基本介紹
內容簡介
本書除包含目前國內樊昌信的《通信原理》的全部內容外，內容更深，旨在克服目前大多數同類書實用性和工程性不足的缺點。還加強了實際套用系統的介紹和理論仿真的介紹與實現。同時，本書實用性、工程性、參考性較強；全書擁有很有特色的體系結構，以套用為目標，先講原理、方法，再給出相關的例子，易於理解。
本書特點主要體現在：
1、本書比《通信原理》多出了信息壓縮技術（即，信源編碼）。體現出數字通信系統的完整性；
2、本書的復用與同步一章的“復用”介紹PDH、SDH這兩種實際復用技術，同步強調實際實現，而《通信原理》的同步強調枯燥的理論，且沒有復用的內容；
3、書中的“基帶傳輸”比《通信原理》多出了“噪聲檢測”的內容；
4、書中的“信道編碼”比《通信原理》更簡潔易懂；
5、本書比《通信原理》增加了MATLAM實現，對於工程套用來說，MATLAB實現更加方便可行。
作者簡介
Mohammed Farooque Mesiya是倫斯勒理工學院工程與科學系教授，是幾家成功創業公司的CEO。專業領域包括無線通信與網路、光纖通信與網路、數字通信與信號處理、寬頻網路與結構等。Mesiya教授還出版過幾本書籍，並發表了眾多的期刊論文和會議論文。
圖書目錄
Preface
CHAPTER
Introduction
1.1 Elements of a Communication System
1.2 Communication Channels
1.2.1 Coaxial Cable
1.2.2 Optical Fibers
1.2.3 Radio Channels
1.3 Analog and Digital Communication Systems
1.3.1 Digital Communication Systems
1.3.2 Why Digital Transmission？
1.4 History of Communications
1.4.1 Wireless Communications
1.5 Key Themes and Drivers
Final Remarks
Further Readings
CHAPTER 2
Review of Signals and Linear Systems
2.1 Basic Signal Concepts
2.1.1 Some Useful Basic Signals
2.1.2 Energy and Power Signals
2.1.3 Logarithmic Power Calculations
2.1.4 Some Basic Operations on Signals
2.2 Basic System Concepts
2.2.1 Classification of Systems
2.2.2 Characterization of LTI Systems
2.3 Frequency Domain Representation
2.4 Fourier Series
2.4.1 Trigonometric Fourier Series
2.4.2 Parseval’s Theorem
2.4.3 Convergence of Fourier Series
2.5 Fourier Transform
2.5.1 Fourier Transforms of Some Common Signals
2.5.2 Properties of Fourier Transform
2.5.3 Fourier Transforms of Periodic Signals
2.6 Time—Bandwidth Product
2.7 Transmission of Signals Through LTI Systems
2.7.1 Distortionless Transmission
2.8 LTI Systems as Frequency Selective Filters
2.8.1 Ideal Filters
2.8.2 Realizable Approximations to Ideal Filters
2.8.3 Analog Filter Design Using MATLAB
2.9 Power Spectral Density
2.9.1 Time—Average Autocorrelation Function
2.9.2 Relationship Between Input and Output Power Spectral Densities
2.10 Frequency Response Characteristics of Transmission Media
2.10.1 Twisted Wire Pairs
2.10.2 Coaxial Cable
2.11 Fourier Transforms for Discrete—Time Signals
Final Remarks
Further Readings
Problems
MATLAB Problems
CHAPTER 3
Simulation of Communication Systems Using MATLAB/Simulink
3.1 Getting Started in Simulink
3.1.1 Solvers
3.2 Modeling in Simulink
3.2.1 Subsystems
3.3 Simulation of Signal and Noise Sources
3.3.1 Deterministic Signals
3.3.2 Random Signals
3.3.3 Modeling of AWGN Channel
3.4 Modeling of Communication Systems
3.4.1 Time—Domain Modeling
3.4.2 Transform—Domain Description
3.5 Displaying Signals in Frequency Domain
3.6 Using Simulink with MATLAB
3.6.1 Running Simulations from MATLAB
Final Remarks
Further Readings
CHAPTER 4
Amplitude Modulation
4.1 Low—Pass and Bandpass Signals
4.2 Double—Sideband Suppressed—Carrier AM
4.2.1 Spectrum of the DSB—SC AM Signal
4.2.2 Demodulation of DSB—SC AM Signals
Experiment 4.1 DSB—SC AM Modulation and Demodulation
4.3 Conventional Amplitude Modulation
4.3.1 Spectrum of the Conventional AM Signal
4.3.2 Demodulation of Conventional AM Signal
Experiment 4.2 Conventional AM Modulation and Demodulation
4.4 Alternative Representations for BP Signals and Systems
4.4.1 Frequency Spectrum of Complex Envelope and Analytic Representations
4.4.2 Complex Envelope Representation of BP Systems
4.5 Single—Sideband AM
4.5.1 Demodulation of SSB—AM Signals
Experiment 4.3 SSB—AM Modulation and Demodulation
4.6 Vestigial—Sideband AM
4.7 Quadrature Multiplexing
4.8 Multiplexing
