Simon Haykin is a University Professor at McMaster University, Hamilton, Ontario, Canada. His research interests include nonlinear dynamics, neural networks and adaptive filters and their applications in radar and communications systems. Dr. Haykin is the editor for a series of books on "Adaptive and Learning Systems for Signal Processing, Communications and Control" published by John Wiley & Sons, Inc. He is both an IEEE Fellow and Fellow of the Royal Society of Canada.

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• Preface viiChapter 1 Prologue 11.1 The Communication Process 11.2 The Layered Approach 21.3 Theme Example—Wireless Communications 3Notes and References 7Chapter 2 Fourier Theory and Communication Signals 82.1 Introduction 82.2 The Fourier Transform 82.3 Properties of the Fourier Transform 142.4 The Inverse Relationship Between Time and Frequency 282.5 Dirac Delta Function 322.6 Fourier Transforms of Periodic Signals 392.7 Transmission of Signals Through Linear Systems 412.8 Filters 472.9 Low-Pass and Band-Pass Signals 522.10 Band-Pass Systems 572.11 Phase and Group Delay 602.12 Sources of Information 622.13 Numerical Computation of the Fourier Transform 642.14 Theme Example—Channel Estimation of a Wireless LAN Channel 662.15 Summary and Discussion 69Notes and References 69Problems 70Chapter 3 Amplitude Modulation 743.1 Introduction 743.2 Amplitude Modulation 753.3 Double Sideband–Suppressed Carrier Modulation 833.4 Quadrature-Carrier Multiplexing 873.5 Single-Sideband and Vestigial-Sideband Methods of Modulation 883.6 Theme Example—VSB Transmission of Analog and Digital Television 923.7 Frequency Translation 933.8 Frequency-Division Multiplexing 943.9 Summary and Discussion 95Notes and References 96Problems 96Chapter 4 Phase and Frequency Modulation 1024.1 Introduction 1024.2 Basic Definitions 1024.3 Frequency Modulation 1094.4 Phase-Locked Loop 1274.5 Nonlinear Effects in FM Systems 1334.6 The Superheterodyne Receiver 1354.7 Theme Example—Analog and Digital FM Cellular Telephones 1374.8 Summary and Discussion 139Notes and References 140Problems 140Chapter 5 Random Variables and Processes 1465.1 Introduction 1465.2 Probability 1475.3 Random Variables 1515.4 Statistical Averages 1565.5 Random Processes 1615.6 Mean, Correlation, and Covariance Functions 1625.7 Transmission of a Random Process Through a Linear Filter 1685.8 Power Spectral Density 1695.9 Gaussian Process 1755.10 Noise 1795.11 Narrowband Noise 1865.12 Theme Example—Stochastic Model of a Mobile Radio Channel 1935.13 Summary and Discussion 198Notes and References 200Problems 201Chapter 6 Noise in Analog Modulation 2076.1 Introduction 2076.2 Receiver Model 2076.3 Noise in DSB–SC Receivers 2106.4 Noise in AM Receivers 2126.5 Noise in FM Receivers 2156.6 Pre-emphasis and De-emphasis in FM 2266.7 Theme Example—Link Budget of FM Satellite Link 2296.8 Summary and Discussion 233Notes and References 235Problems 235Chapter 7 Digital Representation of Analog Signals 2387.1 Introduction 2387.2 Why Digitize Analog Sources? 