Digital Communication Systems, An Indian Adaptation

Simon Haykin

ISBN: 9789354242465

652 pages

INR 769

Description

Digital Communication Systems is a comprehensive textbook, focusing on the core principles of digital communications and relating theory to practice. Starting with the background of Fourier analysis, probability theory, and stochastic processes to analyze random signals, the book covers sampling theory, pulse-amplitude modulation, pulse-code modulation, delta modulation, matched filter, intersymbol interference, and adaptive equalization. It then discusses passband digital modulation techniques such as ASK, PSK, FSK, and QAM, followed by multiple access techniques such as FDMA, TDMA, and CDMA. Lastly, it discourses on information theory in detail and various coding schemes to control the occurrences of errors in communication systems.               

 

 

Chapter 1: Introduction

    1. Historical Background
    2. The Communication Process
    3. Modes of Communication
    4. Need of Modulation
    5. Types of Modulation
    6. Digital versus Analog Communication
    7. Multiple-Access Techniques
    8. Networks
    9. Digital Communication
    10. Self-Sustainable Modern Communication
    11. Organization of the Book

 

Chapter 2: Frequency Analysis And Transmission Of Signals

  1. Introduction
  2. Representation of a Signal
  3. The Fourier Series
  4. The Fourier Transform
  5. The Inverse Relationship between Time-Domain and Frequency-Domain Representations
  6. The Dirac Delta Function
  7. Fourier Transforms of Periodic Signals
  8. Correlation of Signals
  9. Transmission of Signals through Linear Time-Invariant Systems
  10. Ideal Filters
  11. Hilbert Transform
  12. Pre-Envelopes
  13. Complex Envelopes of Band-Pass Signals
  14. Canonical Representation of Band-Pass Signals
  15. Complex Low-Pass Representations of Band-Pass Systems
  16. Putting the Complex Representations of Band-Pass Signals and Systems All Together
  17. Linear Modulation Theory
  18. Superheterodyne Receiver
  19. Phase and Group Delays
  20. Exponential (or Angle) Modulation
  21. Summary and Discussion

 

Chapter 3: Probability Theory And Random Variables

    1. Introduction
    2. Set Theory
    3. Probability Theory
    4. Random Variables
    5. Distribution Functions
    6. The Concept of Expectation
    7. Second-Order Statistical Averages
    8. The Gaussian Distribution
    9. The Central Limit Theorem
    10. Functions of One Random Variable
    11. Functions of Two Random Variables
    12. Bayesian Inference
    13. Parameter Estimation
    14. Hypothesis Testing
    15. Composite Hypothesis Testing
    16. Summary and Discussion

 

Chapter 4: Stochastic Processes

  1. Introduction
  2. Mathematical Definition of a Stochastic Process
  3. Two Classes of Stochastic Processes: Strictly Stationary and Weakly Stationary     
  4. Mean, Correlation, and Covariance Functions of Weakly Stationary Processes
  5. Ergodic Processes
  6. Transmission of a Weakly Stationary Process through a Linear Time-Invariant Filter
  7. Power Spectral Density of a Weakly Stationary Process
  8. Another Definition of the Power Spectral Density
  9. Cross-Spectral Densities
  10. The Poisson Process
  11. The Gaussian Process
  12. Noise
  13. Noise Calculation
  14. Noise Figure
  15. Narrowband Noise
  16. Sine Wave Plus Narrowband Noise
  17. Summary and Discussion 

 

Chapter 5: Baseband Modulation

    1. Introduction
    2. Sampling Theory
    3. Natural Sampling
    4. Pulse-Amplitude Modulation
    5. Pulse-Width and Pulse-Position Modulation
    6. Quantization and Its Statistical Characterization
    7. Pulse-Code Modulation
    8. Noise Considerations in PCM Systems
    9. Linear Prediction
    10. Differential Pulse-Code Modulation
    11. Adaptive Differential Pulse-Code Modulation
    12. Delta Modulation
    13. Line Codes
    14. Time-Division Multiplexing
    15. Summary and Discussion