4.8.1 Frequency Division Multiplexing
4.9 Frequency Translation and Selection
4.9.1 Down—Conversion Mixer
4.9.2 Image—Reject Mixers
4.10 Communication Receivers
4.10.1 Superheterodyne Receivers
4.10.2 Direct—Conversion Receivers
4.10.3 Low—IF Receiver Architectures
Final Remarks
Further Readings
Problems
MATLAB Problems
APPENDIX 4A： Hilbert Transform
CHAPTER 5
Angle Modulation
5.1 FM and PM Signals
5.1.1 FM and PM Signals with Sinusoidal Modulating Signal
5.1.2 Power in Angle—Modulated Signal
5.2 Spectrum of Angle—Modulated Signals
5.2.1 Bandwidth of a Sinusoidally Modulated FM Signal
5.2.2 Bandwidth of an FM Signal Modulated by Arbitrary Message Signal
5.3 Narrowband FM
5.4 Demodulation of Angle—Modulated Signals
5.4.1 Bandpass Limiter
5.4.2 Frequency Discriminator
Experiment 5.1 Simulink Model of an FM System with Frequency Discriminator
Experiment 5.2 FM Demodulation with Balanced Slope Detector
5.4.3 Phase—shift Discriminator： Quadrature Detector
5.5 Phase—Locked Loop
5.5.1 Analog Phase—Locked Loop
5.5.2 APLL Linear Model
5.5.3 First—Order PLL
Experiment 5.3 First—Order PLL
5.5.4 Second—Order PLL
Experiment 5.4 Second—Order PLL
5.5.5 Acquisition Process： APLL in the Unlocked State
5.6 PLL as FM Demodulator
Experiment 5.5 PLL as FM Demodulator
5.7 FM Broadcasting
5.7.1 FM Stereo
5.8 Analog Television
5.8.1 Black—and—White Image
5.8.2 Black—and—White Television
5.8.3 Color Television
5.8.4 Multichannel Television Sound
Final Remarks
Further Readings
Problems
MATLAB Problems
CHAPTER 6
Probability and Random Processes
6.1 Probability Concepts
6.1.1 Relative Frequency
6.1.2 Probability Axioms
6.1.3 Union Bound
6.1.4 Conditional Probability
6.2 Random Variables
6.2.1 Discrete Random Variables
6.2.2 Some Common Discrete Random Variables
6.3 Continuous Random Variables
6.3.1 Some Common Continuous Random Variables
6.3.2 PDFs for Discrete and Mixed Random Variables
6.4 Functions of a Random Variable
6.4.1 Case Ⅰ： g （ x ） Monotonically Increasing or Decreasing
6.4.2 Case Ⅱ： Arbitrary g （ x ）
6.5 Statistics of Random Variables
6.5.1 Moments and Characteristic Functions
6.6 Pairs of Random Variables
6.6.1 Marginal Distributions
6.6.2 Function of Two Random Variables： Expected Values
6.7 Conditional Distributions
6.7.1 Conditional Expected Values
6.7.2 Independent Random Variables
6.8 Jointly Gaussian Random Variables
6.8.1 Two Functions of Two Random Variables
6.8.2 Central Limit Theorem
6.9 Random Processes： Introduction
6.9.1 Characterization of a Random Process
6.9.2 Stationary Random Processes
6.9.3 Wide—Sense Stationary Random Processes
6.9.4 Ergodic Random Processes
6.9.5 Properties of the Autocorrelation Function
6.9.6 Uncorrelated， Orthogonal， and Independent Random Processes
6.10 Power Spectrum of a Random Process
6.10.1 Wiener—Khinchin Theorem
6.10.2 Transmission of Random Signals Through Linear Time—Invariant Systems
6.11 Some Important Random Processes
6.11.1 Gaussian Random Process
6.11.2 White Gaussian Noise
6.11.3 Filtered White Gaussian Noise
6.12 Narrowband Noise
6.12.1 Narrowband White Gaussian Noise
6.12.2 Envelope of Sine Wave in Narrowband Noise
6.13 Noise Sources in Communication Systems
6.13.1 Thermal Noise
6.13.2 Available Power
6.13.3 Shot Noise
6.14 Characterization of System Noise
6.14.1 Noise Factor and Noise Figure
6.14.2 Effective Input Noise Temperature of a Subsystem
6.14.3 Noise Figure of a Cascade of Subsystems
6.14.4 Noise Factor of a Lossy Two—Port Network
6.15 MATLAB Simulation of Random Processes