2397.3 The Sampling Process 2407.4 Pulse-Amplitude Modulation 2447.5 Time-Division Multiplexing 2477.6 Pulse-Position Modulation 2487.7 Theme Example—PPM in Impulse Radio 2557.8 The Quantization Process 2567.9 Pulse-Code Modulation 2607.10 Delta Modulation 2677.11 Theme Example—Digitization of Video and MPEG 2717.12 Summary and Discussion 273Notes and References 274Problems 275Chapter 8 Baseband Transmission Of Digital Signals 2798.1 Introduction 2798.2 Baseband Pulses and Matched Filter Detection 2808.3 Probability of Error Due to Noise 2858.4 Intersymbol Interference 2908.5 Eye Pattern 2948.6 Nyquist’s Criterion for Distortionless Transmission 2968.7 Baseband M-ary PAM Transmission 3018.8 Tapped-Delay-Line Equalization 3028.9 Theme Example—100BASE-TX— Transmission of 100 Mbps Over Twisted Pair 3058.10 Summary and Discussion 308Notes and References 309Problems 309Chapter 9 Band-pass Transmission Of Digital Signals 3139.1 Introduction 3139.2 Band-Pass Transmission Model 3149.3 Transmission of Binary PSK and FSK 3169.4 M-ary Data Transmission Systems 3279.5 Comparison of Noise Performances of Various PSK and FSK Systems 3319.6 Theme Example—Orthogonal Frequency Division Multiplexing (OFDM) 3339.7 Summary and Discussion 337Notes and References 338Problems 338Chapter 10 Information and Forward Error Correction 34210.1 Introduction 34210.2 Uncertainty, Information, and Entropy 34310.3 Source-Coding Theorem 34710.4 Lossless Data Compression 34810.5 Theme Example—The Lempel– Ziv Algorithm and File Compression 35310.6 Discrete Memoryless Channels 35510.7 Channel Capacity 35710.8 Channel Coding Theorem 36010.9 Capacity of a Gaussian Channel 36310.10 Error Control Coding 36610.11 Linear Block Codes 36910.12 Convolutional Codes 37910.13 Trellis-Coded Modulation 38410.14 Turbo Codes 38810.15 Summary and Discussion 393Notes and References 394Problems 395Appendix Mathematical Tables 398Glossary 405Bibliography 409Index 413

Simon Haykin is a University Professor at McMaster University, Hamilton, Ontario, Canada. His research interests include nonlinear dynamics, neural networks and adaptive filters and their applications in radar and communications systems. Dr. Haykin is the editor for a series of books on "Adaptive and Learning Systems for Signal Processing, Communications and Control" published by John Wiley & Sons, Inc. He is both an IEEE Fellow and Fellow of the Royal Society of Canada.

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• Preface viiChapter 1 Prologue 11.1 The Communication Process 11.2 The Layered Approach 21.3 Theme Example—Wireless Communications 3Notes and References 7Chapter 2 Fourier Theory and Communication Signals 82.1 Introduction 82.2 The Fourier Transform 82.3 Properties of the Fourier Transform 142.4 The Inverse Relationship Between Time and Frequency 282.5 Dirac Delta Function 322.6 Fourier Transforms of Periodic Signals 392.7 Transmission of Signals Through Linear Systems 412.8 Filters 472.9 Low-Pass and Band-Pass Signals 522.10 Band-Pass Systems 572.11 Phase and Group Delay 602.12 Sources of Information 622.13 Numerical Computation of the Fourier Transform 642.14 Theme Example—Channel Estimation of a Wireless LAN Channel 662.15 Summary and Discussion 69Notes and References 69Problems 70Chapter 3 Amplitude Modulation 743.1 Introduction 743.2 Amplitude Modulation 753.3 Double Sideband–Suppressed Carrier Modulation 833.4 Quadrature-Carrier Multiplexing 873.5 Single-Sideband and Vestigial-Sideband Methods of Modulation 883.6 Theme Example—VSB Transmission of Analog and Digital Television 923.7 Frequency Translation 933.8 Frequency-Division Multiplexing 943.9 Summary and Discussion 95Notes and References 96Problems 96Chapter 4 Phase and Frequency Modulation 1024.1 Introduction 1024.2 Basic Definitions 1024.3 Frequency Modulation 1094.4 Phase-Locked Loop 1274.5 Nonlinear Effects in FM Systems 1334.6 The Superheterodyne Receiver 1354.7 