Digital communications: fundamentals and applications
Gespeichert in:
| Hauptverfasser: | , |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
[Boston, MA]
Pearson
[2021]
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| Ausgabe: | Third edition |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | 1. Signals and Spectra ; 2. Formatting and Baseband Modulation ; 3. Baseband Demodulation/Detection ; 4. Bandpass Modulation and Demodulation/Detection ; 5. Communications Link Analysis ; 6. Channel Coding I: Waveform Codes and Block Codes ; 7. Channel Coding II: Convolutional Codes and Reed-Solomon Codes ; 8. Channel Coding III: Turbo Codes and Low-Density Parity Check (LDPC) Codes ; 9. Modulation and Coding Trade offs ; 10. Synchronization ; 11. Multiplexing and Multiple Access ; 12. Spread Spectrum Techniques ; 13. Source Coding ; 14. Fading Channels ; 15. The ABCs of OFDM ; 16. The Magic of MIMO ; |
| Beschreibung: | xxix, 1105 Seiten Illustrationen, Diagramme |
| ISBN: | 9780134588568 0134588568 |
Internformat
MARC
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| 245 | 1 | 0 | |a Digital communications |b fundamentals and applications |c Bernard Sklar ; Fred Harris |
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| 500 | |a 1. Signals and Spectra ; 2. Formatting and Baseband Modulation ; 3. Baseband Demodulation/Detection ; 4. Bandpass Modulation and Demodulation/Detection ; 5. Communications Link Analysis ; 6. Channel Coding I: Waveform Codes and Block Codes ; 7. Channel Coding II: Convolutional Codes and Reed-Solomon Codes ; 8. Channel Coding III: Turbo Codes and Low-Density Parity Check (LDPC) Codes ; 9. Modulation and Coding Trade offs ; 10. Synchronization ; 11. Multiplexing and Multiple Access ; 12. Spread Spectrum Techniques ; 13. Source Coding ; 14. Fading Channels ; 15. The ABCs of OFDM ; 16. The Magic of MIMO ; | ||
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Datensatz im Suchindex
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| adam_text | Contents at a Glance Preface xxiii Acknowledgments xxvii About the Authors xxix 1 Signals and Spectra 2 Formatting and Baseband Modulation 53 3 Baseband Demodulation/Detection 99 4 Bandpass Modulation and Demodulation/Detection 161 5 Communications Link Analysis 235 6 Channel Coding: Part 1: Waveform Codes and Block Codes 7 8 1 297 Channel Coding: Part 2: Convolutional Codes and Reed-Solomon Codes 375 Channel Coding: Part 3: Turbo Codes and Low-Density Parity Check (LDPC) Codes 471 v
Modulation and Coding Trade-Offs 549 10 Synchronization 619 11 Multiplexing and Multiple Access 681 12 Spread-Spectrum Techniques 741 13 Source Coding 823 14 Fading Channels 905 15 The ABCs of OFDM (Orthogonal FrequencyDivision Multiplexing) 971 9 16 The Magic of Mimo (Multiple Input/Multiple Output) 1017 1089 Index THE FOLLOWING ELEMENTS WILL BE ONLINE ONLY 17 Encryption and Decryption A A Review of Fourier Techniques В Fundamentals of Statistical Decision Theory C Response of a Correlator to White Noise D Often-Used Identities E S-Domain, Z-Domain, and Digital Filtering F OFDM Symbol Formation with an A-Point Inverse Discrete Fourier Transform (IDFT) G List of Symbols These online elements can be found at informit.com/title/ 9780134588568 vi Contents at a Glance
Contents Preface xxiii Acknowledgments xxvii About the Authors xxix 1 SIGNALS AND SPECTRA 1.1 1.2 1.3 1.4 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 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 Spectral Density 13 1.3.1 Energy Spectral Density 13 1.3.2 Power Spectral Density 14 Autocorrelation 15 1.4.1 Autocorrelation of an Energy Signal 10 1.4.2 Autocorrelation of a Periodic (Power) Signal 16 1
1.5 1.6 1.7 1.8 2 FORMATTING AND BASEBAND MODULATION 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 viii 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 ofa Random Process 22 1.5.5 Noise in Communication Systems 27 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 Bandwidth of Digital Data 41 1.7.1 Baseband Versus Bandpass 41 1.7.2 The Bandwidth Dilemma 44 Conclusion 47 53 Baseband Systems 54 Formatting Textual Data (Character Coding) 55 Messages, Characters, and Symbols 55 2.3.1 Example of Messages, Characters, and Symbols 56 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 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 Pulse Code Modulation 73 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 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 Correlative Coding 88 2.9.1 Duobinary Signaling 88 2.9.2 Duobinary Decoding 89 Contents
2.10 3 BASEBAND DEMODULATION/DETECTION 3.1 3.2 3.3 3.4 3.5 4 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 Conclusion 94 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 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 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 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 A daptive Equalization 152 3.4.5 Filter Update Rate 155 Conclusion 156 BANDPASS MODULATION AND DEMODULATION/DETECTION 4.1 4.2 Contents 99 161 Why Modulate? 162 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 ix
4.3 4.4 4.5 4.6 4.7 4.8 4.9 4.10 x Detection of Signals in Gaussian Noise 169 4.3.1 Decision Regions 169 4.3.2 Correlation Receiver 170 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 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 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 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 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 ΜFSK Signaling 217 Symbol Error Performance for M-ary Systems (Μ 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 Conclusion 228 Contents
