Digital Communication Systems

Contents Preface 1. Introduction 1.1 Some History 1.2 Some Definitions Analog Sources and Signals Digital Sources and Signals Signal Classifications Carrier Modulation 1.3 Digital System Block Diagram and Book Survey Transmitting Station Channel Receiving Station 1.4 Simple Baseband System for Reference References 2. Sampling Principles 2.0 Introduction 2.1 Sampling Theorems for Lowpass Nonrandom Signals Time Domain Sampling Theorem A Network View of Sampling Theorem Aliasing Frequency Domain Sampling Theorem 2.2 Sampling Theorem for Lowpass Random Signals 2.3 Practical Sampling Methods Natural Sampling Flat-Top Sampling 2.4 Practical Sampling with Arbitrary Pulse Shapes 2.5 Practical Signal Recovery Methods Signal Recovery by Zero-Order Sample-Hold First-Order Sample-Hold Higher-Order Sample Hold 2.6 Sampling Theorems for Bandpass Signals Direct Sampling of Bandpass Signals Quadrature Sampling of Bandpass Signals Bandpass Sampling Using Hilbert Transforms Sampling of Bandpass Random Signals 2.7 Other Sampling Theorems Higher-Order Sampling Defined Second-Order Sampling of Lowpass Signals Second-Order Sampling of Bandpass Signals Lowpass Sampling Theorem In Two Dimensions 2.8 Time Division Multiplexing The Basic Concept Synchronization 2.9 Summary and Discussion References Problems 3. Baseband Digital Waveforms 3.0 Introduction 3.1 Digital Conversion of Analog Messages Quantization of Signals Quantization Error and Its Performance Limitation 3.2 Direct Quantizers for A/D Conversion Uniform Quantizers - Nonoptimum Optimum Quantizers 3.3 Companded Quantizers Companders and Their Optimization Logarithmic Companding 3.4 Source Encoding of Digital Messages Natural Binary Encoding Gray Encoding M-ary Encoding Source Information and Entropy Optimum Binary Source Encoding Source Extension Other Encoding Methods 3.5 Channel Encoding Fundamentals Block Codes Block Codes for Single Error Correction Hamming Block Codes Decoding of Block Codes Convolutional Codes - Tree Diagrams Convolutional Codes - Trellis Diagrams Convolutional Codes - State Diagrams Viterbi Decoding of Convolutional Codes 3.6 Waveform Formatting of Digital Signals Unipolar Waveform Polar Waveform Bipolar Waveform Manchester Waveform Differential Waveform Duobinary Waveform Modified Duobinary Waveform Miller Waveform M-ary Waveform 3.7 Spectral Characteristics of Digital Formats Power Spectrum Unipolar Fromat Polar Format Bipolar Format Manchester Format Duobinary Format Modified Duobinary Format Miller Format 3.8 Time Multiplexing of Binary Digital Wvaforms AT&T D-Type Synchronous Multiplexers Hierarchies of Digital Multiplexing Asynchronous Multiplexing Time Division Multiple Access Other TDM Methods 3.9 Summary and Discussion References Problems 4. Baseband Digital Systems 4.0 Introduction 4.1 Requirements and Models for System Optimization Basic Binary System Noise Model Signal Model Optimization Criterion 4.2 Optimum Binary Systems Correlation Receiver Implementaion Matched Filter Implementation Optimum System Output Noise Power Optimum system Output Signal Levels 4.3 Optimum Binary System Error Probabilities Equal Probability Messages Equal Probability, Equal Energy Signals Equal Probability, Antipodal Signals 4.4 Binary Pulse Code Modulation Overall PCM System Unipolar, Polar, and Manchester Formats Error Probabilities Effect of Differential Coding Finite Channel Bandwidth 4.5 Noise Performance of Binary Systems Performance for Digital Messages with Coding Performance for Analog Messages Above Threshold (PCM) Effect of Receiver Noise in PCM Performance Near Threshold in PCM Threshold Calculation 4.6 Intersymbol Interference Pulse Shaping to Reduce Intersymbol Interference Partial Response Signalling For Interference Control Generalized Partial Response Signalling Equalization Methods to Control Intersymbol Interference 4.7 Optimum Duobinary System System Optimum Thresholds Optimum Transmit and Receive Filters Error Probability 4.8 Optimum Modified Duobinary System 4.9 M-ary PAM System Average Transmitted/Received Power Optimum Thresholds Optimum Receiver Error Probability 4.10 Delta Modulation System Block Diagram Errors and Slope Overload Channel Bandwidth Other Configurations 4.11 Noise Performance of Delta Modulation Performance with Granular Noise Only Performance with Slope Overload Noise Added Effect of Receiver Noise on Performance Comparison of DCM and PCM 4.12 Delta-Sigma Modulation Overload Characteristic Channel Bandwidth Granular Noise Performance Limitation Performance with Receiver Noise Added 4.13 Adaptive Delta Modulatiion System Block Diagram Instantaneous Step-Size Control Syllabic