Digital communications / John G. Proakis.

By: Proakis, John G .

Material type: materialTypeLabel

BookSeries: McGraw-Hill series in electrical engineeringCommunications and information theory.Publisher: New York : McGraw-Hill, c1983Description: xvi, 608 p. : ill. ; 25 cm.ISBN: 0070509271 .Subject(s): Digital communications

DDC classification: 621.382

Contents:

Probability and stochastic processes -- Elements of a digital communications system and information theory -- Representation of bandpass signals and systems -- Modulation and demodulation for the additive Gaussian noise channel -- Efficient signaling with coded waveforms -- Digital signaling over a channel with intersymbol interference and additive Gaussian noise -- Digital signaling over fading multipath channels -- Spread spectrum signals for digital communications.

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode	Item holds
General Lending	MTU Bishopstown Library Lending	621.382 (Browse shelf(Opens below))	1	Available		00023759
General Lending	MTU Bishopstown Library Lending	621.382 (Browse shelf(Opens below))	1	Available		00035462

Total holds: 0

Enhanced descriptions from Syndetics:

Revised to reflect all the current trends in the digital communications field, this all-inclusive guide delivers an outstanding introduction to the analysis and design of digital communication systems. Includes expert coverage of new topics: Turbocodes, Turboequalization, Antenna Arrays, Digital Cellular Systems, and Iterative Detection. Convenient, sequential organization begins with a look at the historyo and classification of channel models and builds from there.

Includes bibliographical references and index.

