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Modern Digital and Analog Communications Systems 4th Revised edition [Pehme köide]

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(Professor, Professor Emeritus, Department of Electrical and Electronic Engineering, California State), (Professor, Department of Electrical and Computer Engineering, UC Davis)
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Modern Digital and Analog Communications Systems 4th Revised editionSuurem pilt
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Püsilink: https://www.kriso.ee/db/9780195384932.html
Modern Digital and Analog Communication Systems is ideal for the first communication systems course for electrical and computer engineers; it offers its readers a consistently superb pedagogical style and explains complex subjects and concepts clearly, using both mathematics and heuristics. This new edition seamlessly incorporates many new technological advances in Lathi's trademark style of user-friendliness and high readability. The text begins by introducing students to a panoramic view of communication systems, explaining important concepts of communication theory in a heuristic way. Only after a solid introduction to basic communication systems is analysis of communication systems requiring probability and random processes presented. The authors use real world examples to capture the students' attention and enable them to easily relate the course materials with their daily experience of communication tools. The text features easy-to-understand examples and MatLab exercises to clarify mathematical results and proofs. Among the newly introduced topics are spread spectrum communications and orthogonal frequency devision multiplexing (OFDM), error connection coding, soft-decoding, turbo codes and low density parity check (LDPC) codes. To better motivate various topics, the text provides many related applications including the latest wire-line (DSL) services, cellular systems, and the wireless local area networks (LANs). This unique text is highly informative, interactive, and accessible to beginning students as well as seasoned practitioners.
Preface xvii
1 Introduction
1(19)
1.1 Communication Systems
1(3)
1.2 Analog and Digital Messages
4(5)
1.2.1 Noise Immunity of Digital Signals
4(1)
1.2.2 Viability of Distortionless Regenerative Repeaters
5(1)
1.2.3 Analog-to-Digital (A/D) Conversion
6(1)
1.2.4 Pulse-Coded Modulation---A Digital Representation
7(2)
1.3 Channel Effect, Signal-To-Noise Ratio, and Capacity
9(2)
1.3.1 Signal Bandwidth and Power
9(1)
1.3.2 Channel Capacity and Data Rate
10(1)
1.4 Modulation and Detection
11(2)
1.4.1 Ease of Radiation/Transmission
11(1)
1.4.2 Simultaneous Transmission of Multiple Signals---Multiplexing
12(1)
1.4.3 Demodulation
13(1)
1.5 Digital Source Coding and Error Correction Coding
13(2)
1.6 A Brief Historical Review of Modern Telecommunications
15(5)
2 Signals and Signal Space
20(42)
2.1 Size of A Signal
20(2)
2.2 Classification of Signals
22(4)
2.2.1 Continuous Time and Discrete Time Signals
23(1)
2.2.2 Analog and Digital Signals
23(1)
2.2.3 Periodic and Aperiodic Signals
24(1)
2.2.4 Energy and Power Signals
25(1)
2.2.5 Deterministic and Random Signals
25(1)
2.3 Unit Impulse Signal
26(2)
2.4 Signals Versus Vectors
28(6)
2.4.1 Component of a Vector along Another Vector
28(2)
2.4.2 Decomposition of a Signal and Signal Components
30(2)
2.4.3 Complex Signal Space and Orthogonality
32(2)
2.4.4 Energy of the Sum of Orthogonal Signals
34(1)
2.5 Correlation of Signals
34(2)
2.5.1 Correlation Functions
35(1)
2.5.2 Autocorrelation Function
36(1)
2.6 Orthogonal Signal Set
36(3)
