211
4.8.2 M-ary Signaling 212
4.8.3 Vectorial View of MPSK Signaling 214
4.8.4 BPSK and QPSK Have the Same Bit-Error Probability 216
4.8.5 Vectorial View of MFSK Signaling 217
> 2) 221
4.9.1 Probability of Symbol Error for MPSK 221
4.9.2 Probability of Symbol Error for MFSK 222
4.9.3 Bit-Error Probability Versus Symbol Error Probability for Orthogonal Signals 223
4.9.4 Bit-Error Probability Versus Symbol Error Probability for Multiple-Phase Signaling 226
4.9.5 Effects of Intersymbol Interference 228
4.10 Conclusion 228
Chapter 5 COMMUNICATIONS LINK ANALYSIS 235
5.1 What the System Link Budget Tells the System Engineer 236
5.2 The Channel 236
5.2.1 The Concept of Free Space 237
5.2.2 Error-Performance Degradation 237
5.2.3 Sources of Signal Loss and Noise 238
5.3 Received Signal Power and Noise Power 243
5.3.1 The Range Equation 243
5.3.2 Received Signal Power as a Function of Frequency 247
5.3.3 Path Loss Is Frequency Dependent 248
5.3.4 Thermal Noise Power 250
5.4 Link Budget Analysis 252
5.4.1 Two Eb /N0 Values of Interest 254
5.4.2 Link Budgets Are Typically Calculated in Decibels 256
5.4.3 How Much Link Margin Is Enough? 257
5.4.4 Link Availability 258
5.5 Noise Figure, Noise Temperature, and System Temperature 263
5.5.1 Noise Figure 263
5.5.2 Noise Temperature 265
5.5.3 Line Loss 266
5.5.4 Composite Noise Figure and Composite Noise Temperature 269
5.5.5 System Effective Temperature 270
5.5.6 Sky Noise Temperature 275
5.6 Sample Link Analysis 279
5.6.1 Link Budget Details 279
5.6.2 Receiver Figure of Merit 282
5.6.3 Received Isotropic Power 282
5.7 Satellite Repeaters 283
5.7.1 Nonregenerative Repeaters 283
5.7.2 Nonlinear Repeater Amplifiers 288
5.8 System Trade-Offs 289
5.9 Conclusion 290
Chapter 6 CHANNEL CODING: PART 1: WAVEFORM CODES AND BLOCK CODES 297
6.1 Waveform Coding and Structured Sequences 298
6.1.1 Antipodal and Orthogonal Signals 298
6.1.2 M-ary Signaling 300
6.1.3 Waveform Coding 300
6.1.4 Waveform-Coding System Example 304
6.2 Types of Error Control 307
6.2.1 Terminal Connectivity 307
6.2.2 Automatic Repeat Request 307
6.3 Structured Sequences 309
6.3.1 Channel Models 309
6.3.2 Code Rate and Redundancy 311
6.3.3 Parity-Check Codes 312
6.3.4 Why Use Error-Correction Coding? 315
6.4 Linear Block Codes 320
6.4.1 Vector Spaces 320
6.4.2 Vector Subspaces 321
6.4.3 A (6, 3) Linear Block Code Example 322
6.4.4 Generator Matrix 323
6.4.5 Systematic Linear Block Codes 325
6.4.6 Parity-Check Matrix 326
6.4.7 Syndrome Testing 327
6.4.8 Error Correction 329
6.4.9 Decoder Implementation 332
6.5 Error-Detecting and Error-Correcting Capability 334
6.5.1 Weight and Distance of Binary Vectors 334
6.5.2 Minimum Distance of a Linear Code 335
6.5.3 Error Detection and Correction 335
6.5.4 Visualization of a 6-Tuple Space 339
6.5.5 Erasure Correction 341
6.6 Usefulness of the Standard Array 342
6.6.1 Estimating Code Capability 342
6.6.2 An (n, k) Example 343
6.6.3 Designing the (8, 2) Code...
Details
| Erscheinungsjahr: | 2020 |
|---|---|
| Fachbereich: | Nachrichtentechnik |
| Genre: | Importe, Technik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: | Gebunden |
| ISBN-13: | 9780134588568 |
| ISBN-10: | 0134588568 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Sklar, Bernard
Harris, Fredric J. |
| Auflage: | 3. Auflage |
| Hersteller: | Pearson |
