`SING
`ENGINEERING
`
`Masoud Saleht
`
`John G. Proakis
`
`|
`
`IPR2018-01477
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`
`
`Communication
`Systems
`Engineering
`
`
`John G. Proakis
`
`MasoudSalehi
`
`Northeastern University
`
`=
`
`PRENTICE HALL,Englewood Cliffs, New Jersey 07632
`
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`Library of Congress Cataloging-in-Publication Data
`
`Proakis, John G.
`Communication systems engineering / John G. Proakis, Masoud
`Salehi.
`cm.
`Pp.
`Includes bibliographical references and index.
`ISBN 0-13-158932-6
`1. Telecommunication.
`TKS101-P75 1994
`621.382—dc20
`
`I. Salehi, Masoud.
`
`II. Title.
`
`93-23109
`CIP
`
`Acquisitions editor: DON FOWLEY
`Production editor: IRWIN ZUCKER
`Production coordinator: DAVID DICKEY
`Supplements editor: ALICE DWORKIN
`Copy editors: JOHN COOK and ANNA HALASZ
`Cover design: DESIGN SOLUTIONS
`Editorial assistant: JENNIFER KLEIN
`
`
`
`© 1994 by Prentice-Hall, Inc.
`A Paramount Communications Company
`Englewood Cliffs, New Jersey 07632
`
`All rights reserved. Nopart of this book may be
`reproduced, in any form or by any means,
`withoutpermission in writing from the publisher.
`
`Printed in the United States of America
`
`CE ONES
`
`I
`
`Cy
`
`Shot't.
`
`3}
`
`op)
`
`ISBN 0-13-158932-4
`
`Prentice-Hall International (UK) Limited, London
`Prentice-Hall of Australia Pty. Limited, Sydney
`Prentice-Hall Canada Inc., Toronto
`Prentice-Hall Hispanoamericana, S.A., Mexico
`Prentice-Hall of India Private Limited, New Delhi
`Prentice-Hall of Japan, Inc., Tokyo
`Simon & Schuster Asia Pte. Ltd., Singapore
`Editora Prentice-Hall do Brasil, Ltda., Rio de Janeiro
`
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`ik
`
`Contents
`
`Preface
`Introduction
`
`1
`
`iN
`Lez
`
`133
`1.4
`13S
`1.6
`
`Historical Review 2
`Elements of an Electrical Communication System 5
`1.2.1 Digital Communication System, 8
`1.2.2 Early Work in Digital Communications, I]
`Communication Channels and Their Characteristics
`Mathematical Models for Communication Channels
`Organization of the Book
`23
`Further Reading
`25
`
`13
`21
`
`xv
`1
`
`vii
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`viii
`
`2 Signals and Linear Systems
`
`Del
`
`Basic Concepts
`
`27
`
`Contents
`
`26
`
`2.1.1 Classification of Signals, 27
`2.1.2
`Some Important Signals and Their Properties, 36
`2.1.3 Classification of Systems, 42
`2.1.4 Analysis of LTI Systems in the Time Domain, 45
`
`2.2
`
`Fourier Series
`
`47
`
`Signal Space Concepts, 48
`2.2.1
`2.2.2 Orthogonal Expansionof Signals, 53
`2.2.3 Fourier Series and Its Properties, 55
`2.2.4 Response of LTI Systems to Periodic Signals, 65
`2.2.5 Parseval’s Relation, 68
`
`23
`
`Fourier Transforms
`
`70
`
`From Fourier Series to Fourier Transforms, 70
`2.3.1
`2.3.2 Basic Properties of the Fourier Transform, 78
`2.3.3 Fourier Transform for Periodic Signals, 91
`2.3.4 Transmission over LTI Systems, 94
`
`2.4
`
`Power and Energy
`
`97
`
`2.4.1 Energy-Type Signals, 98
`2.4.2
`Power-Type Signals, 10]
`
`2.5
`
`Sampling of Signals
`and Signal Reconstruction from Samples
`2.5.1
`Ideal Sampling, 104
`2.5.2 Practical Sampling, 110
`
`104
`
`2.6
`
`Bandpass Signals
`
`112
`
`2.6.1 Properties of the Hilbert Transform, 122
`
`Da].