Table of contents provided by Syndetics

Preface (p. xix)
1 Introduction (p. 1)
1.1 Elements of a Digital Communication System (p. 1)
1.2 Communication Channels and Their Characteristics (p. 3)
1.3 Mathematical Models for Communication Channels (p. 10)
1.4 A Historical Perspective in the Development of Digital Communications (p. 13)
1.5 Overview of the Book (p. 15)
1.6 Bibliographical Notes and References (p. 16)
2 Probability and Stochastic Processes (p. 17)
2.1 Probability (p. 17)
2.1.1 Random Variables, Probability Distributions, and Probability Densities
2.1.2 Functions of Random Variables
2.1.3 Statistical Averages of Random Variables
2.1.4 Some Useful Probability Distributions
2.1.5 Upper Bounds on the Tail Probability
2.1.6 Sums of Random Variables and the Central Limit Theorem
2.2 Stochastic Processes (p. 61)
2.2.1 Statistical Averages
2.2.2 Power Density Spectrum
2.2.3 Response of a Linear Time-Invariant System to a Random Input Signal
2.2.4 Sampling Theorem for Band-Limited Stochastic Processes
2.2.5 Discrete-Time Stochastic Signals and Systems
2.2.6 Cyclostationary Processes
2.3 Bibliographical Notes and References (p. 75)
Problems (p. 75)
3 Source Coding (p. 80)
3.1 Mathematical Models for Information Sources (p. 80)
3.2 A Logarithmic Measure of Information (p. 82)
3.2.1 Average Mutual Information and Entropy
3.2.2 Information Measures for Continuous Random Variables
3.3 Coding for Discrete Sources (p. 90)
3.3.1 Coding for Discrete Memoryless Sources
3.3.2 Discrete Stationary Sources
3.3.3 The Lempel-Ziv Algorithm
3.4 Coding for Analog Sources--Optimum Quantization (p. 103)
3.4.1 Rate-Distortion Function
3.4.2 Scalar Quantization
3.4.3 Vector Quantization
3.5 Coding Techniques for Analog Sources (p. 121)
3.5.1 Temporal Waveform Coding
3.5.2 Spectral Waveform Coding
3.5.3 Model-Based Source Coding
3.6 Bibliographical Notes and References (p. 140)
Problems (p. 141)
4 Characterization of Communication Signals and Systems (p. 148)
4.1 Representation of Band-Pass Signals and Systems (p. 148)
4.1.1 Representation of Band-Pass Signals
4.1.2 Representation of Linear Band-Pass Systems
4.1.3 Response of a Band-Pass System to a Band-Pass Signal
4.1.4 Representation of Band-Pass Stationary Stochastic Processes
4.2 Signal Space Representations (p. 158)
4.2.1 Vector Space Concepts
4.2.2 Signal Space Concepts
4.2.3 Orthogonal Expansions of Signals
4.3 Representation of Digitally Modulated Signals (p. 168)
4.3.1 Memoryless Modulation Methods
4.3.2 Linear Modulation with Memory
4.3.3 Non-linear Modulation Methods with Memory--CPFSK and CPM
4.4 Spectral Characteristics of Digitally Modulated Signals (p. 201)
4.4.1 Power Spectra of Linearly Modulated Signals
4.4.2 Power Spectra of CPFSK and CPM Signals
4.4.3 Power Spectra of Modulated Signals with Memory
4.5 Bibliographical Notes and References (p. 221)
Problem (p. 222)
5 Optimum Receivers for the Additive White Gaussian Noise Channel (p. 231)
5.1 Optimum Receiver for Signals Corrupted by Additive White Gaussian Noise (p. 231)
5.1.1 Correlation Demodulator
5.1.2 Matched-Filter Demodulator
5.1.3 The Optimum Detector
5.1.4 The Maximum-Likelihood Sequence Detector
5.1.5 A Symbol-by-Symbol MAP Detector for Signals with Memory
5.2 Performance of the Optimum Receiver for Memoryless Modulation (p. 254)
5.2.1 Probability of Error for Binary Modulation
5.2.2 Probability of Error for M-ary Orthogonal Signals
5.2.3 Probability of Error for M-ary Biorthogonal Signals
5.2.4 Probability of Error for Simplex Signals
5.2.5 Probability of Error for M-ary Binary-Coded Signals
5.2.6 Probability of Error for M-ary PAM
5.2.7 Probability of Error for M-ary PSK
5.2.8 Differential PSK (DPSK) and Its Performance
5.2.9 Probability of Error for QAM
5.2.10 Comparison of Digital Modulation Methods
5.3 Optimum Receiver for CPM Signals (p. 283)
5.3.1 Optimum Demodulation and Detection of CPM
5.3.2 Performance of CPM Signals
5.3.3 Symbol-by-Symbol Detection of CPM Signals
5.3.4 Suboptimum Demodulation and Detection of CPM Signals
5.4 Optimum Receiver for Signals with Random Phase in AWGN Channel (p. 300)
5.4.1 Optimum Receiver for Binary Signals
5.4.2 Optimum Receiver for M-ary Orthogonal Signals
5.4.3 Probability of Error for Envelope Detection of M-ary Orthogonal Signals
5.4.4 Probability of Error for Envelope Detection of Correlated Binary Signals
5.5 Performance Analysis for Wireline and Radio Communication Systems (p. 313)
5.5.1 Regenerative Repeaters
5.5.2 Link Budget Analysis in Radio Communication Systems
5.6 Bibliographical Notes and References (p. 318)
Problems (p. 319)
6 Carrier and Symbol Synchronziation (p. 333)
6.1 Signal Parameter Estimation (p. 333)
6.1.1 The Likelihood Function