Theme Example—Analog and Digital FM Cellular Telephones 1374.8 Summary and Discussion 139Notes and References 140Problems 140Chapter 5 Random Variables and Processes 1465.1 Introduction 1465.2 Probability 1475.3 Random Variables 1515.4 Statistical Averages 1565.5 Random Processes 1615.6 Mean, Correlation, and Covariance Functions 1625.7 Transmission of a Random Process Through a Linear Filter 1685.8 Power Spectral Density 1695.9 Gaussian Process 1755.10 Noise 1795.11 Narrowband Noise 1865.12 Theme Example—Stochastic Model of a Mobile Radio Channel 1935.13 Summary and Discussion 198Notes and References 200Problems 201Chapter 6 Noise in Analog Modulation 2076.1 Introduction 2076.2 Receiver Model 2076.3 Noise in DSB–SC Receivers 2106.4 Noise in AM Receivers 2126.5 Noise in FM Receivers 2156.6 Pre-emphasis and De-emphasis in FM 2266.7 Theme Example—Link Budget of FM Satellite Link 2296.8 Summary and Discussion 233Notes and References 235Problems 235Chapter 7 Digital Representation of Analog Signals 2387.1 Introduction 2387.2 Why Digitize Analog Sources? 2397.3 The Sampling Process 2407.4 Pulse-Amplitude Modulation 2447.5 Time-Division Multiplexing 2477.6 Pulse-Position Modulation 2487.7 Theme Example—PPM in Impulse Radio 2557.8 The Quantization Process 2567.9 Pulse-Code Modulation 2607.10 Delta Modulation 2677.11 Theme Example—Digitization of Video and MPEG 2717.12 Summary and Discussion 273Notes and References 274Problems 275Chapter 8 Baseband Transmission Of Digital Signals 2798.1 Introduction 2798.2 Baseband Pulses and Matched Filter Detection 2808.3 Probability of Error Due to Noise 2858.4 Intersymbol Interference 2908.5 Eye Pattern 2948.6 Nyquist’s Criterion for Distortionless Transmission 2968.7 Baseband M-ary PAM Transmission 3018.8 Tapped-Delay-Line Equalization 3028.9 Theme Example—100BASE-TX— Transmission of 100 Mbps Over Twisted Pair 3058.10 Summary and Discussion 308Notes and References 309Problems 309Chapter 9 Band-pass Transmission Of Digital Signals 3139.1 Introduction 3139.2 Band-Pass Transmission Model 3149.3 Transmission of Binary PSK and FSK 3169.4 M-ary Data Transmission Systems 3279.5 Comparison of Noise Performances of Various PSK and FSK Systems 3319.6 Theme Example—Orthogonal Frequency Division Multiplexing (OFDM) 3339.7 Summary and Discussion 337Notes and References 338Problems 338Chapter 10 Information and Forward Error Correction 34210.1 Introduction 34210.2 Uncertainty, Information, and Entropy 34310.3 Source-Coding Theorem 34710.4 Lossless Data Compression 34810.5 Theme Example—The Lempel– Ziv Algorithm and File Compression 35310.6 Discrete Memoryless Channels 35510.7 Channel Capacity 35710.8 Channel Coding Theorem 36010.9 Capacity of a Gaussian Channel 36310.10 Error Control Coding 36610.11 Linear Block Codes 36910.12 Convolutional Codes 37910.13 Trellis-Coded Modulation 38410.14 Turbo Codes 38810.15 Summary and Discussion 393Notes and References 394Problems 395Appendix Mathematical Tables 398Glossary 405Bibliography 409Index 413

Simon Haykin is a University Professor at McMaster University, Hamilton, Ontario, Canada. His research interests include nonlinear dynamics, neural networks and adaptive filters and their applications in radar and communications systems. Dr. Haykin is the editor for a series of books on "Adaptive and Learning Systems for Signal Processing, Communications and Control" published by John Wiley & Sons, Inc. He is both an IEEE Fellow and Fellow of the Royal Society of Canada.