5 COMMUNICATIONS LINK ANALYSIS 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6 What the System Link Budget Tells the System Engineer 236 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 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 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 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 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 Satellite Repeaters 283 5.7.1 Nonregenerative Repeaters 283 5.7.2 Nonlinear Repeater Amplifiers 288 System Ћade-Offs 289 Conclusion 290 CHANNEL CODING: PART 1: WAVEFORM CODES AND BLOCK CODES 6.1 6.2 Contents 235 297 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 Types of Error Control 307 6.2.1 Terminal Connectivity 307 6.2.2 Automatic Repeat Request 307 xi
6.3 6.4 6.5 6.6 6.7 6.8 6.9 7 CHANNEL CODING: PART 2: CONVOLUTIONAL CODES AND REED-SOLOMON CODES 375 7.1 xii 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 Linear Block Codes 320 6.4.1 VectorSpaces 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 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 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 344 6.6.4 Error Detection Versus Error Correction Trade-Offs 345 6.6.5 The Standard Array Provides Insight 347 Cyclic Codes 349 6.71 Algebraic Structure of Cyclic Codes 349 6.7.2 Binary Cyclic Code Properties 351 6.7.3 Encoding in Systematic Form 352 6.7.4 Circuit for Dividing Polynomials 353 6.7.5 Systematic Encoding with an (n - k)-Stage Shift Register 356 6.7.6 Error Detection with an (n - k)-Stage Shift Register 358 Well-Known Block Codes 359 6.8.1 Hamming Codes 359 6.8.2 Extended Golay Code 361 6.8.3 BCH Codes 363 Conclusion 367 Convolutional Encoding 376 Contents
7.2 7.3 7.4 7.5 7.6 Ί.Ί 7.8 7.9 Contents Convolutional Encoder Representation 378 7.2.1 Connection Representation 378 7.2.2 State Representation and the State Diagram 382 7.2.3 The Tree Diagram 385 7.2.4 The Trellis Diagram 385 Formulation of the Convolutional Decoding Problem 388 7.3.1 Maximum Likelihood Decoding 388 7.3.2 Channel Models: Hard Versus Soft Decisions 390 7.3.3 The Viterbi Convolutional Decoding Algorithm 394 7.3.4 An Example of Viterbi Convolutional Decoding 394 7.3.5 Decoder Implementation 398 7.3.6 Path Memory and Synchronization 401 Properties of Convolutional Codes 402 7.4.1 Distance Properties of Convolutional Codes 402 7.4.2 Systematic and Nonsystematic Convolutional Codes 406 7.4.3 Catastrophic Error Propagation in Convolutional Codes 407 7.4.4 Performance Bounds for Convolutional Codes 408 7.4.5 Coding Gain 409 7.4.6 Best-Known Convolutional Codes 411 7.4.7 Convolutional Code Rate Trade-Off 413 7.4.8 Soft-Decision Viterbi Decoding 413 Other Convolutional Decoding Algorithms 415 7.5.1 Sequential Decoding 415 7.5.2 Comparisons and Limitations of Viterbi and Sequential Decoding 418 7.5.3 Feedback Decoding 419 Reed-Solomon Codes 421 7.6.1 Reed-Solomon Error Probability 423 7.6.2 Why R-S Codes Perform Well Against Burst Noise 426 7.6.3 R-S Performance as a Function of Size, Redundancy, and Code Rate 426 7.6.4 Finite Fields 429 7.6.5 Reed-Solomon Encoding 435 7.6.6 Reed-Solomon Decoding 439 Interleaving and Concatenated Codes 446 7.7.1 Block Interleaving 449 7.7.2 Convolutional Interleaving 452 7.7.3 Concatenated Codes 453 Coding and Interleaving Applied
to the Compact Disc Digital Audio System 454 7.8.1 CIRC Encoding 456 7.8.2 CIRC Decoding 458 7.8.3 Interpolation and Muting 460 Conclusion 462 xiii
8 CHANNEL CODING: PART 3: TURBO CODES AND LOW-DENSITY PARITY CHECK (LDPC) CODES 471 Turbo Codes 472 8.1.1 Turbo Code Concepts 472 8.1.2 Log-Likelihood A lgebra 476 Product Code Example 477 8.1.3 8.1.4 Encoding with Recursive Systematic Codes 484 A Feedback Decoder 489 8.1.5 8.1.6 The MAP Algorithm 493 8.1.7 MAP Decoding Example 499 8.2 Low-Density Parity Check (LDPC) Codes 504 8.2.1 Background and Overview 504 8.2.2 The Parity-Check Matrix 505 8.2.3 Finding the Best-Performing Codes 507 8.2.4 Decoding:An Overview 509 Mathematical Foundations 514 8.2.5 8.2.6 Decoding in the Probability Domain 518 8.2.7 Decoding in the Logarithmic Domain 526 8.2.8 Reduced-Complexity Decoders 531 8.2.9 LDPC Performance 532 8.2.10 Conclusion 535 Appendix 8A: The Sum of Log-Likelihood Ratios 535 Appendix 8B: Using Bayes’Theorem to Simplify the Bit Conditional Probability 537 Appendix 8C: Probability that a Binary Sequence Contains an Even Number of Ones 537 Appendix 8D: Simplified Expression for the Hyperbolic Tangent of the Natural Log of a Ratio of Binary Probabilities 538 Appendix 8E: Proof that ф(х) = ф֊1(х) 538 Appendix 8F: Bit Probability Initialization 539 8.1 9 MODULATION AND CODING TRADE-OFFS 9.1 9.2 9.3 9.4 9.5 xlv Goals of the Communication System Designer 550 Error-Probability Plane 550 Nyquist Minimum Bandwidth 552 Shannon-Hartley Capacity Theorem 554 9.4.1 Shannon Limit 556 9.4.2 Entropy 557 9.4.3 Equivocation and Effective Transmission Rate Bandwidth-Efficiency Plane 562 9.5.1 Bandwidth Efficiency ofMPSK and MFSK Modulation 563 549 560 Contents
Analogies Between the Bandwidth-Efficiency and Error-Probability Planes 564 Modulation and Coding Trade-Offs 565 Defining, Designing, and Evaluating Digital Communication Systems 566 9.7.1 M-ary Signaling 567 9.7.2 Bandwidth-Limited Systems 568 9.7.3 Power-Limited Systems 569 9.7.4 Requirements for MPSК and MFSK Signaling 570 9.7.5 Bandwidth-Limited Uncoded System Example 571 9.7.6 Power-Limited Uncoded System Example 573 9.7.7 Bandwidth-Limited and Power-Limited Coded System Example 575 Bandwidth-Efficient Modulation 583 9.8.1 QPSK and Offset QPSK Signaling 583 9.8.2 Minimum-Shift Keying 587 9.8.3 Quadrature Amplitude Modulation 591 Trellis-Coded Modulation 594 9.9.1 The Idea Behind Trellis-Coded Modulation 595 9.9.2 TCM Encoding 597 9.9.3 TCM Decoding 601 9.9.4 Other Trellis Codes 604 9.9.5 Trellis-Coded Modulation Example 606 9.9.6 Multidimensional Trellis-Coded Modulation 610 Conclusion 610 9.5.2 9.6 9.7 9.8 9.9 9.10 10 SYNCHRONIZATION 10.1 10.2 10.3 Contents 619 Receiver Synchronization 620 10.1.1 Why We Must Synchronize 620 10.1.2 Alignment at the Waveform Level and Bit Stream Level 620 10.1.3 Carrier-Wave Modulation 620 10.1.4 Carrier Synchronization 621 10.1.5 Symbol Synchronization 624 10.1.6 Eye Diagrams and Constellations 625 Synchronous Demodulation 626 10.2.1 Minimizing Energy in the Difference Signal 628 10.2.2 Finding the Peak of the Correlation Function 629 10.2.3 The Basic Analog Phase-Locked Loop (PLL) 631 10.2.4 Phase-Locking Remote Oscillators 631 10.2.5 Estimating Phase Slope (Frequency) 633 Loop Filters, Control Circuits, and Acquisition 634 10.3.1 How
