PREFACE
Of Digital Communications:Fundamentals and Applications——Second Edition
1 SIGNALS AND SPECTRA
1.1 Digital Communication Signal Processing
1.1.1 Why Digital?
1.1.2 Typical Block Diagram and Transformations
1.1.3 Basic Digital Communication Nomenclature
1.1.4 Digital versus Analog Performance Criteria
1.2 Classification of Signals
1.2.1 Deterministic and Random Signals
1.2.2 Periodic and Nonperiodic Signals
1.2.3 Analog and Discrete Signals
1.2.4 Energy and Power Signals
1.2.5 The Unit Impulse Function
1.3 Spectral Density
1.3.1 Energy Spectral Density
1.3.2 Power Spectral Density
1.4 Autocorrelation
1.4.1 Autocorrelation of an Energy Signal
1.4.2 Autocorrelation of a Periodic (Power) Signal
1.5 Random Signals
1.5.1 Random Variables
1.5.2 Random Processes
1.5.3 Time Averaging and Ergodicity
1.5.4 Power Spectral Density and A utocorrelation of a Random Process
1.5.5 Noise in Communication Systems
1.6 Signal Transmission through Linear Systems
1.6.1 Impulse Response
1.6.2 Frequency Transfer Function
1.6.3 Distortionless Transmission
1.6.4 Signals,Circuits,and Spectra
1.7 Bandwidth of Digital Data
1.7.1 Baseband versus Bandpass
1.7.2 The Bandwidth Dilemma
1.8 Conclusion
2 FORMATTING AND BASEBAND MODULATION
2.1 Baseband Systems
2.2 Formatting Textual Data(Character Coding)
2.3 Messages,Characters,and Symbols
2.3.1 Example of MessagesCharactersand Symbols
2.4 Formatting Analog Information
2.4.1 The Sampling Theorem
2.4.2 Aliasing
2.4.3 Why Oversample?
2.4.4 Signal Interface for a Digital System
2.5 Sources of Corruption
2.5.1 Sampling and Quantizing Effects
2.5.2 Channel Effects
2.5.3 Signal-to-Noise Ratio for Quantized Pulses
2.6 Pulse Code Modulation
2.7 Uniform and Nonuniform Quantization
2.7.1 Statistics of Speech Amplitudes
2.7.2 Nonuniform Quantization
2.7.3 Companding Characteristics
2.8 Differential Pulse-Code Modulation
2.8.1 One-Tap Prediction
2.8.2 N-Tap Prediction
2.8.3 Delta Modulation
2.8.4 Sigma-Delta Modulation
2.8.5 Sigma-Delta A-to-D Converter(ADC)
2.8.6 Sigma-Delta D-to-A Converter(DAC)
2.9 Adaptive Prediction
2.9.1 Forward Adaptation
2.9.2 Synthesis/Analysis Coding
2.10 Baseband Transmission
2.10.1 Waveform Representation of Binary Digits
2.10.2 PCM Waveform Types
2.10.3 Spectral Attributes of PCM Waveforms
2.10.4 Bits per PCM Word and Bits per Symbol
2.10.5 M-ary Pulse-Modulation Waveforms
2.11 Correlative Coding
2.11.1 Duobinary Signaling
2.11.2 Duobinary Decoding
2.11.3 Precoding
2.11.4 Duobinary Equivalent Transfer Function
2.11.5 Comparison of Binary with Duobinary Signaling
2.11.6 Polybinary Signaling
2.12 Conclusion
3 BASEBAND DEMODULATION/DETECTION
3.1 Signals and Noise
3.1.1 Error-Performance Degradation in Communication Systems
3.1.2 Demodulation and Detection
3.1.3 A Vectorial View of Signals and Noise
3.1.4 The Basic SNR Parameter for Digital Communication Systems
3.1.5 Why Eb/No Is a Natural Figure of Merit
3.2 Detection of Binary Signals in Gaussian Noise