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• Preface viiChapter 1 Prologue 11.1 The Communication Process 11.2 The Layered Approach 21.3 Theme Example—Wireless Communications 3Notes and References 7Chapter 2 Fourier Theory and Communication Signals 82.1 Introduction 82.2 The Fourier Transform 82.3 Properties of the Fourier Transform 142.4 The Inverse Relationship Between Time and Frequency 282.5 Dirac Delta Function 322.6 Fourier Transforms of Periodic Signals 392.7 Transmission of Signals Through Linear Systems 412.8 Filters 472.9 Low-Pass and Band-Pass Signals 522.10 Band-Pass Systems 572.11 Phase and Group Delay 602.12 Sources of Information 622.13 Numerical Computation of the Fourier Transform 642.14 Theme Example—Channel Estimation of a Wireless LAN Channel 662.15 Summary and Discussion 69Notes and References 69Problems 70Chapter 3 Amplitude Modulation 743.1 Introduction 743.2 Amplitude Modulation 753.3 Double Sideband–Suppressed Carrier Modulation 833.4 Quadrature-Carrier Multiplexing 873.5 Single-Sideband and Vestigial-Sideband Methods of Modulation 883.6 Theme Example—VSB Transmission of Analog and Digital Television 923.7 Frequency Translation 933.8 Frequency-Division Multiplexing 943.9 Summary and Discussion 95Notes and References 96Problems 96Chapter 4 Phase and Frequency Modulation 1024.1 Introduction 1024.2 Basic Definitions 1024.3 Frequency Modulation 1094.4 Phase-Locked Loop 1274.5 Nonlinear Effects in FM Systems 1334.6 The Superheterodyne Receiver 1354.7 Theme Example—Analog and Digital FM Cellular Telephones 1374.8 Summary and Discussion 139Notes and References 140Problems 140Chapter 5 Random Variables and Processes 1465.1 Introduction 1465.2 Probability 1475.3 Random Variables 1515.4 Statistical Averages 1565.5 Random Processes 1615.6 Mean, Correlation, and Covariance Functions 1625.7 Transmission of a Random Process Through a Linear Filter 1685.8 Power Spectral Density 1695.9 Gaussian Process 1755.10 Noise 1795.11 Narrowband Noise 1865.12 Theme Example—Stochastic Model of a Mobile Radio Channel 1935.13 Summary and Discussion 198Notes and References 200Problems 201Chapter 6 Noise in Analog Modulation 2076.1 Introduction 2076.2 Receiver Model 2076.3 Noise in DSB–SC Receivers 2106.4 Noise in AM Receivers 2126.5 Noise in FM Receivers 2156.6 Pre-emphasis and De-emphasis in FM 2266.7 Theme Example—Link Budget of FM Satellite Link 2296.8 Summary and Discussion 233Notes and References 235Problems 235Chapter 7 Digital Representation of Analog Signals 2387.1 Introduction 2387.2 Why Digitize Analog Sources? 2397.3 The Sampling Process 2407.4 Pulse-Amplitude Modulation 2447.5 Time-Division Multiplexing 2477.6 Pulse-Position Modulation 2487.7 Theme Example—PPM in Impulse Radio 2557.8 The Quantization Process 2567.9 Pulse-Code Modulation 2607.10 Delta Modulation 2677.11 Theme Example—Digitization of Video and MPEG 2717.12 Summary and Discussion 273Notes and References 274Problems 275Chapter 8 Baseband Transmission Of Digital Signals 2798.1 Introduction 2798.2 Baseband Pulses and Matched Filter Detection 2808.3 Probability of Error Due to Noise 2858.4 Intersymbol Interference 2908.5 Eye Pattern 2948.6 Nyquist’s Criterion for Distortionless Transmission 2968.7 Baseband M-ary PAM Transmission 3018.8 Tapped-Delay-Line Equalization 3028.9 Theme Example—100BASE-TX— Transmission of 100 Mbps Over Twisted Pair 3058.10 Summary and Discussion 308Notes and References 309Problems 309Chapter 9 Band-pass Transmission Of Digital Signals 3139.1 Introduction 3139.2 Band-Pass Transmission Model 3149.3 Transmission of Binary PSK and FSK 3169.4 M-ary Data Transmission Systems 3279.5 Comparison of Noise Performances of Various PSK and FSK Systems 3319.6 Theme Example—Orthogonal Frequency Division Multiplexing (OFDM) 3339.7 Summary and Discussion 337Notes and References 338Problems 338Chapter 10 Information and Forward Error Correction 34210.1 Introduction 34210.2 Uncertainty, Information, and Entropy 34310.3 Source-Coding Theorem 34710.4 Lossless Data Compression 34810.5 Theme Example—The Lempel– Ziv Algorithm and File Compression 35310.6 Discrete Memoryless Channels 35510.7 Channel Capacity 35710.8 Channel Coding Theorem 36010.9 Capacity of a Gaussian Channel 36310.10 Error Control Coding 36610.11 Linear Block Codes 36910.12 Convolutional Codes 37910.13 Trellis-Coded Modulation 38410.14 Turbo Codes 38810.15 Summary and Discussion 393Notes and References 394Problems 395Appendix Mathematical Tables 398Glossary 405Bibliography 409Index 413