Many Loop Filters Are There in a System? 634 10.3.2 The Key Loop Filters 634 XV
10.4 10.5 10.6 10.7 11 MULTIPLEXING AND MULTIPLE ACCESS 11.1 11.2 11.3 xvi 10.3.3 Why We Want R Times R-dot 634 10.3.4 The Phase Error S-Curve 636 Phase-Locked Loop Timing Recovery 637 10.4.1 Recovering Carrier Timing from a Modulated Waveform 637 10.4.2 Classical Timing Recovery Architectures 638 10.4.3 Timing-Error Detection: Insight from the Correlation Function 641 10.4.4 Maximum-Likelihood Timing-Error Detection 642 10.4.5 Polyphase Matched Filter and Derivative Matched Filter 643 10.4.6 Approximate ML Timing Recovery PLL for a 32-Path PLL 647 Frequency Recovery Using a Frequency-Locked Loop(FLL) 652 10.5.1 Band-Edge Filters 654 10.5.2 Band-Edge Filter Non-Data-Aided Timing Synchronization 660 Effects of Phase and Frequency Offsets 664 10.6.1 Phase Offset and No Spinning: Effect on Constellation 665 10.6.2 Slow Spinning Effect on Constellation 667 10.6.3 Fast Spinning Effect on Constellation 670 Conclusion 672 681 Allocation of the Communications Resource 682 11.1.1 Frequency-Division Multiplexing/Multiple Access 683 11.1.2 Time-Division Multiplexing/Multiple Access 688 11.1.3 Communications Resource Channelization 691 11.1.4 Performance Comparison ofFDMA and TDMA 692 11.1.5 Code-Division Multiple Access 695 11.1.6 Space-Division and Polarization-Division Multiple Access 698 Multiple-Access Communications System and Architecture 700 11.2.1 Multiple-Access Information Flow 701 11.2.2 Demand-Assignment Multiple Access 702 Access Algorithms 702 11.3.1 ALOHA 702 11.3.2 Slotted ALOHA 705 11.3.3 Reservation ALOHA 706 11.3.4 Performance Comparison of S-ALOHA and R-ALOHA 708
11.3.5 Polling Techniques 710 Contents
11.4 11.5 11.6 12 Multiple-Access Techniques Employed with INTELSAT 712 11.4.1 Preassigned FDM/FM/FDMA or MCPC Operation 713 11.4.2 MCPC Modes ofAccessing an INTELSAT Satellite 713 11.4.3 SPADE Operation 716 11.4.4 TDMA in INTELSAT 721 11.4.5 Satellite-Switched TDMA in INTELSAT 727 Multiple-Access Techniques for Local Area Networks 731 11.5.1 Carrier-Sense Multiple-Access Networks 731 11.5.2 Token-Ring Networks 733 11.5.3 Performance Comparison of CSMA/CD and Token-Ring Networks 734 Conclusion 736 SPREAD-SPECTRUM TECHNIQUES 12.1 12.2 12.3 12.4 12.5 12.6 Contents 741 Spread-Spectrum Overview 742 12.1.1 The Beneficial Attributes of Spread-Spectrum Systems 742 12.1.2 A Catalog of Spreading Techniques 746 12.1.3 Model for Direct-Sequence Spread-Spectrum Interference Rejection 747 12.1.4 Historical Background 748 Pseudonoise Sequences 750 12.2.1 Randomness Properties 750 12.2.2 Shift Register Sequences 750 12.2.3 PN Autocorrelation Function 752 Direct-Sequence Spread-Spectrum Systems 753 12.3.1 Example of Direct Sequencing 755 12.3.2 Processing Gain and Performance 756 Frequency-Hopping Systems 759 12.4.1 Frequency-Hopping Example 761 12.4.2 Robustness 762 12.4.3 Frequency Hopping with Diversity 762 12.4.4 Fast Hopping Versus Slow Hopping 763 12.4.5 FFH/MFSK Demodulator 765 12.4.6 Processing Gain 766 Synchronization 766 12.5.1 Acquisition 767 12.5.2 Tracking 772 Jamming Considerations 775 12.6.1 The Jamming Game 775 12.6.2 Broadband Noise Jamming 780 12.6.3 Partial-Band Noise Jamming 781 12.6.4 Multiple-Tone Jamming 783 12.6.5 Pulse Jamming 785 xvii
12.7 12.8 12.9 13 SOURCE CODING 13.1 13.2 13.3 13.4 13.5 13.6 13.7 xviii 12.6.6 Repeat-Back Jamming 787 12.6.7 BLADES System 788 Commercial Applications 789 12.7.1 Code-Division Multiple Access 789 12.7.2 Multipath Channels 792 12.7.3 The FCC Part 15 Rules for Spread-Spectrum Systems 12.7.4 Direct Sequence Versus Frequency Hopping 794 Cellular Systems 796 12.8.1 Direct-Sequence CDMA 796 12.8.2 Analog FM Versus TDMA Versus CDMA 799 12.8.3 Interference-Limited Versus Dimension-Limited Systems 801 12.8.4 IS-95 CDMA Digital Cellular System 803 Conclusion 814 793 823 Sources 824 13.1.1 Discrete Sources 824 13.1.2 Waveform Sources 829 Amplitude Quantizing 830 13.2.1 Quantizing Noise 833 13.2.2 Uniform Quantizing 836 13.2.3 Saturation 840 13.2.4 Dithering 842 13.2.5 Nonuniform Quantizing 845 Pulse Code Modulation 849 13.3.1 Differential Pulse Code Modulation 850 13.3.2 One-Tap Prediction 853 13.3.3 N-Tap Prediction 854 13.3.4 Delta Modulation 856 13.3.5 Σ-Δ Modulation 858 13.3.6 ^-IsA-to-D Converter (ADC) 862 13.3.7 Σ-Δ D-to-A Converter (DAC) 863 Adaptive Prediction 865 13.4.1 Forward Adaptation 865 13.4.2 Synthesis/Analysis Coding 866 Block Coding 868 13.5.1 Vector Quantizing 868 Transform Coding 870 13.6.1 Quantization for Transform Coding 872 13.6.2 Subband Coding 872 Source Coding for Digital Data 873 13.7.1 Properties of Codes 875 Contents