2.6.1 Orthogonal Vector Space
36(2)
2.6.2 Orthogonal Signal Space
38(1)
2.6.3 Parseval's Theorem
39(1)
2.7 The Exponential Fourier Series
39(7)
2.8 Matlab Exercises
46(16)
3 Analysis and Transmission of Signals
62(78)
3.1 Aperiodic Signal Representation By Fourier Integral
62(7)
3.2 Transforms of Some Useful Functions
69(6)
3.3 Some Properties of The Fourier Transform
75(15)
3.3.1 Time-Frequency Duality
76(1)
3.3.2 Duality Property
77(2)
3.3.3 Time-Scaling Property
79(2)
3.3.4 Time-Shifting Property
81(2)
3.3.5 Frequency-Shifting Property
83(4)
3.3.6 Convolution Theorem
87(1)
3.3.7 Time Differentiation and Time Integration
88(2)
3.4 Signal Transmission Through A Linear System
90(5)
3.4.1 Signal Distortion during Transmission
92(1)
3.4.2 Distortionless Transmission
92(3)
3.5 Ideal Versus Practical Filters
95(2)
3.6 Signal Distortion Over A Communication Channel
97(6)
3.6.1 Linear Distortion
97(2)
3.6.2 Distortion Caused by Channel Nonlinearities
99(2)
3.6.3 Distortion Caused by Multipath Effects
101(2)
3.6.4 Fading Channels
103(1)
3.7 Signal Energy And Energy Spectral Density
103(8)
3.7.1 Parseval's Theorem
103(1)
3.7.2 Energy Spectral Density (ESD)
104(1)
3.7.3 Essential Bandwidth of a Signal
105(3)
3.7.4 Energy of Modulated Signals
108(1)
3.7.5 Time Autocorrelation Function and the Energy Spectral Density
109(2)
3.8 Signal Power And Power Spectral Density
111(7)
3.8.1 Power Spectral Density (PSD)
111(2)
3.8.2 Time Autocorrelation Function of Power Signals
113(4)
3.8.3 Input and Output Power Spectral Densities
117(1)
3.8.4 PSD of Modulated Signals
118(1)
3.9 Numerical Computation of Fourier Transform: Thedft
118(5)
3.10 Matlab Exercises
123(17)
4 Amplitude Modulations And Demodulations
140(62)
4.1 Baseband Versus Carrier Communications
140(2)
4.2 Double-Sideband Amplitude Modulation
142(9)
4.3 Amplitude Modulation (AM)
151(7)
4.4 Bandwidth-Efficient Amplitude Modulations
158(9)
4.5 Amplitude Modulations: Vestigial Sideband (VSB)
167(3)
4.6 Local Carrier Synchronization
170(2)
4.7 Frequency Division Multiplexing (FDM)
172(1)
4.8 Phase-Locked Loop and Some Applications
173(8)
4.9 Matlab Exercises
181(21)
5 Angle Modulation and Demodulation
202(49)
5.1 Nonlinear Modulation
202(7)
5.2 Bandwidth of Angle-Modulated Waves
209(13)
5.3 Generating Fm Waves
222(9)
5.4 Demodulation of FM Signals
231(3)
5.5 Effects of Nonlinear Distortion And Interference
234(5)
5.6 Superheterodyne Analog AM/FM Receivers
239(2)
5.7 FM Broadcasting System
241(1)
5.8 Matlab Exercises
242(9)
6 Sampling and Analog-To-Digital Conversion
251(75)
6.1 Sampling Theorem
251(17)
6.1.1 Signal Reconstruction from Uniform Samples
253(5)
6.1.2 Practical Issues in Signal Sampling and Reconstruction
258(4)
6.1.3 Maximum Information Rate: Two Pieces of Information per Second per Hertz
262(1)
6.1.4 Nonideal Practical Sampling Analysis
263(4)
6.1.5 Some Applications of the Sampling Theorem
267(1)
6.2 Pulse Code Modulation (PCM)
268(13)
6.2.1 Advantages of Digital Communication
270(1)
6.2.2 Quantizing
271(3)
6.2.3 Principle of Progressive Taxation: Nonuniform Quantization
274(4)
6.2.4 Transmission Bandwidth and the Output SNR
278(3)
6.3 Digital Telephony: PCM in T1 Carrier Systems
281(4)
6.4 Digital Multiplexing
285(5)
6.4.1 Signal Format
285(2)
6.4.2 Asynchronous Channels and Bit Stuffing
287(1)
6.4.3 Plesiochronous (almost Synchronous) Digital Hierarchy
288(2)
6.5 Differential Pulse Code Modulation (DPCM)
290(4)
6.6 Adaptive Differential PCM (ADPCM)
294(1)
6.7 Delta Modulation
295(5)
6.8 Vocoders and Video Compression
300(10)
6.8.1 Linear Prediction Coding Vocoders
301(9)
6.9 Matlab Exercises
310(16)
7 Principles of Digital Data Transmission
326(67)
7.1 Digital Communication Systems
