Modern Digital And Analog Communication Systems

Preface

1 Introduction
1.1 Communication Systems
1.2 Design Challenges: Channel Distortions and Noises
1.3 Message Sources
1.4 Channel Effect, Signal-To-Noise Ratio, and Capacity
1.5 Modulation and Detection
1.6 Digital Source Coding and Error Correction Coding
1.7 A Brief Historical Review of Modern Telecommunications

2 Signals and Signal Space
2.1 Size of A Signal
2.2 Classification of Signals
2.3 Some Useful Signal Operations
2.4 Unit Impulse Signal
2.5 Signals versus Vectors
2.6 Correlation of Signals
2.7 Orthogonal Signal Sets
2.8 Trigonometric Fourier Series
2.9 Frequency Domain and Exponential Fourier Series
2.10 Matlab Exercises

3 Analysis and Transmission of Signals
3.1 Fourier Transform of Signals
3.2 Transforms of Some Useful Functions
3.3 Some Fourier Transform Properties
3.4 Signal Transmission Through a Linear Time-Invariant System
3.5 Ideal versus Practical Filters
3.6 Signal Distortion Over a Communication Channel
3.7 Signal Energy and Energy Spectral Density
3.8 Signal Power and Power Spectral Density
3.9 Numerical Computation of Fourier Transform: The Dft
3.10 Matlab Exercises

4 Analog Modulations and Demodulations
4.1 Baseband versus Carrier Communications
4.2 Double-Sideband Amplitude Modulation
4.3 Amplitude Modulation (AM)
4.4 Bandwidth-Efficient Amplitude Modulations
4.5 Fm and Pm: Nonlinear Angle Modulations
4.6 Bandwidth Analysis of Angle Modulations
4.7 Demodulation of Fm Signals
4.8 Frequency Conversion and Superheterodyne
4.9 Generating Fm Signals
4.10 Frequency Division Multiplexing (FDM)
4.11 Phase-Locked Loop and Applications
4.12 Matlab Exercises

5 Digitization of Analog
Source Signals
5.1 Sampling Theorem
5.2 Pulse Code Modulation (PCM)
5.3 Digital Telephony: Pcm in T1 Carrier Systems
5.4 Digital Multiplexing Hierarchy
5.5 Differential Pulse Code Modulation (DPCM)
5.6 Delta Modulation
5.7 Vocoders and Video Compression
5.8 Matlab Exercises

6 Principles of Digital Data Transmission
6.1 Digital Communication Systems
6.2 Baseband Line Coding
6.3 Pulse Shaping
6.4 Scrambling
6.5 Digital Receivers and Regenerative Repeaters
6.6 Eye Diagrams: An Important Diagnostic Tool
6.7 Pam: M-Ary Baseband Signaling
6.8 Digital Carrier Systems
6.9 M-Ary Digital Carrier Modulation
6.10 Matlab Exercises

7 Fundamentals of Probability Theory
7.1 Concept of Probability
7.2 Random Variables
7.3 Statistical Averages (means)
7.4 Correlation
7.5 Linear Mean Square Estimation
7.6 Sum of Random Variables
7.7 Central Limit Theorem

8 Random Processes and Spectral Analysis
8.1 from Random Variable to Random Process
8.2 Classification of Random Processes
8.3 Power Spectral Density
8.4 Multiple Random Processes
8.5 Transmission of Random Processes Through Linear Systems
8.6 Bandpass Random Processes

9 Performance Analysis of Digital Communication Systems
9.1 Optimum Linear Detector for Binary Polar Signaling
9.2 General Binary Signaling
9.3 Coherent Receivers for Digital Carrier Modulations
9.4 Signal Space Analysis of Optimum Detection
9.5 Vector Decomposition of White Noise Random Processes
9.6 Optimum Receiver for White Gaussian Noise Channels
9.7 General Error Probability of Optimum Receivers
9.8 Equivalent Signal Sets
9.9 Nonwhite (colored) Channel Noise
9.10 Other Useful Performance Criteria
9.11 Noncoherent Detection
9.12 Matlab Exercises

10 Spread Spectrum Communications
10.1 Frequency Hopping Spread Spectrum (FHSS) Systems
10.2 Multiple Fhss User Systems and Performance
10.3 Applications of FHSS
10.4 Direct Sequence Spread Spectrum
10.5 Resilient Features of DSSS
10.6 Code Division Multiple-Access (CDMA) of DSSS
10.7 Multiuser Detection (MUD)
10.8 Modern Practical DSSS CDMA Systems
10.9 Matlab Exercises

11 Digital Communications Over Linearly Distortive Channels
11.1 Linear Distortions of Wireless Multipath Channels
11.2 Receiver Channel Equalization
11.3 Linear T-Spaced Equalization (TSE)
11.4 Linear Fractionally Spaced Equalizers (FSE)
11.5 Channel Estimation
11.6 Decision Feedback Equalizer
11.7 OFDM (multicarrier) Communications
11.8 Discrete Multitone (DMT) Modulations
11.9 Real-Life Applications of OFDM and DMT
11.10 Blind Equalization and Identification
11.11 Time-Varying Channel Distortions Due to Mobility
11.12 Matlab Exercises

12 Introduction to Information Theory
12.1 Measure of Information
12.2 Source Encoding
12.3 Error-Free Communication Over a Noisy Channel
12.4 Channel Capacity of A Discrete Memoryless Channel
12.5 Channel Capacity of A Continuous Memoryless Channel
12.6 Frequency-Selective Channel Capacity
12.7 Multiple-Input--Multiple-Output Communication Systems
12.8 Matlab Exercises

13 Error Correcting Codes
13.1 Overview
13.2 Redundancy for Error Correction
13.3 Linear Block Codes
13.4 Cyclic Codes
13.5 the Benefit of Error Correction
13.6 Convolutional Codes
13.7 Trellis Diagram of Block Codes
13.8 Code Combining and Interleaving
13.9 Soft Decoding
13.10 Soft-Output Viterbi Algorithm (SOVA)
13.11 Turbo Codes
13.12 Low-Density Parity Check (LDPC) Codes
13.13 Matlab Exercises

A. Orthogonality of Some Signal Sets
A.1 Trigonometric Sinusoid Signal Set
A.2 Orthogonality of The Exponential Sinusoid Signal Set
B. Cauchy-Schwarz Inequality
C. Gram-Schmidt Orthogonalization of A Vector Set
D. Basic Matrix Properties and Operations
D.1 Notations
D.2 Matrix Product and Properties
D.3 Identity and Diagonal Matrices
D.4 Determinant of Square Matrices
D.5 Trace
D.6 Eigendecomposition
D.7 Special Hermitian Square Matrices
E Miscellaneous
E.1 L'Opital's Rule
E.2 Taylor and Maclaurin Series
E.3 Power Series
E.4 Sums
E.5 Complex Numbers
E.6 Trigonometric Identities
E.7 Indefinite Integrals

Index