13.8 13.9 14 13.7.2 Huffman Code 877 13.7.3 Run-Length Codes 880 Examples of Source Coding 884 13.8.1 Audio Compression 884 13.8.2 Image Compression 889 Conclusion 898 FADING CHANNELS 14.1 14.2 14.3 14.4 14.5 14.6 14.7 14.8 Contents 905 The Challenge of Communicating over Fading Channels 906 Characterizing Mobile-Radio Propagation 907 14.2.1 Large-Scale Fading 912 14.2.2 Small-Scale Fading 914 Signal Time Spreading 918 14.3.1 Signal Time Spreading Viewed in the Time-Delay Domain 918 14.3.2 Signal Time Spreading Viewed in the Frequency Domain 920 14.3.3 Examples of Flat Fading and Frequency-Selective Fading 924 Time Variance of the Channel Caused by Motion 926 14.4.1 Time Variance Viewed in the Time Domain 926 14.4.2 Time Variance Viewed in the Doppler-Shift Domain 929 14.4.3 Performance over a Slow- and Flat-Fading Rayleigh Channel 935 Mitigating the Degradation Effects of Fading 937 14.5.1 Mitigation to Combat Frequency-Selective Distortion 939 14.5.2 Mitigation to Combat Fast-Fading Distortion 942 14.5.3 Mitigation to Combat Loss in SNR 942 14.5.4 Diversity Techniques 944 14.5.5 Modulation Types for Fading Channels 946 14.5.6 The Role of an Interleaver 947 Summary of the Key Parameters Characterizing Fading Channels 951 14.6.1 Fast-Fading Distortion: Case 1 951 14.6.2 Frequency-Selective Fading Distortion: Case 2 952 14.6.3 Fast-Fading and Frequency-Selective Fading Distortion: Case 3 953 Applications: Mitigating the Effects of Frequency-Selective Fading 955 14.7.1 The Viterbi Equalizer as Applied to GSM 955 14.7.2 The Rake Receiver Applied to Direct-Sequence Spread-
Spectrum (DS/SS) Systems 958 Conclusion 960 xix
15 THE ABCs OF OFDM (ORTHOGONAL FREQUENCY- DIVISION MULTIPLEXING) 15.1 15.2 15.3 15.4 15.5 15.6 15.7 15.8 15.9 15.10 15.11 15.12 15.13 15.14 15.15 15.16 15.17 15.18 XX 971 What Is OFDM? 972 Why OFDM? 972 Getting Started with OFDM 973 Our Wish List (Preference for Flat Fading and Slow Fading) 974 15.4.1 OFDM’s Most Important Contribution to Communications over Multipath Channels 975 Conventional Multi-Channel FDM versus Multi-Channel OFDM 976 The History of the Cyclic Prefix (CP) 977 15.6.1 Examining the Lengthened Symbol in OFDM 978 15.6.2 The Length of the CP 979 OFDM System Block Diagram 979 Zooming in on the IDFT 981 An Example of OFDM Waveform Synthesis 981 Summarizing OFDM Waveform Synthesis 983 Data Constellation Points Distributed over the Subcarrier Indexes 984 15.11.1 Signal Processing in the OFDM Receiver 986 15.11.2 OFDM Symbol-Time Duration 986 15.11.3 Why DC Is Not Used as a Subcarrier in Real Systems 987 Hermitian Symmetry 987 How Many Subcarriers Are Needed? 989 The Importance of the Cyclic Prefix (CP) in OFDM 989 15.14.1 Properties of Continuous and Discrete Fourier Transforms 990 15.14.2 Reconstructing the OFDM Subcarriers 991 15.14.3 A Property of the Discrete Fourier Transform (DFT) 992 15.14.4 Using Circular Convolution for Reconstructing an OFDM Subcarrier 993 15.14.5 The Trick That Makes Linear Convolution Appear Circular 994 An Early OFDM Application: Wi-Fi Standard 802.11a 997 15.15.1 Why the Transform Size N Needs to Be Larger Than the Number of Subcarriers 999 Cyclic Prefix (CP) and Tone Spacing 1000 Long-Term Evolution (LTE) Use of OFDM 1001
15.17.1 LTE Resources: Grid, Block, and Element 1002 15.17.2 OFDM Frame in LTE 1003 Drawbacks of OFDM 1006 15.18.1 Sensitivity to Doppler 1006 15.18.2 Peak-to-Average Power Ratio (PAPR) and SC-OFDM 1006 15,18.3 Motivation for Reducing PAPR 1007 Contents
15.19 15.20 16 Single-Carrier OFDM (SC-OFDM) for Improved PAPR Over Standard OFDM 1007 15.19.1 SC-OFDM Signals Have Short Mainlobe Durations 1010 15.19.2 Is There an Easier Way to Implement SC-OFDM? 1011 Conclusion 1012 THE MAGIC OF MIMO (MULTIPLE INPUT/MULTIPLE OUTPUT) 16.1 16.2 16.3 16.4 16.5 16.6 16.7 Contents 1017 What is MIMO? 1018 16.1.1 MIMO Historical Perspective 1019 16.1.2 Vectors and Phasors 1019 16.1.3 MIMO Channel Model 1020 Various Benefits of Multiple Antennas 1023 16.2.1 Array Gain 1023 16.2.2 Diversity Gain 1023 16.2.3 SIMO Receive Diversity Example 1026 16.2.4 MISO Transmit Diversity Example 1027 16.2.5 Two-Time Interval MISO Diversity Example 1028 16.2.6 Coding Gain 1029 16.2.7 Visualization ofArray Gain, Diversity Gain, and Coding Gain 1029 Spatial Multiplexing 1031 16.3.1 Basic Idea of MIMO-Spatial Multiplexing (MIMO-SM) 1031 16.3.2 Analogy Between MIMO-SM and CDMA 1033 16.3.3 When Only the Receiver Has Channel-State Information (CSI) 1033 16.3.4 Impact of the Channel Model 1034 16.3.5 MIMO and OFDM Form a Natural Coupling 1036 Capacity Performance 1037 16.4.1 Deterministic Channel Modeling 1038 16.4.2 Random Channel Models 1040 Transmitter Channel-State Information (CSI) 1042 16.5.1 Optimum Power Distribution 1044 Space-Time Coding 1047 16.6.1 Block Codes in MIMO Systems 1047 16.6.2 Trellis Codes in MIMO Systems 1050 MIMO Trade-Offs 1051 16.7.1 Fundamental Trade-Off 1051 16.7.2 Trade-Off Yielding Greater Robustness for PAM and QAM 1052 16.7.3 Trade-Off Yielding Greater Capacity for PAM and QAM 1053 16.7.4 Tools for Trading Off Multiplexing Gain and
Diversity Gain 1054 xxi
16.8 16.9 Multi-User MIMO (MU-MIMO) 1058 16.8.1 What Is MU-MIMO? 1059 16.8.2 SU-MIMO and MU-MIMO Notation 1059 16.8.3 A Real Shift in MIMO Thinking 1061 16.8.4 MU-MIMO Capacity 1067 16.8.5 Sum-Rate Capacity Comparison for Various Precoding Strategies 1081 16.8.6 MU-MIMO Versus SU-MIMO Performance 1082 Conclusion 1083 Index 1089 THE FOLLOWING ELEMENTSWILL BE ONLINE ONLY 17 Encryption and Decryption A A Review of Fourier Techniques В Fundamentals of Statistical Decision Theory C Response of a Correlator to White Noise D Often-Used Identities E 5-Domain, Z-Domain, and Digital Filtering F OFDM Symbol Formation with an A-Point Inverse Discrete Fourier Transform (IDFT) G List of Symbols These online elements can be found at informit.com/ title/9780134588568 xxii Contents
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Contents at a Glance Preface xxiii Acknowledgments xxvii About the Authors xxix 1 Signals and Spectra 2 Formatting and Baseband Modulation 53 3 Baseband Demodulation/Detection 99 4 Bandpass Modulation and Demodulation/Detection 161 5 Communications Link Analysis 235 6 Channel Coding: Part 1: Waveform Codes and Block Codes 7 8 1 297 Channel Coding: Part 2: Convolutional Codes and Reed-Solomon Codes 375 Channel Coding: Part 3: Turbo Codes and Low-Density Parity Check (LDPC) Codes 471 v
