- Coverpage
- Titlepage
- Copyright
- Dedication
- Preface
- Contents
- 1 Introduction
- 2 Fourier Analysis of Signals and Systems
- 2.1 Introduction
- 2.2 The Fourier Series
- 2.3 The Fourier Transform
- 2.4 The Inverse Relationship between Time-Domain and Frequency-Domain Representations
- 2.5 The Dirac Delta Function
- 2.6 Fourier Transforms of Periodic Signals
- 2.7 Transmission of Signals through Linear Time-Invariant Systems
- 2.8 Hilbert Transform
- 2.9 Pre-envelope
- 2.10 Complex Envelopes of Band-Pass Signals
- 2.11 Canonical Representation of Band-Pass Signals
- 2.12 Complex Low-Pass Representations of Band-Pass Systems
- 2.13 Putting the Complex Representations of Band-Pass Signals and Systems All Together
- 2.14 Linear Modulation Theory
- 2.15 Phase and Group Delays
- 2.16 Numerical Computation of the Fourier Transform
- 2.17 Summary and Discussion
- 3 Probability Theory and Bayesian Inference
- 3.1 Introduction
- 3.2 Set Theory
- 3.3 Probability Theory
- 3.4 Random Variables
- 3.5 Distribution Functions
- 3.6 The Concept of Expectation
- 3.7 Second-Order Statistical Averages
- 3.8 Characteristic Function
- 3.9 The Gaussian Distribution
- 3.10 The Central Limit Theorem
- 3.11 Bayesian Inference
- 3.12 Parameter Estimation
- 3.13 Hypothesis Testing
- 3.14 Composite Hypothesis Testing
- 3.15 Summary and Discussion
- 4 Stochastic Processes
- 4.1 Introduction
- 4.2 Mathematical Definition of a Stochastic Process
- 4.3 Two Classes of Stochastic Processes: Strictly Stationary and Weakly Stationary
- 4.4 Mean, Correlation, and Covariance Functions of Weakly Stationary Processes
- 4.5 Ergodic Processes
- 4.6 Transmission of a Weakly Stationary Process through a Linear Time-invariant Filter
- 4.7 Power Spectral Density of a Weakly Stationary Process
- 4.8 Another Definition of the Power Spectral Density
- 4.9 Cross-spectral Densities
- 4.10 The Poisson Process
- 4.11 The Gaussian Process
- 4.12 Noise
- 4.13 Narrowband Noise
- 4.14 Sine Wave Plus Narrowband Noise
- 4.15 Summary and Discussion
- 5 Information Theory
- 5.1 Introduction
- 5.2 Entropy
- 5.3 Source-coding Theorem
- 5.4 Lossless Data Compression Algorithms
- 5.5 Discrete Memoryless Channels
- 5.6 Mutual Information
- 5.7 Channel Capacity
- 5.8 Channel-coding Theorem
- 5.9 Differential Entropy and Mutual Information for Continuous Random Ensembles
- 5.10 Information Capacity Law
- 5.11 Implications of the Information Capacity Law
- 5.12 Information Capacity of Colored Noisy Channel
- 5.13 Rate Distortion Theory
- 5.14 Summary and Discussion
- 6 Conversion of Analog Waveforms into Coded Pulses
- 6.1 Introduction
- 6.2 Sampling Theory
- 6.3 Pulse-Amplitude Modulation
- 6.4 Quantization and its Statistical Characterization
- 6.5 Pulse-Code Modulation
- 6.6 Noise Considerations in PCM Systems
- 6.7 Prediction-Error Filtering for Redundancy Reduction
- 6.8 Differential Pulse-Code Modulation
- 6.9 Delta Modulation
- 6.10 Line Codes
- 6.11 Summary and Discussion
- 7 Signaling over AWGN Channels
- 7.1 Introduction
- 7.2 Geometric Representation of Signals
- 7.3 Conversion of the Continuous AWGN Channel into a Vector Channel
- 7.4 Optimum Receivers Using Coherent Detection
- 7.5 Probability of Error
- 7.6 Phase-Shift Keying Techniques Using Coherent Detection