 

Chapter 6:  Signaling Over Band-Limited Channels

    1. Introduction
    2. Optimum Receiver Filter
    3. Matched Filter
    4. Error Rate due to Channel Noise in a Matched Filter Receiver
    5. Intersymbol Interference
    6. Signal Design for Zero ISI
    7. Ideal Nyquist Pulse for Distortionless Baseband Data Transmission
    8. Raised-Cosine Spectrum
    9. Correlative-Level Coding
    10. Post-Processing Techniques: The Eye Pattern
    11. Optimum Linear Receiver
    12. Adaptive Equalization
    13. Summary and Discussion

 

Chapter 7: Passband Modulation

    1. Introduction
    2. Geometric Representation of Signals
    3. Conversion of the Continuous AWGN Channel into a Vector Channel
    4. Band-Pass Sampling
    5. Optimum Receivers Using Coherent Detection
    6. Probability of Error
    7. Band-Pass Transmission Model
    8. Binary Amplitude-Shift Keying Using Coherent Detection
    9. Phase-Shift Keying Techniques Using Coherent Detection
    10. M-ary Quadrature Amplitude Modulation
    11. Frequency-Shift Keying Techniques Using Coherent Detection
    12. Comparison of M-ary PSK and M-ary FSK from an Information-Theoretic Viewpoint
    13. Detection of Signals with Unknown Phase
    14. Noncoherent Orthogonal Modulation Techniques
    15. Binary Frequency-Shift Keying Using Noncoherent Detection
    16. Differential Phase-Shift Keying
    17. BER Comparison of Signaling Schemes over AWGN Channels
    18. Synchronization
    19. Summary and Discussion

 

Chapter 8: Spread Spectrum and Multiuser Communications

    1. Introduction
    2. Pseudo-Noise Sequences
    3. A Notion of Spread Spectrum
    4. Direct-Sequence Spread Spectrum with Coherent Binary Phase-Shift Keying
    5. Signal-Space Dimensionality Processing Gain
    6. Probability of Error
    7. Frequency-Hop Spread Spectrum
    8. Code-Division Multiple Access
    9. Orthogonal Frequency Division Multiplexing
    10. Satellite Communication
    11. Radio Link Analysis
    12. Mobile Radio
    13. Summary and Discussion

 

Chapter 9: Information Theory

    1. Introduction
    2. Information
    3. Entropy
    4. Source-Coding Theorem
    5. Lossless Data Compression Algorithms
    6. Discrete Memoryless Channels
    7. Mutual Information
    8. Channel Capacity
    9. Special Channels
    10. Channel-Coding Theorem
    11. Differential Entropy and Mutual Information for Continuous Random Ensembles
    12. Information Capacity Law
    13. Implications of the Information Capacity Law
    14. Summary and Discussion

 

Chapter 10: Error-Control Coding

    1. Introduction
    2. Error Control Using Forward Error Correction
    3. Discrete Memoryless Channels
    4. Linear Block Codes
    5. Cyclic Codes
    6. Convolutional Codes
    7. Optimum Decoding of Convolutional Codes
    8. Maximum Likelihood Decoding of Convolutional Codes
    9. Maximum a Posteriori Probability Decoding of Convolutional Codes
    10. Turbo Codes
    11. Low-Density Parity-Check Codes
    12. Trellis-Coded Modulation
    13. Turbo Decoding of Serial Concatenated Codes
    14. Summary and Discussion

Problems

Multiple Choice Questions

 

Appendix A Advanced Probabilistic Models

Appendix B Bounds on The Q-Function

Appendix C Bessel Functions

Appendix D Method of Lagrange Multipliers

Appendix E Multiple-Input, Multiple-Output Systems

Appendix F Interleaving

Appendix G The Peak-Power Reduction Problem In Of dm

Appendix H Nonlinear Solid-State Power Amplifiers

Appendix I Monte Carlo Integration

Appendix J Mathematical Tables

 

Glossary

Bibliography

Index

Credits