Modulation and Coding Trade-Offs 549 10 Synchronization 619 11 Multiplexing and Multiple Access 681 12 Spread-Spectrum Techniques 741 13 Source Coding 823 14 Fading Channels 905 15 The ABCs of OFDM (Orthogonal FrequencyDivision Multiplexing) 971 9 16 The Magic of Mimo (Multiple Input/Multiple Output) 1017 1089 Index THE FOLLOWING ELEMENTS WILL BE ONLINE ONLY 17 Encryption and Decryption A A Review of Fourier Techniques В Fundamentals of Statistical Decision Theory C Response of a Correlator to White Noise D Often-Used Identities E S-Domain, Z-Domain, and Digital Filtering F OFDM Symbol Formation with an A-Point Inverse Discrete Fourier Transform (IDFT) G List of Symbols These online elements can be found at informit.com/title/ 9780134588568 vi Contents at a Glance
Contents Preface xxiii Acknowledgments xxvii About the Authors xxix 1 SIGNALS AND SPECTRA 1.1 1.2 1.3 1.4 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 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 Spectral Density 13 1.3.1 Energy Spectral Density 13 1.3.2 Power Spectral Density 14 Autocorrelation 15 1.4.1 Autocorrelation of an Energy Signal 10 1.4.2 Autocorrelation of a Periodic (Power) Signal 16 1
1.5 1.6 1.7 1.8 2 FORMATTING AND BASEBAND MODULATION 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 viii 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 ofa Random Process 22 1.5.5 Noise in Communication Systems 27 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 Bandwidth of Digital Data 41 1.7.1 Baseband Versus Bandpass 41 ' 1.7.2 The Bandwidth Dilemma 44 Conclusion 47 53 Baseband Systems 54 Formatting Textual Data (Character Coding) 55 Messages, Characters, and Symbols 55 2.3.1 Example of Messages, Characters, and Symbols 56 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 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 Pulse Code Modulation 73 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 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 Correlative Coding 88 2.9.1 Duobinary Signaling 88 2.9.2 Duobinary Decoding 89 Contents
2.10 3 BASEBAND DEMODULATION/DETECTION 3.1 3.2 3.3 3.4 3.5 4 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 Conclusion 94 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 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 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 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 A daptive Equalization 152 3.4.5 Filter Update Rate 155 Conclusion 156 BANDPASS MODULATION AND DEMODULATION/DETECTION 4.1 4.2 Contents 99 161 Why Modulate? 162 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 ix
4.3 4.4 4.5 4.6 4.7 4.8 4.9 4.10 x Detection of Signals in Gaussian Noise 169 4.3.1 Decision Regions 169 4.3.2 Correlation Receiver 170 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 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 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 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 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 ΜFSK Signaling 217 Symbol Error Performance for M-ary Systems (Μ 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 Conclusion 228 Contents
5 COMMUNICATIONS LINK ANALYSIS 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6 What the System Link Budget Tells the System Engineer 236 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 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 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 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 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 Satellite Repeaters 283 5.7.1 Nonregenerative Repeaters 283 5.7.2 Nonlinear Repeater Amplifiers 288 System Ћade-Offs 289 Conclusion 290 CHANNEL CODING: PART 1: WAVEFORM CODES AND BLOCK CODES 6.1 6.2 Contents 235 297 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 Types of Error Control 307 6.2.1 Terminal Connectivity 307 6.2.2 Automatic Repeat Request 307 xi
6.3 6.4 6.5 6.6 6.7 6.8 6.9 7 CHANNEL CODING: PART 2: CONVOLUTIONAL CODES AND REED-SOLOMON CODES 375 7.1 xii 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 Linear Block Codes 320 6.4.1 VectorSpaces 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 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 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 344 6.6.4 Error Detection Versus Error Correction Trade-Offs 345 6.6.5 The Standard Array Provides Insight 347 Cyclic Codes 349 6.71 Algebraic Structure of Cyclic Codes 349 6.7.2 Binary Cyclic Code Properties 351 6.7.3 Encoding in Systematic Form 352 6.7.4 Circuit for Dividing Polynomials 353 6.7.5 Systematic Encoding with an (n - k)-Stage Shift Register 356 6.7.6 Error Detection with an (n - k)-Stage Shift Register 358 Well-Known Block Codes 359 6.8.1 Hamming Codes 359 6.8.2 Extended Golay Code 361 6.8.3 BCH Codes 363 Conclusion 367 Convolutional Encoding 376 Contents
7.2 7.3 7.4 7.5 7.6 Ί.Ί 7.8 7.9 Contents Convolutional Encoder Representation 378 7.2.1 Connection Representation 378 7.2.2 State Representation and the State Diagram 382 7.2.3 The Tree Diagram 385 7.2.4 The Trellis Diagram 385 Formulation of the Convolutional Decoding Problem 388 7.3.1 Maximum Likelihood Decoding 388 7.3.2 Channel Models: Hard Versus Soft Decisions 390 7.3.3 The Viterbi Convolutional Decoding Algorithm 394 7.3.4 An Example of Viterbi Convolutional Decoding 394 7.3.5 Decoder Implementation 398 7.3.6 Path Memory and Synchronization 401 Properties of Convolutional Codes 402 7.4.1 Distance Properties of Convolutional Codes 402 7.4.2 Systematic and Nonsystematic Convolutional Codes 406 7.4.3 Catastrophic Error Propagation in Convolutional Codes 407 7.4.4 Performance Bounds for Convolutional Codes 408 7.4.5 Coding Gain 409 7.4.6 Best-Known Convolutional Codes 411 7.4.7 Convolutional Code Rate Trade-Off 413 7.4.8 Soft-Decision Viterbi Decoding 413 Other Convolutional Decoding Algorithms 415 7.5.1 Sequential Decoding 415 7.5.2 Comparisons and Limitations of Viterbi and Sequential Decoding 418 7.5.3 Feedback Decoding 419 Reed-Solomon Codes 421 7.6.1 Reed-Solomon Error Probability 423 7.6.2 Why R-S Codes Perform Well Against Burst Noise 426 7.6.3 R-S Performance as a Function of Size, Redundancy, and Code Rate 426 7.6.4 Finite Fields 429 7.6.5 Reed-Solomon Encoding 435 7.6.6 Reed-Solomon Decoding 439 Interleaving and Concatenated Codes 446 7.7.1 Block Interleaving 449 7.7.2 Convolutional Interleaving 452 7.7.3 Concatenated Codes 453 Coding and Interleaving Applied