6.15.1 Generating Arbitrary PDF Random Variables
6.15.2 Autocorrelation Function and Spectral Density
6.15.3 Samples of White Gaussian Noise
Final Remarks
Further Readings
Problems
MATLAB Problems
CHAPTER 7
Noise Performance of Analog Communication Systems
7.1 Noise Performance of Baseband Systems
7.2 Effect of Noise on the Performance of AM Systems
7.2.1 Noise Performance of DSB—SC
Experiment 7.1 Noise Performance of a DSB—SC AM System
7.2.2 Noise Performance of SSB—AM
Experiment 7.2 Noise Performance of an SSB—AM System
7.2.3 Noise Performance of Conventional AM
Experiment 7.3 Noise Performance of Conventional AM System
7.3 Noise Performance of Angle—Modulation Systems
7.3.1 High—CNR Operation
7.3.2 FM System Operation： Low—CNR Case
Experiment 7.4 Noise Performance of an FM System
7.4 Preemphasis and Deemphasis
7.5 Comparison of Analog Modulation Systems
7.6 Link Design
7.6.1 Analog Repeater
7.6.2 Performance of Analog Communication System Using Cascade of Repeaters
Final Remarks
Further Readings
Problems
MATLAB Problems
CHAPTER 8
Conversion of Analog Signals to Digital Format
8.1 Sampling of Low—Pass Signals
8.1.1 Nyquist—Shannon Sampling Theorem
8.1.2 DFT of the Sampled Sequence
8.1.3 Reconstruction of the Analog Signal
8.1.4 Practical Sampling Techniques
8.2 Aliasing
Experiment 8.1 Natural Sampling of a LP Random Signal
8.3 Digitization of Analog Signals
8.3.1 Quantization
8.3.2 Coding of Quantized Samples
8.3.3 Errors Introduced by Quantization Process
Experiment 8.2 Study of m—Bit Quantization Errors
8.3.4 Quantization Noise
8.4 Pulse Code Modulation
8.4.1 Nonuniform Quantization
8.5 Differential Pulse Code Modulation
8.6 Oversampling in Analog—to—Digital Conversion
8.7 Delta Modulation
8.7.1 Slope Overload and Granular Noise
8.7.2 Adaptive Delta Modulation
8.7.3 Continuously Variable Slope Delta Modulation
8.7.4 Quantization Noise
Experiment 8.3 Delta Modulation
8.8 Sigma—Delta Modulation
8.8.1 First—Order Sigma—Delta Modulation
8.8.2 Noise Performance
Experiment 8.4 Sigma—Delta Modulation
8.9 Sampling Theorem for Bandpass Signals
Experiment 8.5 Natural Sampling of a BP Random Signal
8.9.1 BP Sampling in Digital Receivers
Final Remarks
Further Readings
Problems
MATLAB Problems
CHAPTER 9
Digital Baseband Modulation
9.1 Pulse Amplitude Modulation
9.2 Binary Line—Coding Techniques
9.3 Spectra of Digital Baseband Signals
9.3.1 Power Spectral Density of Random Pulse Trains
9.3.2 Spectra of Binary Line Codes
Experiment 9.1 Waveforms and Spectra of Several Line—Coding Schemes
9.4 Bandwidth of Digital Baseband Signals
9.5 Spectral and Power Out—of—Band Plots
9.6 Block Line Codes
9.6.1 Binary Block Codes
9.6.2 Multilevel Block Codes
9.7 Scrambling
9.7.1 Frame—Synchronous Scrambler
9.7.2 SONET Scrambler
9.7.3 Self—Synchronous Scrambler
9.7.4 ATM Scrambler
9.8 Pulse Shaping to Improve Spectral Efficiency
9.8.1 Sinc Pulse
9.8.2 Raised Cosine Pulses
Experiment 9.2 Effect of Channel on Baseband Digital Signals
9.9 Estimation of Allowable Bit Rate
Final Remarks
Further Readings
Problems
MATLAB Problems
CHAPTER 10
Detection of Baseband Signals in Noise
10.1 Binary Signal Detection in AWGN
10.1.1 Probability of Bit Error
10.2 The Matched Filter
10.2.1 Correlation Detectors
10.2.2 Performance of Binary Signaling Systems
Experiment 10.1 Binary Antipodal System with Correlation Detector
Experiment 10.2 Binary Antipodal Signaling System with Matched—Filter Detection
10.3 Vector Space Concepts
10.3.1 Finite Dimensional Vector Spaces