| Verantwortliche Person für die EU: | Pearson, St.-Martin-Str. 82, D-81541 München, salesde@pearson.com |
| Maße: | 235 x 178 x 61 mm |
| Von/Mit: | Bernard Sklar (u. a.) |
| Erscheinungsdatum: | 24.12.2020 |
| Gewicht: | 1,928 kg |
Über den Autor
Dr. Bernard Sklar has over 40 years of experience in technical design and management positions at Republic Aviation, Hughes Aircraft, Litton Industries, and The Aerospace Corporation, where he helped develop the MILSTAR satellite system. He is now head of advanced systems at Communications Engineering Services, a consulting company he founded in 1984. He has taught engineering courses at several universities, including UCLA and USC, and has trained professional engineers worldwide.
Dr. Fredric J. Harris is a professor of electrical engineering and the CUBIC signal processing chair at San Diego State University and an internationally renowned expert on DSP and communication systems. He is also the co-inventor of the BlackmanHarris filter. He has extensively published many technical papers, the most famous being the seminal 1978 paper On the Use of Windows for Harmonic Analysis with the Discrete Fourier Transform. He is also the author of the textbook Multi-Rate Signal Processing for Communication Systems and the source coding chapter in the previous edition of this book.
Inhaltsverzeichnis
Preface xxiii
Chapter 1 SIGNALS AND SPECTRA 1
1.1 Digital Communication Signal Processing 2
1.1.1 Why Digital? 2
1.1.2 Typical Block Diagram and Transformations 4
1.1.3 Basic Digital Communication Nomenclature 7
1.1.4 Digital Versus Analog Performance Criteria 9
1.2 Classification of Signals 10
1.2.1 Deterministic and Random Signals 10
1.2.2 Periodic and Nonperiodic Signals 10
1.2.3 Analog and Discrete Signals 10
1.2.4 Energy and Power Signals 11
1.2.5 The Unit Impulse Function 12
1.3 Spectral Density 13
1.3.1 Energy Spectral Density 13
1.3.2 Power Spectral Density 14
1.4 Autocorrelation 15
1.4.1 Autocorrelation of an Energy Signal 10
1.4.2 Autocorrelation of a Periodic (Power) Signal 16
1.5 Random Signals 17
1.5.1 Random Variables 17
1.5.2 Random Processes 19
1.5.3 Time Averaging and Ergodicity 21
1.5.4 Power Spectral Density and Autocorrelation of a Random Process 22
1.5.5 Noise in Communication Systems 27
1.6 Signal Transmission Through Linear Systems 30
1.6.1 Impulse Response 30
1.6.2 Frequency Transfer Function 31
1.6.3 Distortionless Transmission 32
1.6.4 Signals, Circuits, and Spectra 39
1.7 Bandwidth of Digital Data 41
1.7.1 Baseband Versus Bandpass 41`
1.7.2 The Bandwidth Dilemma 44
1.8 Conclusion 47
Chapter 2 FORMATTING AND BASEBAND MODULATION 53
2.1 Baseband Systems 54
2.2 Formatting Textual Data (Character Coding) 55
2.3 Messages, Characters, and Symbols 55
2.3.1 Example of Messages, Characters, and Symbols 56
2.4 Formatting Analog Information 57
2.4.1 The Sampling Theorem 57
2.4.2 Aliasing 64
2.4.3 Why Oversample? 67
2.4.4 Signal Interface for a Digital System 69
2.5 Sources of Corruption 70
2.5.1 Sampling and Quantizing Effects 71
2.5.2 Channel Effects 71
2.5.3 Signal-to-Noise Ratio for Quantized Pulses 72
2.6 Pulse Code Modulation 73
2.7 Uniform and Nonuniform Quantization 75
2.7.1 Statistics of Speech Amplitudes 75
2.7.2 Nonuniform Quantization 77
2.7.3 Companding Characteristics 77
2.8 Baseband Transmission 79