to the Compact Disc Digital Audio System 454 7.8.1 CIRC Encoding 456 7.8.2 CIRC Decoding 458 7.8.3 Interpolation and Muting 460 Conclusion 462 xiii
8 CHANNEL CODING: PART 3: TURBO CODES AND LOW-DENSITY PARITY CHECK (LDPC) CODES 471 Turbo Codes 472 8.1.1 Turbo Code Concepts 472 8.1.2 Log-Likelihood A lgebra 476 Product Code Example 477 8.1.3 8.1.4 Encoding with Recursive Systematic Codes 484 A Feedback Decoder 489 8.1.5 8.1.6 The MAP Algorithm 493 8.1.7 MAP Decoding Example 499 8.2 Low-Density Parity Check (LDPC) Codes 504 8.2.1 Background and Overview 504 8.2.2 The Parity-Check Matrix 505 8.2.3 Finding the Best-Performing Codes 507 8.2.4 Decoding:An Overview 509 Mathematical Foundations 514 8.2.5 8.2.6 Decoding in the Probability Domain 518 8.2.7 Decoding in the Logarithmic Domain 526 8.2.8 Reduced-Complexity Decoders 531 8.2.9 LDPC Performance 532 8.2.10 Conclusion 535 Appendix 8A: The Sum of Log-Likelihood Ratios 535 Appendix 8B: Using Bayes’Theorem to Simplify the Bit Conditional Probability 537 Appendix 8C: Probability that a Binary Sequence Contains an Even Number of Ones 537 Appendix 8D: Simplified Expression for the Hyperbolic Tangent of the Natural Log of a Ratio of Binary Probabilities 538 Appendix 8E: Proof that ф(х) = ф֊1(х) 538 Appendix 8F: Bit Probability Initialization 539 8.1 9 MODULATION AND CODING TRADE-OFFS 9.1 9.2 9.3 9.4 9.5 xlv Goals of the Communication System Designer 550 Error-Probability Plane 550 Nyquist Minimum Bandwidth 552 Shannon-Hartley Capacity Theorem 554 9.4.1 Shannon Limit 556 9.4.2 Entropy 557 9.4.3 Equivocation and Effective Transmission Rate Bandwidth-Efficiency Plane 562 9.5.1 Bandwidth Efficiency ofMPSK and MFSK Modulation 563 549 560 Contents
Analogies Between the Bandwidth-Efficiency and Error-Probability Planes 564 Modulation and Coding Trade-Offs 565 Defining, Designing, and Evaluating Digital Communication Systems 566 9.7.1 M-ary Signaling 567 9.7.2 Bandwidth-Limited Systems 568 9.7.3 Power-Limited Systems 569 9.7.4 Requirements for MPSК and MFSK Signaling 570 9.7.5 Bandwidth-Limited Uncoded System Example 571 9.7.6 Power-Limited Uncoded System Example 573 9.7.7 Bandwidth-Limited and Power-Limited Coded System Example 575 Bandwidth-Efficient Modulation 583 9.8.1 QPSK and Offset QPSK Signaling 583 9.8.2 Minimum-Shift Keying 587 9.8.3 Quadrature Amplitude Modulation 591 Trellis-Coded Modulation 594 9.9.1 The Idea Behind Trellis-Coded Modulation 595 9.9.2 TCM Encoding 597 9.9.3 TCM Decoding 601 9.9.4 Other Trellis Codes 604 9.9.5 Trellis-Coded Modulation Example 606 9.9.6 Multidimensional Trellis-Coded Modulation 610 Conclusion 610 9.5.2 9.6 9.7 9.8 9.9 9.10 10 SYNCHRONIZATION 10.1 10.2 10.3 Contents 619 Receiver Synchronization 620 10.1.1 Why We Must Synchronize 620 10.1.2 Alignment at the Waveform Level and Bit Stream Level 620 10.1.3 Carrier-Wave Modulation 620 10.1.4 Carrier Synchronization 621 10.1.5 Symbol Synchronization 624 10.1.6 Eye Diagrams and Constellations 625 Synchronous Demodulation 626 10.2.1 Minimizing Energy in the Difference Signal 628 10.2.2 Finding the Peak of the Correlation Function 629 10.2.3 The Basic Analog Phase-Locked Loop (PLL) 631 10.2.4 Phase-Locking Remote Oscillators 631 10.2.5 Estimating Phase Slope (Frequency) 633 Loop Filters, Control Circuits, and Acquisition 634 10.3.1 How
Many Loop Filters Are There in a System? 634 10.3.2 The Key Loop Filters 634 XV
10.4 10.5 10.6 10.7 11 MULTIPLEXING AND MULTIPLE ACCESS 11.1 11.2 11.3 xvi 10.3.3 Why We Want R Times R-dot 634 10.3.4 The Phase Error S-Curve 636 Phase-Locked Loop Timing Recovery 637 10.4.1 Recovering Carrier Timing from a Modulated Waveform 637 10.4.2 Classical Timing Recovery Architectures 638 10.4.3 Timing-Error Detection: Insight from the Correlation Function 641 10.4.4 Maximum-Likelihood Timing-Error Detection 642 10.4.5 Polyphase Matched Filter and Derivative Matched Filter 643 10.4.6 Approximate ML Timing Recovery PLL for a 32-Path PLL 647 Frequency Recovery Using a Frequency-Locked Loop(FLL) 652 10.5.1 Band-Edge Filters 654 10.5.2 Band-Edge Filter Non-Data-Aided Timing Synchronization 660 Effects of Phase and Frequency Offsets 664 10.6.1 Phase Offset and No Spinning: Effect on Constellation 665 10.6.2 Slow Spinning Effect on Constellation 667 10.6.3 Fast Spinning Effect on Constellation 670 Conclusion 672 681 Allocation of the Communications Resource 682 11.1.1 Frequency-Division Multiplexing/Multiple Access 683 11.1.2 Time-Division Multiplexing/Multiple Access 688 11.1.3 Communications Resource Channelization 691 11.1.4 Performance Comparison ofFDMA and TDMA 692 11.1.5 Code-Division Multiple Access 695 11.1.6 Space-Division and Polarization-Division Multiple Access 698 Multiple-Access Communications System and Architecture 700 11.2.1 Multiple-Access Information Flow 701 11.2.2 Demand-Assignment Multiple Access 702 Access Algorithms 702 11.3.1 ALOHA 702 11.3.2 Slotted ALOHA 705 11.3.3 Reservation ALOHA 706 11.3.4 Performance Comparison of S-ALOHA and R-ALOHA 708
11.3.5 Polling Techniques 710 Contents