6.1.2 Carrier Recovery and Symbol Synchronization in Signal Demodulation
6.2 Carrier Phase Estimation (p. 338)
6.2.1 Maximum-Likelihood Carrier Phase Estimation
6.2.2 The Phase-Locked Loop
6.2.3 Effect of Additive Noise on the Phase Estimate
6.2.4 Decision-Directed Loops
6.2.5 Non-Decision-Directed Loops
6.3 Symbol Timing Estimation (p. 359)
6.3.1 Maximum-Likelihood Timing Estimation
6.3.2 Non-Decision-Directed Timing Estimation
6.4 Joint Estimation of Carrier Phase and Symbol Timing (p. 366)
6.5 Performance Characteristics of ML Estimators (p. 368)
6.6 Bibliographical Notes and References (p. 371)
Problems (p. 372)
7 Channel Capacity and Coding (p. 376)
7.1 Channel Models and Channel Capacity (p. 376)
7.1.1 Channel Models
7.1.2 Channel Capacity
7.1.3 Achieving Channel Capacity with Orthogonal Signals
7.1.4 Channel Reliability Functions
7.2 Random Selection of Codes (p. 392)
7.2.1 Random Coding Based on M-ary Binary-Coded Signals
7.2.2 Random Coding Based on M-ary Multiamplitude Signals
7.2.3 Comparison of R*[subscript 0] with the Capacity of the AWGN Channel
7.3 Communication System Design Based on the Cutoff Rate (p. 402)
7.4 Bibliographical Notes and References (p. 408)
Problems (p. 409)
8 Block and Convolutional Channel Codes (p. 416)
8.1 Linear Block Codes (p. 416)
8.1.1 The Generator Matrix and the Parity Check Matrix
8.1.2 Some Specific Linear Block Codes
8.1.3 Cyclic Codes
8.1.4 Optimum Soft-Decision Decoding of Linear Block Codes
8.1.5 Hard-Decision Decoding of Linear Block Codes
8.1.6 Comparison of Performance Between Hard-Decision and Soft-Decision Decoding
8.1.7 Bounds on Minimum Distance of Linear Block Codes
8.1.8 Nonbinary Block Codes and Concatenated Block Codes
8.1.9 Interleaving of Coded Data for Channels with Burst Errors
8.1.10 Serial and Parallel Concatenated Block Codes
8.2 Convolutional Codes (p. 471)
8.2.1 The Transfer Function of a Convolutional Code
8.2.2 Optimum Decoding of Convolutional Codes--The Viterbi Algorithm
8.2.3 Probability of Error for Soft-Decision Decoding
8.2.4 Probability of Error for Hard-Decision Decoding
8.2.5 Distance Properties of Binary Convolutional Codes
8.2.6 Punctured Convolutional Codes
8.2.7 Other Decoding Algorithms for Convolutional Codes
8.2.8 Practical Considerations in the Application of Convolutional Codes
8.2.9 Nonbinary Dual-k Codes and Concatenated Codes
8.2.10 Parallel and Serial Concatenated Convolutional Codes
8.3 Coded Modulation for Bandwidth-Constrained Channels--Trellis-Coded Modulation (p. 522)
8.4 Bibliographical Notes and References (p. 539)
Problems (p. 541)
9 Signal Design for Band-Limited Channels (p. 548)
9.1 Characterization of Band-Limited Channels (p. 548)
9.2 Signal Design for Band-Limited Channels (p. 554)
9.2.1 Design of Band-Limited Signals for No Intersymbol Interference--The Nyquist Criterion
9.2.2 Design of Band-Limited Signals with Controlled ISI--Partial-Response Signals
9.2.3 Data Detection for Controlled ISI
9.2.4 Signal Design for Channels with Distortion
9.3 Probability of Error in Detection of PAM (p. 574)
9.3.1 Probability of Error for Detection of PAM with Zero ISI
9.3.2 Probability of Error for Detection of Partial-Response Signals
9.4 Modulation Codes for Spectrum Shaping (p. 578)
9.5 Bibliographical Notes and References (p. 588)
Problems (p. 588)
10 Communication Through Band-Limited Linear Filter Channels (p. 598)
10.1 Optimum Receiver for Channels with ISI and AWGN (p. 599)
10.1.1 Optimum Maximum-Likelihood Receiver
10.1.2 A Discrete-Time Model for a Channel with ISI
10.1.3 The Viterbi Algorithm for the Discrete-Time White Noise Filter Model
10.1.4 Performance of MLSE for Channels with ISI
10.2 Linear Equalization (p. 616)
10.2.1 Peak Distortion Criterion
10.2.2 Mean-Square-Error (MSE) Criterion
10.2.3 Performance Characteristics of the MSE Equalizer
10.2.4 Fractionally Spaced Equalizers
10.2.5 Baseband and Passband Linear Equalizers
10.3 Decision-Feedback Equalization (p. 638)
10.3.1 Coefficient Optimization
10.3.2 Performance Characteristics of DFE
10.3.3 Predictive Decision-Feedback Equalizer
10.3.4 Equalization at the Transmitter--Tomlinson-Harashima Precoding
10.4 Reduced Complexity ML Detectors (p. 647)
10.5 Iterative Equalization and Decoding--Turbo Equalization (p. 649)
10.6 Bibliographical Notes and References (p. 651)
Problems (p. 652)
11 Adaptive Equalization (p. 660)
11.1 Adaptive Linear Equalizer (p. 660)
11.1.1 The Zero-Forcing Algorithm
11.1.2 The LMS Algorithm
11.1.3 Convergence Properties of the LMS Algorithm
11.1.4 Excess MSE Due to Noisy Gradient Estimates
11.1.5 Accelerating the Initial Convergence Rate in the LMS Algorithm
11.1.6 Adaptive Fractionally Spaced Equalizer--The Tap Leakage Algorithm
11.1.7 An Adaptive Channel Estimator for ML Sequence Detection