2.8.1 Waveform Representation of Binary Digits 79
2.8.2 PCM Waveform Types 80
2.8.3 Spectral Attributes of PCM Waveforms 83
2.8.4 Bits per PCM Word and Bits per Symbol 84
2.8.5 M-ary Pulse-Modulation Waveforms 86
2.9 Correlative Coding 88
2.9.1 Duobinary Signaling 88
2.9.2 Duobinary Decoding 89
2.9.3 Precoding 90
2.9.4 Duobinary Equivalent Transfer Function 91
2.9.5 Comparison of Binary and Duobinary Signaling 93
2.9.6 Polybinary Signaling 94
2.10 Conclusion 94
Chapter 3 BASEBAND DEMODULATION/DETECTION 99
3.1 Signals and Noise 100
3.1.1 Error-Performance Degradation in Communication Systems 100
3.1.2 Demodulation and Detection 101
3.1.3 A Vectorial View of Signals and Noise 105
3.1.4 The Basic SNR Parameter for Digital Communication Systems 112
3.1.5 Why Eb /N0 Is a Natural Figure of Merit 113
3.2 Detection of Binary Signals in Gaussian Noise 114
3.2.1 Maximum Likelihood Receiver Structure 114
3.2.2 The Matched Filter 117
3.2.3 Correlation Realization of the Matched Filter 119
3.2.4 Optimizing Error Performance 122
3.2.5 Error Probability Performance of Binary Signaling 126
3.3 Intersymbol Interference 130
3.3.1 Pulse Shaping to Reduce ISI 133
3.3.2 Two Types of Error-Performance Degradation 136
3.3.3 Demodulation/Detection of Shaped Pulses 140
3.4 Equalization 144
3.4.1 Channel Characterization 144
3.4.2 Eye Pattern 145
3.4.3 Equalizer Filter Types 146
3.4.4 Preset and Adaptive Equalization 152
3.4.5 Filter Update Rate 155
3.5 Conclusion 156
Chapter 4 BANDPASS MODULATION AND DEMODULATION/DETECTION 161
4.1 Why Modulate? 162
4.2 Digital Bandpass Modulation Techniques 162
4.2.1 Phasor Representation of a Sinusoid 163
4.2.2 Phase-Shift Keying 166
4.2.3 Frequency-Shift Keying 167
4.2.4 Amplitude Shift Keying 167
4.2.5 Amplitude-Phase Keying 168
4.2.6 Waveform Amplitude Coefficient 168
4.3 Detection of Signals in Gaussian Noise 169
4.3.1 Decision Regions 169
4.3.2 Correlation Receiver 170
4.4 Coherent Detection 175
4.4.1 Coherent Detection of PSK 175
4.4.2 Sampled Matched Filter 176
4.4.3 Coherent Detection of Multiple Phase-Shift Keying 181
4.4.4 Coherent Detection of FSK 184
4.5 Noncoherent Detection 187
4.5.1 Detection of Differential PSK 187
4.5.2 Binary Differential PSK Example 188
4.5.3 Noncoherent Detection of FSK 190
4.5.4 Required Tone Spacing for Noncoherent Orthogonal FSK Signaling 192
4.6 Complex Envelope 196
4.6.1 Quadrature Implementation of a Modulator 197
4.6.2 D8PSK Modulator Example 198
4.6.3 D8PSK Demodulator Example 200
4.7 Error Performance for Binary Systems 202
4.7.1 Probability of Bit Error for Coherently Detected BPSK 202
4.7.2 Probability of Bit Error for Coherently Detected, Differentially Encoded Binary PSK 204
4.7.3 Probability of Bit Error for Coherently Detected Binary Orthogonal FSK 204
4.7.4 Probability of Bit Error for Noncoherently Detected Binary Orthogonal FSK 206
4.7.5 Probability of Bit Error for Binary DPSK 208
4.7.6 Comparison of Bit-Error Performance for Various Modulation Types 210
4.8 M-ary Signaling and Performance 211
4.8.1 Ideal Probability of Bit-Error Performance 211
4.8.2 M-ary Signaling 212
4.8.3 Vectorial View of MPSK Signaling 214
4.8.4 BPSK and QPSK Have the Same Bit-Error Probability 216
4.8.5 Vectorial View of MFSK Signaling 217
> 2) 221
4.9.1 Probability of Symbol Error for MPSK 221
4.9.2 Probability of Symbol Error for MFSK 222