326(3)
7.1.1 Source
326(1)
7.1.2 Line Coder
327(1)
7.1.3 Multiplexer
328(1)
7.1.4 Regenerative Repeater
328(1)
7.2 Line Coding
329(14)
7.2.1 PSD of Various Line Codes
330(4)
7.2.2 Polar Signaling
334(2)
7.2.3 Constructing a DC Null in PSD by Pulse Shaping
336(1)
7.2.4 On-Off Signaling
337(2)
7.2.5 Bipolar Signaling
339(4)
7.3 Pulse Shaping
343(12)
7.3.1 Intersymbol Interferences (ISI) and Effect
343(1)
7.3.2 Nyquist's First Criterion for Zero ISI
344(6)
7.3.3 Controlled ISI or Partial Response Signaling
350(1)
7.3.4 Example of a Duobinary Pulse
351(1)
7.3.5 Pulse Relationship between Zero ISI, Duobinary, and Modified Duobinary
352(1)
7.3.6 Detection of Duobinary Signaling and Differential Encoding
353(2)
7.3.7 Pulse Generation
355(1)
7.4 Scrambling
355(3)
7.5 Digital Receivers and Regenerative Repeaters
358(8)
7.5.1 Equalizers
359(4)
7.5.2 Timing Extraction
363(2)
7.5.3 Detection Error
365(1)
7.6 Eye Diagrams: An Important Tool
366(3)
7.7 Pam: Mary Baseband Signaling for Higher Data Rate
369(3)
7.8 Digital Carrier Systems
372(8)
7.8.1 Basic Binary Carrier Modulations
372(2)
7.8.2 PSD of Digital Carrier Modulation
374(2)
7.8.3 Connections between Analog and Digital Carrier Modulations
376(1)
7.8.4 Demodulation
377(3)
7.9 Mary Digital Carrier Modulation
380(6)
7.10 Matlab Exercises
386(7)
8 Fundamentals of Probability Theory
393(63)
8.1 Concept of Probability
393(15)
8.2 Random Variables
408(19)
8.3 Statistical Averages (MEANS)
427(9)
8.4 Correlation
436(4)
8.5 Linear Mean Square Estimation
440(3)
8.6 Sum of Random Variables
443(3)
8.7 Central Limit Theorem
446(10)
9 Random Processes And Spectral Analysis
456(50)
9.1 From Random Variable to Random Process
456(5)
9.2 Classification of Random Processes
461(4)
9.3 Power Spectral Density
465(14)
9.4 Multiple Random Processes
479(1)
9.5 Transmission of Random Processes Through Linear Systems
480(3)
9.6 Application: Optimum Filtering (Wiener-Hopf Filter)
483(3)
9.7 Application: Performance Analysis of Baseband Analog Systems
486(2)
9.8 Application: Optimum Preemphasis-Deemphasis Systems
488(3)
9.9 Bandpass Random Processes
491(15)
10 Performance Analysis of Digital Communication Systems
506(108)
10.1 Optimum Linear Detector For Binary Polar Signaling
506(6)
10.1.1 Binary Threshold Detection
507(1)
10.1.2 Optimum Receiver Filter-Matched Filter
508(4)
10.2 General Binary Signaling
512(8)
10.2.1 Optimum Linear Receiver Analysis
512(4)
10.2.2 Performance Analysis of General Binary Systems
516(4)
10.3 Coherent Receivers for Digital Carrier Modulations
520(5)
10.4 Signal Space Analysis of Optimum Detection
525(5)
10.4.1 Geometrical Signal Space
525(2)
10.4.2 Signal Space and Basis Signals
527(3)
10.5 Vector Decomposition of White Noise Random Processes
530(6)
10.5.1 Determining Basis Functions for a Random Process
530(1)
10.5.2 Geometrical Representation of White Noise Processes
531(2)
10.5.3 White Gaussian Noise
533(1)
10.5.4 Properties of Gaussian Random Process
534(2)
10.6 Optimum Receiver for White Gaussian Noise Channels
536(25)
10.6.1 Geometric Representations
536(2)
10.6.2 Dimensionality of the Detection Signal Space
538(3)
10.6.3 (Simplified) Signal Space and Decision Procedure
541(4)
10.6.4 Decision Regions and Error Probability
545(6)
10.6.5 Multiamplitude Signaling (PAM)
551(3)
10.6.6 Mary QAM Analysis
554(7)
10.7 General Expression for Error Probability of Optimum Receivers
561(8)
10.8 Equivalent Signal Sets
569(8)
10.8.1 Minimum Energy Signal Set
572(3)
10.8.2 Simplex Signal Set
575(2)
10.9 Nonwhite (Colored) Channel Noise
577(1)
10.10 Other Useful Performance Criteria
578(3)
10.11 Noncoherent Detection
581(8)
10.12 Matlab Exercises
589(25)