3.2.1 Maximum Likelihood Receiver Structure
3.2.2 The Matched Filter
3.2.3 Correlation Realization of the Matched Filter
3.2.4 Optimizing Error Performance
3.2.5 Error Probability Performance of Binary Signaling
3.3 Intersymbol Interference
3.3.1 Pulse Shaping to Reduce ISI
3.3.2 Two Types of Error-Performance Degradation
3.3.3 Demodulation/Detection of Shaped Pulses
3.4 Equalization
3.4.1 Channel Characterization
3.4.2 Eye Pattern
3.4.3 Equalizer Filter Types
3.4.4 Preset and Adaptive Equalization
3.4.5 Filter Update Rate
3.5 Conclusion
4 BANDPASS MODULATION AND DEMODULATION
4.1 Why Modulate?
4.2 Digital Bandpass Modulation Techniques
4.2.1 Phasor Representation of a Sinusoid
4.2.2 Phase Shift Keying
4.2.3 Frequency Shift Keying
4.2.4 Amplitude Shift Keying
4.2.5 Amplitude Phase Keying
4.2.6 Waveform Amplitude Coefficient
4.3 Detection of Signals in Gaussian Noise
4.3.1 Decision Regions
4.3.2 Correlation Receiver
4.4 Coherent Detection
4.4.I Coherent Detection of PSK
4.4.2 Sampled Matched Filter
4.4.3 Coherent Detection of Multiple Phase-Shift Keying
4.4.4 Coherent Detection of FSK
4.5 Noncoherent Detection
4.5.1 Detection of Differential PSK
4.5.2 Binary Differential PSK Example
4.5.3 Noncoherent Detection of FSK
4.5.4 Required Tone Spacing for Noncoherent Orthogonal FSK Signaling
4.6 Complex Envelope
4.6.1 Quadrature Implementation of a Modulator
4.6.2 D8 PSK Modulator Example
4.6.3 D8PSK Demodulator Example
4.7 Error Performance for Binary Systems
4.7.1 Probability of Bit Error for Coherently Detected BPSK
4.7.2 Probability of Bit Error for Coherently DetectedDifferentially Encoded Binary PSK
4.7.3 Probability of Bit Error for Coherently Detected Binary Orthogonal FSK
4.7.4 Probability of Bit Error for Noncoherently Detected Binary Orthogonal FSK
4.7.5 Probability of Bit Error for Binary DPSK
4.7.6 Comparison of Bit Error Performance for Various Modulation Types
4.8 M-ary Signaling and Performance
4.8.1 Ideal Probability of Bit Error Performance
4.8.2 M-ary Signaling
4.8.3 Vectorial View of MPSK Signaling
4.8.4 BPSK and QPSK Have the Same Bit Error Probability
4.8.5 Vectorial View of MFSK Signaling
4.9 Symbol Error Performance for M-ary Systems(M>2)
4.9.1 Probability of Symbol Error for MPSK
4.9.2 Probability of Symbol Error for MFSK
4.9.3 Bit Error Probability versus Symbol Error Probability for Orthogonal Signals
4.9.4 Bit Error Probability versus Symbol Error Probability for Multiple Phase Signaling
4.9.5 Effects of Intersymbol Interference
4.10 Conclusion
5 CHANNEL CODING:PART 1
……
6 CHANNEL CODING:PART 2
7 MODULATION AND CODING TRADE-OFFS
8 SYNCHRONIZATION
9 MULTIPLEXING，MULTIPLE ACCESS AND SPREAD SPECTRUM
A A REVIEW OF FOURIER TECHNIQUES
B FUNDAMENTALS OF STATISTICAL DECISION THEORY
C RESPONSE OF CORRELATORS TO WHITE NOISE
D OFTEN-USED IDENTITIES
E s-DOMAIN，z-DOMAIN AND DIGITAL FILTERING
F LIST OF SYMBOLS
INDEX
鄂公网安备 42010302001612号 