10.3.2 Inner—Product Vector Spaces
10.3.3 Gram—Schmidt Orthonormalization Procedure
10.4 Vector Space Representation of Signals and WGN
10.4.1 Vector Space Representation of Waveforms
10.4.2 Examples of Signal Constellations
10.4.3 Vector Space Representation of WGN
10.5 M —ary Signal Detection in AWGN
10.5.1 The Maximum a Posteriori Detector
10.5.2 The Maximum Likelihood Detector
10.5.3 MAP and ML Detector Implementations
10.5.4 Decision Regions
10.6 Error Performance of ML Detectors
10.6.1 Two—Signal Error Probability
10.6.2 M —Signal Error Probability
10.6.3 Relationship Between Bit and Symbol Error Rates
10.7 Error Performance of M —ary PAM Signals
Experiment 10.3 Noise Performance of 4—PAM Signaling System
Final Remarks
Further Readings
Problems
MATLAB Problems
CHAPTER 11
Digital Information Transmission Using Carrier Modulation
11.1 Basic Concepts
11.1.1 Representations of Digitally Modulated Carrier Signals
11.2 Binary Amplitude—Shift Keying
11.2.1 Coherent Demodulation of BASK Signals
Experiment 11.1 BASK Simulation and Performance Comparison
11.3 Binary Phase—Shift Keying
11.3.1 Coherent Demodulation of BPSK Signals
Experiment 11.2 BPSK Simulation and Performance Comparison
11.4 Binary Frequency—Shift Keying
11.4.1 Orthogonality of BFSK Signals
11.4.2 Coherent Demodulation of BFSK Signals
Experiment 11.3 BFSK Simulation and Performance Comparison
11.5 Differential Binary Phase—Shift Keying
11.6 Noncoherent Demodulation of Binary Digital Carrier Signals
11.6.1 Noncoherent Binary ASK
11.6.2 Noncoherent Binary FSK
11.7 Quadrature Modulation Schemes
11.7.1 Demodulation of Quadrature—Modulated Signals
11.7.2 QPSK
Experiment 11.4 QPSK Simulation and Performance Comparison
11.7.3 Offset QPSK
Experiment 11.5 OQPSK Simulation and Performance Comparison
11.7.4 M —ary Phase—Shift Keying
11.8 Minimum Shift Keying
Experiment 11.6 MSK Simulation and Performance Comparison
11.9 Quadrature Amplitude Modulation
Experiment 11.716—QAM System Simulation and Performance Comparison
11.10 Spectra of Quadrature Modulated Signals
11.10.1 Other Bandwidth Definitions
11.11 Comparison of Carrier Modulation Schemes
Final Remarks
Further Readings
Problems
MATLAB Problems
CHAPTER 12
Digital Signal Transmission Through Time Dispersive Channels
12.1 Transmission of PAM Signals Through Bandlimited Channels
12.1.1 Eye Diagrams
12.2 Nyquist’s Criterion for Zero ISI
12.2.1 RC Pulse Signaling
12.3 Transmit and Receive Filters for Bandlimited AWGN Channels
12.3.1 Probability of Error Performance
12.4 Partial Response （Duobinary） Signaling
12.4.1 Detection of Duobinary Signals
12.4.2 Probability of Error Performance
12.5 Linear Equalizers
12.5.1 Zero—Forcing Equalizer
12.5.2 Minimum Mean—Square Error Equalizer
12.6 Adaptive Equalization
12.6.1 Least Mean Square Error Algorithm
12.7 Decision Feedback Equalizers
12.7.1 Coefficient Optimization
12.7.2 Channel Estimation
12.8 Performance of Linear and Decision Feedback Equalizers
Final Remarks
Further Readings
Problems
MATLAB Problems
CHAPTER 13
Digital Multiplexing and Synchronization
13.1 Digital Multiplexing
13.1.1 Plesiochronous Digital Hierarchies
13.1.2 Synchronization of PDH Signals
13.1.3 M12 Multiplexer： DS2 Frame
13.1.4 DS2 OH Bits
13.2 SONET
13.2.1 Multiplexing of SONET Signals
13.2.2 Synchronization of SONET Signals
13.3 Carrier Synchronization
13.3.1 Raised—Power Loops
13.3.2 Costas Loop
13.3.3 Effect of Noise on the Carrier Phase Estimation
13.3.4 Effect of Noise on the Performance of Carrier Synchronizers