4.9.3 Bit-Error Probability Versus Symbol Error Probability for Orthogonal Signals 223
4.9.4 Bit-Error Probability Versus Symbol Error Probability for Multiple-Phase Signaling 226
4.9.5 Effects of Intersymbol Interference 228
4.10 Conclusion 228
Chapter 5 COMMUNICATIONS LINK ANALYSIS 235
5.1 What the System Link Budget Tells the System Engineer 236
5.2 The Channel 236
5.2.1 The Concept of Free Space 237
5.2.2 Error-Performance Degradation 237
5.2.3 Sources of Signal Loss and Noise 238
5.3 Received Signal Power and Noise Power 243
5.3.1 The Range Equation 243
5.3.2 Received Signal Power as a Function of Frequency 247
5.3.3 Path Loss Is Frequency Dependent 248
5.3.4 Thermal Noise Power 250
5.4 Link Budget Analysis 252
5.4.1 Two Eb /N0 Values of Interest 254
5.4.2 Link Budgets Are Typically Calculated in Decibels 256
5.4.3 How Much Link Margin Is Enough? 257
5.4.4 Link Availability 258
5.5 Noise Figure, Noise Temperature, and System Temperature 263
5.5.1 Noise Figure 263
5.5.2 Noise Temperature 265
5.5.3 Line Loss 266
5.5.4 Composite Noise Figure and Composite Noise Temperature 269
5.5.5 System Effective Temperature 270
5.5.6 Sky Noise Temperature 275
5.6 Sample Link Analysis 279
5.6.1 Link Budget Details 279
5.6.2 Receiver Figure of Merit 282
5.6.3 Received Isotropic Power 282
5.7 Satellite Repeaters 283
5.7.1 Nonregenerative Repeaters 283
5.7.2 Nonlinear Repeater Amplifiers 288
5.8 System Trade-Offs 289
5.9 Conclusion 290
Chapter 6 CHANNEL CODING: PART 1: WAVEFORM CODES AND BLOCK CODES 297
6.1 Waveform Coding and Structured Sequences 298
6.1.1 Antipodal and Orthogonal Signals 298
6.1.2 M-ary Signaling 300
6.1.3 Waveform Coding 300
6.1.4 Waveform-Coding System Example 304
6.2 Types of Error Control 307
6.2.1 Terminal Connectivity 307
6.2.2 Automatic Repeat Request 307
6.3 Structured Sequences 309
6.3.1 Channel Models 309
6.3.2 Code Rate and Redundancy 311
6.3.3 Parity-Check Codes 312
6.3.4 Why Use Error-Correction Coding? 315
6.4 Linear Block Codes 320
6.4.1 Vector Spaces 320
6.4.2 Vector Subspaces 321
6.4.3 A (6, 3) Linear Block Code Example 322
6.4.4 Generator Matrix 323
6.4.5 Systematic Linear Block Codes 325
6.4.6 Parity-Check Matrix 326
6.4.7 Syndrome Testing 327
6.4.8 Error Correction 329
6.4.9 Decoder Implementation 332
6.5 Error-Detecting and Error-Correcting Capability 334
6.5.1 Weight and Distance of Binary Vectors 334
6.5.2 Minimum Distance of a Linear Code 335
6.5.3 Error Detection and Correction 335
6.5.4 Visualization of a 6-Tuple Space 339
6.5.5 Erasure Correction 341
6.6 Usefulness of the Standard Array 342
6.6.1 Estimating Code Capability 342
6.6.2 An (n, k) Example 343
6.6.3 Designing the (8, 2) Code...
Details
| Erscheinungsjahr: | 2020 |
|---|---|
| Fachbereich: | Nachrichtentechnik |
| Genre: | Importe, Technik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: | Gebunden |
| ISBN-13: | 9780134588568 |
| ISBN-10: | 0134588568 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Sklar, Bernard
Harris, Fredric J. |
| Auflage: | 3. Auflage |
| Hersteller: | Pearson |
| Verantwortliche Person für die EU: | Pearson, St.-Martin-Str. 82, D-81541 München, salesde@pearson.com |
| Maße: | 235 x 178 x 61 mm |
| Von/Mit: | Bernard Sklar (u. a.) |
| Erscheinungsdatum: | 24.12.2020 |
| Gewicht: | 1,928 kg |
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