Step-Size Control Quantization Noise Performance of ADM Hybrid Configurations 4.14 Differential PCM DPCM System Block Diagram Channel Bandwidth Performance with Granular Noise Only Performance Comparison with DM and PCM Performance with Slope Overload Noise Added Other System Configurations 4.15 Summary and Discussion References Problems 5. Bandpass Binary Digital Systems 5.0 Introduction 5.1 Optimum Coherent Bandpass Systems Output Signal Levels and Noise Power Probability of Error 5.2 Coherent Amplitude Shift Keying System Implementations ASK Noise Performance Signal Power Spectrum and Bandwidth Local Carrier Generation for Coherent ASK 5.3 Phase Shift Keying Optimum System Spectral Properties of PSK Error Probability of PSK 5.4 Quadrature PSK System for Two Message Sources System for Single Message Source Other Quadrature Modulations: QAM and OQPSK Carrier Recovery in QAM and QPSK 5.5 Coherent Frequency Shift Keying FSK Using Independent Oscillators Continuos Phase FSK Power Spectrum of CPFSK 5.6 Minimum Shift Keying CPFSK Signal Decomposition Parallel MSK Systems - Type I Fast Frequency Shift Keying Parallel MSK - Type II Serial MSK Power Spectrum of MSK Noise Performance of MSK Other MSK Implementations and Comments 5.7 Optimum Noncoherent Bandpass Systems System, Noise, and Signal Definitions Optimum Receiver Decision Rule Correlation Receievr Implementation Matched Filter Implementation 5.8 Noncoherent ASK Noncoherent System and Threshold Bit Error Probability 5.9 Noncoherent FSK System Block Diagram Bit Error Probability 5.10 Differential PSK DPSK System Signals and Noises in DPSK Bit Error Probability 5.11 Differential Detection of FSK and MSK Signals Detector Operation Noise Performance 5.12 Noise Performance Comparisons of Systems 5.13 Summary ans Discussion References Problems 6. M-ary Digital Systems 6.0 Introduction 6.1 Vector Representation of Signals Orthogonal Functions Vector Signals and Signal Space Gram-Schmidt Procedure Signal Energy and Average Power 6.2 Vector Representation of Noise White Noise Case 6.3 Optimization of the M-ary Digital System Signal and Noise Vectors Decision Rule Decision Regions Error Probability Some Signal Constellation Properties 6.4 Optimum Receivers Correlation Receiver Structures Matched Filter Structures 6.5 M-ary Amplitude Shift Keying Signal Constellation System and Its Error Probability 6.6 M-ary Phase Shift Keying Signal Constellation Symbol Error Probability 6.7 Orthogonal Signal Sets Decision Rule and System Error Probability Simplex Signal Sets 6.8 M-ary Frequency Shift Keying 6.9 Quantized Pulse Position Modulation 6.10 Biorthogonal Signal Sets Optimum Receiver Symbol Error Probability QPSK Example 6.11 Vertices of Hypercube Signal Sets System and Its Error Probability Polar NRZ Format Example 6.12 Summary and Discussion References Problems Appendix A. Review of Deterministic Signals and Networks A.0 Introduction A.1 Energy Signals Fourier Transforms Properties of Fourier Transforms Energy and Energy Density Spectrum A.2 Some Useful Energy Signals Rectangular Function Triangular Function A.3 Power Signals Average Power and Power Density Spectrum Time Autocorrelation Function A.4 Periodic Power Signals Fourier Series Impulse Function Spectrum of a Periodic Signal Power spectrum, Autocorrelation Function, and Power A.5 Signal Bandwidth and spectral Extent Three-dB Bandwidth Mean Freqency and RMS Bandwidth A.6 Linear Networks Impulse Response Transfer Function Bandwidth Ideal Networks Energy and Power Spectrums of Response References Problems Appendix B. Review of Random Signal Theory B.0 Introduction B.1 Sample spaces, Events, and Probability Sample Spaces Events Probability Joint Probability Conditional Probability Statistical Independence B.2 Random Variables, Distributions, and Densities Random Variable Distribution Functions Probability Density Functions Conditional Distribution and Density Statistical Independence B.3 Statistical Averages Average of a Function of Random Variables Moments B.4 Gaussian Random Variables B.5 Random Signals and Processes Random Process Concept Correlation Functions Stationarity B.6 Power Density Spectrums Stationary Processes Nonstationary Processes Power B.7 Random Signal Respose of Networks Fundamental Limit Output Correlation Functions Power Density Spectrums B.8 Bandpass Random Processes B.9 Matched Filters Colored Noise Case White Noise Case Refeneces Problems Appendix C. Trigonometric Identities Appendix D. Useful Intergrals and Series Appendix E. Gaussian (Normal) Probability Density and Distribution Functions Appendix F. Table of Error Functions Appendix G. Table of Useful Fourier Transform Pairs Index