13.4 Symbol Synchronization
13.4.1 Clock Recovery from NRZ Data
13.4.2 PLL for Clock Recovery
Experiment 13.1 SONET OC—48 Clock and Data Recovery Using PLL
13.5 Frame Synchronization
13.5.1 Performance of a Frame Synchronizer
13.5.2 Choice of Frame Alignment Word
Final Remarks
Further Readings
Problems
MATLAB Problems
CHAPTER 14
Information Theory and Compression Techniques
14.1 Basic Concepts of Information Theory
14.1.1 Joint and Conditional Entropy
14.1.2 Differential Entropy
14.1.3 Mutual Information
14.2 Source Coding
14.2.1 Discrete Memoryless Sources
14.2.2 Shannon’s Source Coding Theorem
14.3 Channel Coding
14.3.1 Modeling of Communication Channels
14.3.2 Capacity of a Communication Channel
14.3.3 Shannon’s Channel Capacity Theorem
14.3.4 Another Channel Coding Theorem
14.4 Capacity of AWGN Channels
14.4.1 Shannon’s Capacity Theorem for AWGN Channels
14.4.2 Capacity of Bandlimited AWGN Channels
14.4.3 Implications of Capacity Theorem for Bandlimited AWGN Channels
14.4.4 Power—Bandwidth Trade—Offs
14.5 Lossless Compression Techniques
14.5.1 Lossless Compression Techniques
14.5.2 Huffman Coding
14.5.3 Run—Length Encoding
14.5.4 Lempel—Ziv Coding
14.6 Image Compression： JPEG
14.6.1 Discrete Cosine Transform
14.6.2 JPEG Compression Standard
14.6.3 Subsampling of Chrominance Components
14.7 Digital Video Compression： MPEG
14.7.1 MPEG
Final Remarks
Further Readings
Problems
MATLAB Problems
APPENDIX A： Capacity of AWGN Channel： Alternative Proof
CHAPTER 15
Channel Coding Techniques
15.1 Block Codes
15.1.1 Linear Block Codes
15.1.2 Systematic Linear Block Codes
15.1.3 Error and Syndrome Vectors
15.2 Hard—Decision Decoding of Block Codes
15.2.1 Syndrome Decoding of Block Codes
15.2.2 Error—Detecting and Error—Correcting Capabilities
15.3 Cyclic Codes
15.3.1 Encoding of Systematic Cyclic Codes
15.3.2 Decoding of Cyclic Codes
15.3.3 Important Families of Block Codes
15.3.4 Cyclic Redundancy Check Codes
15.4 Error Correction Performance of Hard—Decision Decoded Block Codes
15.5 Soft—Decision Decoding of Block Codes
15.5.1 Soft—Decision Decoding Error Performance
15.5.2 Coding Gain
15.6 Convolutional Codes
15.6.1 Representation of Convolutional Codes
15.6.2 Decoding of Convolutional Codes
15.6.3 The Viterbi Algorithm
15.7 Error Performance of Convolutional Codes
15.7.1 Transfer Function of a Convolutional Code
15.7.2 Probability of Error for Convolutional Codes
15.7.3 Coding Gain
15.8 Turbo Codes
15.8.1 Turbo Decoding
15.8.2 Performance of Turbo Codes
15.9 Trellis—Coded Modulation
15.9.1 Decoding of TCM Codes
Final Remarks
Further Readings
Problems
MATLAB Problems
APPENDIX A
Mathematical Tables
APPENDIX B
Abbreviations
APPENDIX C
List of Symbols
Index
序言
Preface
Communication systems transfer information between different points in space or time. Contemporary Communication Systems provides a comprehensive introduction to analog and digital communication systems that form the infrastructure of today’s optical fiber, wireless, and satellite communication networks. The book not only provides a logical and easy-tounderstand presentation of the fundamental principles but also engages students in the issues relevant to system and product implementation.
As such, the book covers several topics that get scant coverage in other textbooks but are very relevant in implementing modern analog and digital communication systems.
