Home Page Icon
Home Page
Table of Contents for
Titlepage
Close
Titlepage
by Simon Haykin
Digital Communication Systems
Coverpage
Titlepage
Copyright
Dedication
Preface
Contents
1 Introduction
1.1 Historical Background
1.2 The Communication Process
1.3 Multiple-Access Techniques
1.4 Networks
1.5 Digital Communications
1.6 Organization of the Book
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
A.1 The Chi-Square Distribution
A.2 The Log-Normal Distribution
A.3 The Nakagami Distribution
B Bounds on the Q-Function
C Bessel Functions
C.1 Series Solution of Bessel’s Equation
C.2 Properties of the Bessel Function
C.3 Modified Bessel Function
D Method of Lagrange Multipliers
D.1 Optimization Involving a Single Equality Constraint
E Information Capacity of MIMO Channels
E.1 Log-Det Capacity Formula of MIMO Channels
E.2 MIMO Capacity for Channel Known at the Transmitter
F Interleaving
F.1 Block Interleaving
F.2 Convolutional Interleaving
F.3 Random Interleaving
G The Peak-Power Reduction Problem in OFDM
G.1 PAPR Properties of OFDM Signals
G.2 Maximum PAPR in OFDM Using M-ary PSK
G.3 Clipping-Filtering: A Technique for PAPR Reduction
H Nonlinear Solid-State Power Amplifiers
H.1 Power Amplifier Nonlinearities
H.2 Nonlinear Modeling of Band-Pass Power Amplifiers
I Monte Carlo Integration
J Maximal-Length Sequences
J.1 Properties of Maximal-Length Sequences
J.2 Choosing a Maximal-Length Sequence
K Mathematical Tables
Glossary
Bibliography
Index
Credits
Search in book...
Toggle Font Controls
Playlists
Add To
Create new playlist
Name your new playlist
Playlist description (optional)
Cancel
Create playlist
Sign In
Email address
Password
Forgot Password?
Create account
Login
or
Continue with Facebook
Continue with Google
Sign Up
Full Name
Email address
Confirm Email Address
Password
Login
Create account
or
Continue with Facebook
Continue with Google
Prev
Previous Chapter
Coverpage
Next
Next Chapter
Copyright
Add Highlight
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click
here
login for view all page.
Day Mode
Cloud Mode
Night Mode
Reset