11.4 11.5 11.6 12 Multiple-Access Techniques Employed with INTELSAT 712 11.4.1 Preassigned FDM/FM/FDMA or MCPC Operation 713 11.4.2 MCPC Modes ofAccessing an INTELSAT Satellite 713 11.4.3 SPADE Operation 716 11.4.4 TDMA in INTELSAT 721 11.4.5 Satellite-Switched TDMA in INTELSAT 727 Multiple-Access Techniques for Local Area Networks 731 11.5.1 Carrier-Sense Multiple-Access Networks 731 11.5.2 Token-Ring Networks 733 11.5.3 Performance Comparison of CSMA/CD and Token-Ring Networks 734 Conclusion 736 SPREAD-SPECTRUM TECHNIQUES 12.1 12.2 12.3 12.4 12.5 12.6 Contents 741 Spread-Spectrum Overview 742 12.1.1 The Beneficial Attributes of Spread-Spectrum Systems 742 12.1.2 A Catalog of Spreading Techniques 746 12.1.3 Model for Direct-Sequence Spread-Spectrum Interference Rejection 747 12.1.4 Historical Background 748 Pseudonoise Sequences 750 12.2.1 Randomness Properties 750 12.2.2 Shift Register Sequences 750 12.2.3 PN Autocorrelation Function 752 Direct-Sequence Spread-Spectrum Systems 753 12.3.1 Example of Direct Sequencing 755 12.3.2 Processing Gain and Performance 756 Frequency-Hopping Systems 759 12.4.1 Frequency-Hopping Example 761 12.4.2 Robustness 762 12.4.3 Frequency Hopping with Diversity 762 12.4.4 Fast Hopping Versus Slow Hopping 763 12.4.5 FFH/MFSK Demodulator 765 12.4.6 Processing Gain 766 Synchronization 766 12.5.1 Acquisition 767 12.5.2 Tracking 772 Jamming Considerations 775 12.6.1 The Jamming Game 775 12.6.2 Broadband Noise Jamming 780 12.6.3 Partial-Band Noise Jamming 781 12.6.4 Multiple-Tone Jamming 783 12.6.5 Pulse Jamming 785 xvii
12.7 12.8 12.9 13 SOURCE CODING 13.1 13.2 13.3 13.4 13.5 13.6 13.7 xviii 12.6.6 Repeat-Back Jamming 787 12.6.7 BLADES System 788 Commercial Applications 789 12.7.1 Code-Division Multiple Access 789 12.7.2 Multipath Channels 792 12.7.3 The FCC Part 15 Rules for Spread-Spectrum Systems 12.7.4 Direct Sequence Versus Frequency Hopping 794 Cellular Systems 796 12.8.1 Direct-Sequence CDMA 796 12.8.2 Analog FM Versus TDMA Versus CDMA 799 12.8.3 Interference-Limited Versus Dimension-Limited Systems 801 12.8.4 IS-95 CDMA Digital Cellular System 803 Conclusion 814 793 823 Sources 824 13.1.1 Discrete Sources 824 13.1.2 Waveform Sources 829 Amplitude Quantizing 830 13.2.1 Quantizing Noise 833 13.2.2 Uniform Quantizing 836 13.2.3 Saturation 840 13.2.4 Dithering 842 13.2.5 Nonuniform Quantizing 845 Pulse Code Modulation 849 13.3.1 Differential Pulse Code Modulation 850 13.3.2 One-Tap Prediction 853 13.3.3 N-Tap Prediction 854 13.3.4 Delta Modulation 856 13.3.5 Σ-Δ Modulation 858 13.3.6 ^-IsA-to-D Converter (ADC) 862 13.3.7 Σ-Δ D-to-A Converter (DAC) 863 Adaptive Prediction 865 13.4.1 Forward Adaptation 865 13.4.2 Synthesis/Analysis Coding 866 Block Coding 868 13.5.1 Vector Quantizing 868 Transform Coding 870 13.6.1 Quantization for Transform Coding 872 13.6.2 Subband Coding 872 Source Coding for Digital Data 873 13.7.1 Properties of Codes 875 Contents
13.8 13.9 14 13.7.2 Huffman Code 877 13.7.3 Run-Length Codes 880 Examples of Source Coding 884 13.8.1 Audio Compression 884 13.8.2 Image Compression 889 Conclusion 898 FADING CHANNELS 14.1 14.2 14.3 14.4 14.5 14.6 14.7 14.8 Contents 905 The Challenge of Communicating over Fading Channels 906 Characterizing Mobile-Radio Propagation 907 14.2.1 Large-Scale Fading 912 14.2.2 Small-Scale Fading 914 Signal Time Spreading 918 14.3.1 Signal Time Spreading Viewed in the Time-Delay Domain 918 14.3.2 Signal Time Spreading Viewed in the Frequency Domain 920 14.3.3 Examples of Flat Fading and Frequency-Selective Fading 924 Time Variance of the Channel Caused by Motion 926 14.4.1 Time Variance Viewed in the Time Domain 926 14.4.2 Time Variance Viewed in the Doppler-Shift Domain 929 14.4.3 Performance over a Slow- and Flat-Fading Rayleigh Channel 935 Mitigating the Degradation Effects of Fading 937 14.5.1 Mitigation to Combat Frequency-Selective Distortion 939 14.5.2 Mitigation to Combat Fast-Fading Distortion 942 14.5.3 Mitigation to Combat Loss in SNR 942 14.5.4 Diversity Techniques 944 14.5.5 Modulation Types for Fading Channels 946 14.5.6 The Role of an Interleaver 947 Summary of the Key Parameters Characterizing Fading Channels 951 14.6.1 Fast-Fading Distortion: Case 1 951 14.6.2 Frequency-Selective Fading Distortion: Case 2 952 14.6.3 Fast-Fading and Frequency-Selective Fading Distortion: Case 3 953 Applications: Mitigating the Effects of Frequency-Selective Fading 955 14.7.1 The Viterbi Equalizer as Applied to GSM 955 14.7.2 The Rake Receiver Applied to Direct-Sequence Spread-
Spectrum (DS/SS) Systems 958 Conclusion 960 xix
15 THE ABCs OF OFDM (ORTHOGONAL FREQUENCY- DIVISION MULTIPLEXING) 15.1 15.2 15.3 15.4 15.5 15.6 15.7 15.8 15.9 15.10 15.11 15.12 15.13 15.14 15.15 15.16 15.17 15.18 XX 971 What Is OFDM? 972 Why OFDM? 972 Getting Started with OFDM 973 Our Wish List (Preference for Flat Fading and Slow Fading) 974 15.4.1 OFDM’s Most Important Contribution to Communications over Multipath Channels 975 Conventional Multi-Channel FDM versus Multi-Channel OFDM 976 The History of the Cyclic Prefix (CP) 977 15.6.1 Examining the Lengthened Symbol in OFDM 978 15.6.2 The Length of the CP 979 OFDM System Block Diagram 979 Zooming in on the IDFT 981 An Example of OFDM Waveform Synthesis 981 Summarizing OFDM Waveform Synthesis 983 Data Constellation Points Distributed over the Subcarrier Indexes 984 15.11.1 Signal Processing in the OFDM Receiver 986 15.11.2 OFDM Symbol-Time Duration 986 15.11.3 Why DC Is Not Used as a Subcarrier in Real Systems 987 Hermitian Symmetry 987 How Many Subcarriers Are Needed? 989 The Importance of the Cyclic Prefix (CP) in OFDM 989 15.14.1 Properties of Continuous and Discrete Fourier Transforms 990 15.14.2 Reconstructing the OFDM Subcarriers 991 15.14.3 A Property of the Discrete Fourier Transform (DFT) 992 15.14.4 Using Circular Convolution for Reconstructing an OFDM Subcarrier 993 15.14.5 The Trick That Makes Linear Convolution Appear Circular 994 An Early OFDM Application: Wi-Fi Standard 802.11a 997 15.15.1 Why the Transform Size N Needs to Be Larger Than the Number of Subcarriers 999 Cyclic Prefix (CP) and Tone Spacing 1000 Long-Term Evolution (LTE) Use of OFDM 1001
15.17.1 LTE Resources: Grid, Block, and Element 1002 15.17.2 OFDM Frame in LTE 1003 Drawbacks of OFDM 1006 15.18.1 Sensitivity to Doppler 1006 15.18.2 Peak-to-Average Power Ratio (PAPR) and SC-OFDM 1006 15,18.3 Motivation for Reducing PAPR 1007 Contents