The book is designed for introductory courses in communication systems and in digital communications at the upper-level undergraduate, and first-year graduate programs in electrical and computer engineering. It provides detailed coverage of the background required to study communication systems in two chapters, one on signals and systems with emphasis on the frequency-domain analysis, and the other on the probability theory and random processes. Analog communications systems are covered in Chapters 4, 5, and 7. These
chapters include not only the traditional material but some new topics that are relevant to the design of today’s wireless communication receivers and optical networks employing cascade of optical amplifiers. Digital transmission is the enabling technology for global Internet, optical fiber, and new generations of wireless networks. Chapters 8 to 15 cover various aspects of digital communications systems.
Organization
Chapter 1 provides an introduction to communication systems, the history of their development, and major trends driving their evolution.
Chapter 2 is a review of signals and systems with an emphasis on the frequency domain analysis of signal transmission through LTI systems.
Chapter 3 introduces the capabilities of Simulink® for modeling and the simulation of analog and digital communication systems.
Chapter 4 is devoted to various amplitude modulation schemes. We also discuss multiplexing techniques and key operations implemented in communication transmitters and receivers. The chapter concludes with a discussion of various receiver architectures implemented in modern communication systems.
Chapter 5 covers angle modulation systems (FM and PM). This is followed by a detailed treatment of analog phase-locked loops and analog NTSC TV system.
Chapter 6 reviews the basic concepts of probability theory and random processes that are relevant to the modeling and analysis of information signals and ubiquitous noise in communication systems. Transmission of random signals and noise through LTI systems are then analyzed in both time and frequency domains.
Chapter 7 addresses the effect of noise in the demodulation of amplitude- and angle-modulated signals. We compare the performance of analog communication systems and study the effects of transmission losses and noise on the design of analog transmission systems with repeaters.
Chapter 8 considers the conversion of analog signals into digital format. We study sampling theorem and quantization techniques
followed by waveform coding methods such as PCM, DPCM, and DM. The chapter concludes with a discussion of sigma-delta converters and bandpass sampling.
Chapter 9 presents baseband modulation schemes for transmission of digital data. Key requirements and characteristics of various line coding schemes are explained. We also study the design of pulse shapes to improve the spectral efficiency of digital baseband transmission systems.
In Chapter 10 we consider the detection of transmission symbols being conveyed in the digitally modulated signals in the presence of additive white Gaussian noise (AWGN). We introduce the representation of signal waveforms and AWGN as vectors in finitedimensional vector spaces and use these concepts to develop optimum detector structures and analyze their performance.
Chapter 11 considers the transmission of digital data by modulating a carrier. We consider binary and quadrature modulation schemes and analyze their performance using vector space concepts. Frequency shift keying and minimum shift keying are also treated.