- 7.7 M-ary Quadrature Amplitude Modulation
- 7.8 Frequency-Shift Keying Techniques Using Coherent Detection
- 7.9 Comparison of M-ary PSK and M-ary FSK from an Information-Theoretic Viewpoint
- 7.10 Detection of Signals with Unknown Phase
- 7.11 Noncoherent Orthogonal Modulation Techniques
- 7.12 Binary Frequency-Shift Keying Using Noncoherent Detection
- 7.13 Differential Phase-Shift Keying
- 7.14 BER Comparison of Signaling Schemes over AWGN Channels
- 7.15 Synchronization
- 7.16 Recursive Maximum Likelihood Estimation for Synchronization
- 7.17 Summary and Discussion
- 8 Signaling over Band-Limited Channels
- 8.1 Introduction
- 8.2 Error Rate Due to Channel Noise in a Matched-Filter Receiver
- 8.3 Intersymbol Interference
- 8.4 Signal Design for Zero ISI
- 8.5 Ideal Nyquist Pulse for Distortionless Baseband Data Transmission
- 8.6 Raised-Cosine Spectrum
- 8.7 Square-Root Raised-Cosine Spectrum
- 8.8 Post-Processing Techniques: The Eye Pattern
- 8.9 Adaptive Equalization
- 8.10 Broadband Backbone Data Network: Signaling over Multiple Baseband Channels
- 8.11 Digital Subscriber Lines
- 8.12 Capacity of AWGN Channel Revisited
- 8.13 Partitioning Continuous-Time Channel into a Set of Subchannels
- 8.14 Water-Filling Interpretation of the Constrained Optimization Problem
- 8.15 DMT System Using Discrete Fourier Transform
- 8.16 Summary and Discussion
- 9 Signaling over Fading Channels
- 9.1 Introduction
- 9.2 Propagation Effects
- 9.3 Jakes Model
- 9.4 Statistical Characterization of Wideband Wireless Channels
- 9.5 FIR Modeling of Doubly Spread Channels
- 9.6 Comparison of Modulation Schemes: Effects of Flat Fading
- 9.7 Diversity Techniques
- 9.8 “Space Diversity-on-Receive” Systems
- 9.9 “Space Diversity-on-Transmit” Systems
- 9.10 “Multiple-Input, Multiple-Output” Systems: Basic Considerations
- 9.11 MIMO Capacity for Channel Known at the Receiver
- 9.12 Orthogonal Frequency Division Multiplexing
- 9.13 Spread Spectrum Signals
- 9.14 Code-Division Multiple Access
- 9.15 The RAKE Receiver and Multipath Diversity
- 9.16 Summary and Discussion
- 10 Error-Control Coding
- 10.1 Introduction
- 10.2 Error Control Using Forward Error Correction
- 10.3 Discrete Memoryless Channels
- 10.4 Linear Block Codes
- 10.5 Cyclic Codes
- 10.6 Convolutional Codes
- 10.7 Optimum Decoding of Convolutional Codes
- 10.8 Maximum Likelihood Decoding of Convolutional Codes
- 10.9 Maximum a Posteriori Probability Decoding of Convolutional Codes
- 10.10 Illustrative Procedure for Map Decoding in the Log-Domain
- 10.11 New Generation of Probabilistic Compound Codes
- 10.12 Turbo Codes
- 10.13 EXIT Charts
- 10.14 Low-Density Parity-Check Codes
- 10.15 Trellis-Coded Modulation
- 10.16 Turbo Decoding of Serial Concatenated Codes
- 10.17 Summary and Discussion
- A Advanced Probabilistic Models
- B Bounds on the Q-Function
- C Bessel Functions
- D Method of Lagrange Multipliers
- E Information Capacity of MIMO Channels
- F Interleaving
- G The Peak-Power Reduction Problem in OFDM
- H Nonlinear Solid-State Power Amplifiers
- I Monte Carlo Integration
- J Maximal-Length Sequences
- K Mathematical Tables
- Glossary
- Bibliography
- Index
- Credits
-
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