11.2 Adaptive Decision-Feedback Equalizer (p. 677)
11.3 Adaptive Equalization of Trellis-Coded Signals (p. 678)
11.4 Recursive Least-Squares Algorithms for Adaptive Equalization (p. 682)
11.4.1 Recursive Least-Squares (Kalman) Algorithm
11.4.2 Linear Prediction and the Lattice Filter
11.5 Self-Recovering (Blind) Equalization (p. 693)
11.5.1 Blind Equalization Based on the Maximum-Likelihood Criterion
11.5.2 Stochastic Gradient Algorithms
11.5.3 Blind Equalization Algorithms Based on Second- and Higher-Order Signal Statistics
11.6 Bibliographical Notes and References (p. 704)
Problems (p. 705)
12 Multichannel and Multicarrier Systems (p. 709)
12.1 Multichannel Digital Communications in AWGN Channels (p. 709)
12.1.1 Binary Signals
12.1.2 M-ary Orthogonal Signals
12.2 Multicarrier Communications (p. 715)
12.2.1 Capacity of a Nonideal Linear Filter Channel
12.2.2 An FFT-Based Multicarrier System
12.2.3 Minimizing Peak-to-Average Ratio in the Multicarrier Systems
12.3 Bibliographical Notes and References (p. 723)
Problems (p. 724)
13 Spread Spectrum Signals for Digital Communications (p. 726)
13.1 Model of Spread Spectrum Digital Communication System (p. 728)
13.2 Direct Sequence Spread Spectrum Signals (p. 729)
13.2.1 Error Rate Performance of the Decoder
13.2.2 Some Applications of DS Spread Spectrum Signals
13.2.3 Effect of Pulsed Interference on DS Spread Spectrum Systems
13.2.4 Excision of Narrowband Interference in DS Spread Spectrum Systems
13.2.5 Generation of PN Sequences
13.3 Frequency-Hopped Spread Spectrum Signals (p. 771)
13.3.1 Performance of FH Spread Spectrum Signals in an AWGN Channel
13.3.2 Performance of FH Spread Spectrum Signals in Partial-Band Interference
13.3.3 A CDMA System Based on FH Spread Spectrum Signals
13.4 Other Types of Spread Spectrum Signals (p. 784)
13.5 Synchronization of Spread Spectrum Systems (p. 786)
13.6 Bibliographical Notes and References (p. 792)
Problems (p. 794)
14 Digital Communications through Fading Multipath Channels (p. 800)
14.1 Characterization of Fading Multipath Channels (p. 801)
14.1.1 Channel Correlation Functions and Power Spectra
14.1.2 Statistical Models for Fading Channels
14.2 The Effect of Signal Characteristics on the Choice of a Channel Model (p. 814)
14.3 Frequency-Nonselective, Slowly Fading Channel (p. 816)
14.4 Diversity Techniques for Fading Multipath Channels (p. 821)
14.4.1 Binary Signals
14.4.2 Multiphase Signals
14.4.3 M-ary Orthogonal Signals
14.5 Digital Signaling over a Frequency-Selective, Slowly Fading Channel (p. 840)
14.5.1 A Tapped-Delay-Line Channel Model
14.5.2 The RAKE Demodulator
14.5.3 Performance of RAKE Demodulator
14.5.4 Receiver Structures for Channels with Intersymbol Interference
14.6 Coded Waveforms for Fading Channels (p. 852)
14.6.1 Probability of Error for Soft-Decision Decoding of Linear Binary Block Codes
14.6.2 Probability of Error for Hard-Decision Decoding of Linear Binary Block Codes
14.6.3 Upper Bounds on the Performance of Convolutional Codes for a Rayleigh Fading Channel
14.6.4 Use of Constant-Weight Codes and Concatenated Codes for a Fading Channel
14.6.5 System Design Based on the Cutoff Rate
14.6.6 Performance of Coded Phase-Coherent Communication Systems--Bit-Interleaved Coded Modulation
14.6.7 Trellis-Coded Modulation
14.7 Multiple-Antenna Systems (p. 878)
14.8 Bibliographical Notes and References (p. 885)
Problems (p. 887)
15 Multiuser Communications (p. 896)
15.1 Introduction to Multiple Access Techniques (p. 896)
15.2 Capacity of Multiple Access Methods (p. 899)
15.3 Code-Division Multiple Access (p. 905)
15.3.1 CDMA Signal and Channel Models
15.3.2 The Optimum Receiver
15.3.3 Suboptimum Detectors
15.3.4 Successive Interference Cancellation
15.3.5 Performance Characteristics of Detectors
15.4 Random Access Methods (p. 922)
15.4.1 ALOHA Systems and Protocols
15.4.2 Carrier Sense Systems and Protocols
15.5 Bibliographical Notes and References (p. 931)
Problems (p. 933)
Appendix A The Levinson-Durbin Algorithm (p. 939)
Appendix B Error Probability for Multichannel Binary Signals (p. 943)
Appendix C Error Probabilities for Adaptive Reception of M-Phase Signals (p. 949)
C.1 Mathematical Model for M-Phase Signaling Communication System (p. 949)
C.2 Characteristic Function and Probability Density Function of the Phase [theta] (p. 952)
C.3 Error Probabilities for Slowly Rayleigh Fading Channels (p. 953)
C.4 Error Probabilities for Time-Invariant and Ricean Fading Channels (p. 956)
Appendix D Square-Root Factorization (p. 961)
References and Bibliography (p. 963)
Index (p. 993)

Digital communications / John G. Proakis.

By: Proakis, John G.

Enhanced descriptions from Syndetics:

Table of contents provided by Syndetics

By: Proakis, John G .