11 Spread Spectrum Communications
614(52)
11.1 Frequency Hopping Spread Spectrum (FHSS) Systems
614(4)
11.2 Multiple FHSS User Systems And Performance
618(3)
11.3 Applications of FHSS
621(3)
11.4 Direct Sequence Spread Spectrum
624(4)
11.5 Resilient Features of DSSS
628(2)
11.6 Code Division Multiple-Access (CDMA) of Dsss
630(7)
11.7 Multiuser Detection (MUD)
637(6)
11.8 Modern Practical DSSS CDMA Systems
643(8)
11.8.1 CDMA in Cellular Phone Networks
643(4)
11.8.2 CDMA in the Global Positioning System (GPS)
647(2)
11.8.3 IEEE 802 11 b Standard for Wireless LAN
649(2)
11.9 Matlab Exercises
651(15)
12 Digital Communications Under Linearly Distortive Channels
666(68)
12.1 Linear Distortions of Wireless Multipath Channels
666(4)
12.2 Receiver Channel Equalization
670(6)
12.2.1 Antialiasing Filter vs. Matched Filter
670(3)
12.2.2 Maximum Likelihood Sequence Estimation (MLSE)
673(3)
12.3 Linear TSpaced Equalization (TSE)
676(8)
12.3.1 Zero-Forcing TSE
677(2)
12.3.2 TSE Design Based on MMSE
679(5)
12.4 Linear Fractionally Spaced Equalizers (FSE)
684(4)
12.4.1 The Single-Input-Multiple-Output (SIMO) Model
684(2)
12.4.2 FSE Designs
686(2)
12.5 Channel Estimation
688(1)
12.6 Decision Feedback Equalizer
689(3)
12.7 OFDM (Multicarrier) Communications
692(10)
12.7.1 Principles of OFDM
692(6)
12.7.2 OFDM Channel Noise
698(2)
12.7.3 Zero-Padded OFDM
700(1)
12.7.4 Cyclic Prefix Redundancy in OFDM
701(1)
12.7.5 OFDM Equalization
701(1)
12.8 Discrete Multitone (DMT) Modulations
702(5)
12.9 Real-Life Applications of OFDM And DMT
707(4)
12.10 Blind Equalization And Identification
711(1)
12.11 Time-Varying Channel Distortions Due to Mobility
712(3)
12.12 Matlab Exercises
715(19)
13 Introduction to Information Theory
734(68)
13.1 Measure of Information
734(5)
13.2 Source Encoding
739(6)
13.3 Error-Free Communication Over A Noisy Channel
745(3)
13.4 Channel Capacity of A Discrete Memoryless Channel
748(8)
13.5 Channel Capacity of A Continuous Memoryless Channel
756(17)
13.6 Practical Communication Systems in Light of Shannon's Equation
773(3)
13.7 Frequency-Selective Channel Capacity
776(5)
13.8 Multiple-Input-Multiple-Output Communication Systems
781(8)
13.8.1 Capacity of MIMO Channels
781(2)
13.8.2 Transmitter without Channel Knowledge
783(2)
13.8.3 Transmitter with Channel Knowledge
785(4)
13.9 Matlab Exercises
789(13)
14 Error Correcting Codes
802
14.1 Overview
802(1)
14.2 Redundancy For Error Correction
803(3)
14.3 Linear Block Codes
806(7)
14.4 Cyclic Codes
813(9)
14.5 The Effects of Error Correction
822(5)
14.6 Convolutional Codes
827(10)
14.6.1 Convolutional Encoder
827(4)
14.6.2 Decoding Convolutional Codes
831(6)
14.7 Trellis Diagram of Block Codes
837(2)
14.8 Code Combining And Interleaving
839(2)
14.9 Soft Decoding
841(3)
14.10 Soft-Output Viterbi Algorithm (SOVA)
844(2)
14.11 Turbo Codes
846(8)
14.12 Low-Density Parity Check (LDPC) Codes
854(7)
14.13 Matlab Exercises
861
A Orthogonality of Some Signal Sets
373(502)
A.1 Orthogonality of the Trigonometric And Exponential Signal Set
873(1)
A.2 Orthogonality of the Exponential Signal Set
874(1)
B Cauchy-Schwarz Inequality
875(2)
C Gram-Schmidt Orthogonalization of A Vector Set
877(3)
D Basic Matrix Properties and Operations
880(5)
D.1 Notation
880(1)
D.2 Matrix Product and Properties
881(1)
D.3 Identity and Diagonal Matrices
882(1)
D.4 Determinant of Square Matrices
882(1)
D.5 Trace
883(1)
D.6 Eigendecomposition
883(1)
D.7 Special Hermitian Square Matrices
884(1)
E Miscellaneous
885(4)
E.1 L'Hopital's Rule
885(1)
E.2 Taylor And Maclaurin Series
885(1)
E.3 Power Series
885(1)
E.4 Sums
886(1)
E.5 Complex Numbers
886(1)
E.6 Trigonometric Identities
886(1)
E.7 Indefinite Integrals
887(2)
Index 889