Noncoherent and differentially coherent schemes are then discussed. The chapter concludes with spectral analysis and a comparison of
various digital carrier modulation schemes.
Chapter 12 treats the transmission of digitally modulated signals through channels that introduce inter-symbol interference (ISI) in addition to AWGN. We consider signal design and equalization schemes for the mitigation of ISI and noise.
Chapter 13 addresses two major topics in digital communications: digital multiplexing and synchronization. Multiplexing is used to combine multiple user signals for the efficient sharing of a high-speed communication channel. This is followed by the coverage of carrier, symbol timing, and frame sync recovery circuits that are used to properly recover and demultiplex the constituent signals at the receiver.
Chapter 14 is an introduction to information theory where we explain fundamental limits on communication of information. After introducing the concepts of information content of a source and capacity of a communication channel, we study Shannon’s theorems on source coding and channel capacity. The chapter concludes with a detailed treatment of text, image, and video compression schemes.
Chapter 15 is devoted to channel coding for reliable transmission of information over noisy communication channels. We consider both linear block codes and convolutional codes and their performance using hard- and soft-decision decoding strategies. Coding for bandlimited channels and capacity-achieving turbo codes are also treated.
Pedagogical Features
The pedagogical features of the book include the following:
Chapter introductions that preview the material covered in that chapter and its relevance in practice.
Numerous examples, including MATLAB® exercises, to reinforce the key concepts and mathematical results.
End-of-chapter problems with varying degrees of difficulty. MATLAB exercises are provided with extensive help to assist students in programming problem solutions.
Simulink is used as a key pedagogical tool to help students understand theoretical results and develop familiarity with key elements in the design of communication systems. The author believes that Simulink can be used as a virtual laboratory to conduct experiments in the classroom setting to
Display signal waveforms and spectra at various points in communication systems.
Analyze the performance of systems and compare them with theoretical results.
Study the design approaches and possible trade-offs.
Each chapter concludes with final remarks that reiterate the key concepts and comment on important developments.
Each chapter includes a list of references that point to further reading materials.
Extensive resources for instructors and students on the book’s website are provided.
The development of communication systems has a rich and interesting history. A special effort has been made in the text to chronicle the milestone events in the field with historical boxes sprinkled throughout the book.
Most chapters include interviews with modern pioneers and renowned contributors in the field of communications that should inspire and motivate students.
Course Options
The book can be used to offer a variety of courses in communication systems. By a selective choice of chapters and sections therein, the instructor can provide the desired concentration for the course or adjust the content for the background of the students. An important consideration in this context is whether or not the students have already taken a course in probability and random processes at a senior level. We offer the following options for consideration, although many variants are possible.
A one-semester course in analog and digital communication systems: Selected review of sections from Chapters 2 and 6, Chapters 3 through 5, Chapter 7: Sections 7.1 to 7.5, Chapter 8: Sections 8.1 to 8.4, Chapter 9: Sections 9.1 to 9.2, Chapter 10: Sections 10.1 to 10.2, Chapter 11: Sections 11.1 to 11.2, and selections from Chapters 14 through 15 if time permits.
A one-semester course in digital communications: Selected review of sections from Chapters 2 and 6, Chapter 3, and Chapters 8 through 15.
A two-semester course sequence in analog and digital communication systems:
Chapters 2 through 8 for the first course
Chapters 9 through 15 for the second course
Online Resources
A website to accompany this text can be found at www.mhhe.com/mesiya . The site contains an instructor’s solutions manual, lecture PowerPoints, MATLAB m-files, Simulink models for all experiments, additional problems, and an image library. Instructors can also obtain access to COSMOS—a Complete Online Solutions Manual Organization System, which instructors can use to create
exams and assignments, create custom content, and edit supplied problems and solutions.
Electronic Textbook Option
This text is offered through CourseSmart for both instructors and students. CourseSmart is an online resource where students can purchase the complete text online at almost half the cost of a traditional text. Purchasing the eTextbook allows students to take advantage of CourseSmart’s web tools for learning, which include full text search, notes and highlighting, and email tools for sharing notes between classmates. To learn more about CourseSmart options, contact your sales representative or visit www.CourseSmart.com.
McGraw-Hill Create
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