15.19 15.20 16 Single-Carrier OFDM (SC-OFDM) for Improved PAPR Over Standard OFDM 1007 15.19.1 SC-OFDM Signals Have Short Mainlobe Durations 1010 15.19.2 Is There an Easier Way to Implement SC-OFDM? 1011 Conclusion 1012 THE MAGIC OF MIMO (MULTIPLE INPUT/MULTIPLE OUTPUT) 16.1 16.2 16.3 16.4 16.5 16.6 16.7 Contents 1017 What is MIMO? 1018 16.1.1 MIMO Historical Perspective 1019 16.1.2 Vectors and Phasors 1019 16.1.3 MIMO Channel Model 1020 Various Benefits of Multiple Antennas 1023 16.2.1 Array Gain 1023 16.2.2 Diversity Gain 1023 16.2.3 SIMO Receive Diversity Example 1026 16.2.4 MISO Transmit Diversity Example 1027 16.2.5 Two-Time Interval MISO Diversity Example 1028 16.2.6 Coding Gain 1029 16.2.7 Visualization ofArray Gain, Diversity Gain, and Coding Gain 1029 Spatial Multiplexing 1031 16.3.1 Basic Idea of MIMO-Spatial Multiplexing (MIMO-SM) 1031 16.3.2 Analogy Between MIMO-SM and CDMA 1033 16.3.3 When Only the Receiver Has Channel-State Information (CSI) 1033 16.3.4 Impact of the Channel Model 1034 16.3.5 MIMO and OFDM Form a Natural Coupling 1036 Capacity Performance 1037 16.4.1 Deterministic Channel Modeling 1038 16.4.2 Random Channel Models 1040 Transmitter Channel-State Information (CSI) 1042 16.5.1 Optimum Power Distribution 1044 Space-Time Coding 1047 16.6.1 Block Codes in MIMO Systems 1047 16.6.2 Trellis Codes in MIMO Systems 1050 MIMO Trade-Offs 1051 16.7.1 Fundamental Trade-Off 1051 16.7.2 Trade-Off Yielding Greater Robustness for PAM and QAM 1052 16.7.3 Trade-Off Yielding Greater Capacity for PAM and QAM 1053 16.7.4 Tools for Trading Off Multiplexing Gain and
Diversity Gain 1054 xxi
16.8 16.9 Multi-User MIMO (MU-MIMO) 1058 16.8.1 What Is MU-MIMO? 1059 16.8.2 SU-MIMO and MU-MIMO Notation 1059 16.8.3 A Real Shift in MIMO Thinking 1061 16.8.4 MU-MIMO Capacity 1067 16.8.5 Sum-Rate Capacity Comparison for Various Precoding Strategies 1081 16.8.6 MU-MIMO Versus SU-MIMO Performance 1082 Conclusion 1083 Index 1089 THE FOLLOWING ELEMENTSWILL BE ONLINE ONLY 17 Encryption and Decryption A A Review of Fourier Techniques В Fundamentals of Statistical Decision Theory C Response of a Correlator to White Noise D Often-Used Identities E 5-Domain, Z-Domain, and Digital Filtering F OFDM Symbol Formation with an A-Point Inverse Discrete Fourier Transform (IDFT) G List of Symbols These online elements can be found at informit.com/ title/9780134588568 xxii Contents |
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| author | Sklar, Bernard ca. 20./21- Jh Harris, Fredric J. |
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| discipline | Elektrotechnik / Elektronik / Nachrichtentechnik |
| discipline_str_mv | Elektrotechnik / Elektronik / Nachrichtentechnik |
| edition | Third edition |
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| id | DE-604.BV047115641 |
| illustrated | Illustrated |
| index_date | 2024-07-03T16:27:24Z |
| indexdate | 2024-07-10T09:03:04Z |
| institution | BVB |
| isbn | 9780134588568 0134588568 |
| language | English |
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| physical | xxix, 1105 Seiten Illustrationen, Diagramme |
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| spelling | Sklar, Bernard ca. 20./21- Jh. Verfasser (DE-588)1264158122 aut Digital communications fundamentals and applications Bernard Sklar ; Fred Harris Third edition [Boston, MA] Pearson [2021] xxix, 1105 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier 1. Signals and Spectra ; 2. Formatting and Baseband Modulation ; 3. Baseband Demodulation/Detection ; 4. Bandpass Modulation and Demodulation/Detection ; 5. Communications Link Analysis ; 6. Channel Coding I: Waveform Codes and Block Codes ; 7. Channel Coding II: Convolutional Codes and Reed-Solomon Codes ; 8. Channel Coding III: Turbo Codes and Low-Density Parity Check (LDPC) Codes ; 9. Modulation and Coding Trade offs ; 10. Synchronization ; 11. Multiplexing and Multiple Access ; 12. Spread Spectrum Techniques ; 13. Source Coding ; 14. Fading Channels ; 15. The ABCs of OFDM ; 16. The Magic of MIMO ; bisacsh / TECHNOLOGY & ENGINEERING / Telecommunications Digitale Nachrichtentechnik (DE-588)4224275-7 gnd rswk-swf Digitale Signalverarbeitung (DE-588)4113314-6 gnd rswk-swf Digitale Nachrichtentechnik (DE-588)4224275-7 s Digitale Signalverarbeitung (DE-588)4113314-6 s DE-604 Harris, Fredric J. Verfasser (DE-588)1232423394 aut Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032522041&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Sklar, Bernard ca. 20./21- Jh Harris, Fredric J. Digital communications fundamentals and applications bisacsh / TECHNOLOGY & ENGINEERING / Telecommunications Digitale Nachrichtentechnik (DE-588)4224275-7 gnd Digitale Signalverarbeitung (DE-588)4113314-6 gnd |
| subject_GND | (DE-588)4224275-7 (DE-588)4113314-6 |
| title | Digital communications fundamentals and applications |
| title_auth | Digital communications fundamentals and applications |
| title_exact_search | Digital communications fundamentals and applications |
| title_exact_search_txtP | Digital communications fundamentals and applications |
| title_full | Digital communications fundamentals and applications Bernard Sklar ; Fred Harris |
| title_fullStr | Digital communications fundamentals and applications Bernard Sklar ; Fred Harris |
| title_full_unstemmed | Digital communications fundamentals and applications Bernard Sklar ; Fred Harris |
| title_short | Digital communications |
| title_sort | digital communications fundamentals and applications |
| title_sub | fundamentals and applications |
| topic | bisacsh / TECHNOLOGY & ENGINEERING / Telecommunications Digitale Nachrichtentechnik (DE-588)4224275-7 gnd Digitale Signalverarbeitung (DE-588)4113314-6 gnd |
| topic_facet | bisacsh / TECHNOLOGY & ENGINEERING / Telecommunications Digitale Nachrichtentechnik Digitale Signalverarbeitung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032522041&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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