`
`Further Reading
`Problems
`125
`
`125
`
`3 Random Processes
`
`143
`
`3.1
`
`Se
`
`33
`
`144
`Probability and Random Variables
`160
`Random Processes: Basic Concepts
`3.2.1 Description of Random Processes, 162
`3.2.2 Statistical Averages, 164
`3.2.3 Stationary Processes, 167
`3.2.4 Random processes and linear systems, 175
`Random Processes in the Frequency Domain
`
`178
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`221
`
`Contents
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`3.3.1 Power Spectrum of Stochastic Processes, 179
`3.3.2 Transmission over LTI Systems, 185
`
`3.4
`
`Gaussian and White Processes
`
`188
`
`3.5
`
`3.6
`
`3:7
`
`3.4.1 Gaussian Processes, 188
`3.4.2 White Processes, 190
`
`Bandlimited Processes and Sampling
`Bandpass Processes
`196
`
`193
`
`Further Reading
`
`204
`
`Problems
`
`204
`
`4 Information Sources and Source Coding
`Modeling of Information Sources
`222
`4.1.1 Measure of Information, 223
`4.1.2
`Joint and Conditional Entropy, 225
`
`4.1
`
`4.2
`
`4.3
`
`Source-Coding Theorem 228
`
`Source-Coding Algorithms
`
`230
`
`The Huffman Source-Coding Algorithm, 230
`4.3.1
`4.3.2 The Lempel-Ziv Source Coding Algorithm, 235
`
`4.4
`
`Rate-Distortion Theory
`
`237
`
`4.4.1 Mutual Information, 238
`4.4.2 Differential Entropy, 239
`4.4.3 Rate-Distortion Function, 240
`
`4.5
`
`Quantization
`
`246
`
`4.5.1 Scalar Quantization, 247
`4.5.2 Vector Quantization, 256
`
`4.6
`
`Waveform Coding
`
`259
`
`Pulse-Code Modulation, 259
`4.6.1
`4.6.2 Differential Pulse-Code Modulation, 264
`4.6.3 Delta Modulation, 267
`
`4.7
`
`4.8
`
`270
`Analysis-Synthesis Techniques
`Digital Audio Transmission and Digital Audio Recording
`4.8.1 Digital Audio in Telephone Transmission Systems, 274
`4.8.2 Digital Audio Recording, 276
`
`274
`
`4.9
`
`Further Reading
`
`282
`
`Problems
`
`282
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`x
`
`5 Analog Signal Transmission and Reception
`
`Contents
`
`296
`
`5.1
`
`3:2
`
`5.3
`
`Introduction to Modulation
`
`297
`
`298
`Amplitude Modulation
`5.2.1 Double-Sideband Suppressed Carrier AM, 298
`5.2.2 Conventional Amplitude Modulation, 306
`5.2.3 Single-Sideband AM, 310
`5.2.4 Vestigial-Sideband AM, 317
`5.2.5
`Implementation of AM Modulators and Demodulators, 320
`5.2.6 Signal Multiplexing, 326
`
`328
`Angle Modulation
`5.3.1 Representation of FM and PM Signals, 329
`5.3.2 Spectral Characteristics of Angle Modulated Signals, 333
`5.3.3.
`Implementation of Angle Modulators and Demodulators, 343
`
`5.4
`
`Radio and Television Broadcasting
`
`351
`
`5.4.1 AM Radio Broadcasting, 351
`5.4.2 FM Radio Broadcasting, 354
`5.4.3 Television Broadcasting, 356
`
`Mobile Radio Systems
`
`367
`
`Further Reading
`
`369
`
`Problems
`
`370
`
`a5
`
`5.6
`
`6 Effect of Noise on Analog Communication Systems
`
`385
`
`6.1
`
`Effect of Noise on Linear Modulation Systems
`
`386
`
`6.1.1 Effect of Noise on a Baseband System, 386
`6.1.2 Effect of Noise on DSB-SC AM, 386
`6.1.3 Effect of Noise on SSB AM, 388
`6.1.4 Effect of Noise on Conventional AM, 389
`
`Carrier Phase Estimation with a Phase-Locked Loop
`6.2.1 Effect of Additive Noise on Phase Estimation, 398
`
`394
`
`Effect of Noise on Angle Modulation
`404
`6.3.1 Threshold Effect in Angle Modulation, 414
`6.3.2 Pre-emphasis and De-emphasis Filtering, 418
`Comparison of Analog-Modulation Systems
`421
`Effects of Transmission Losses and Noise
`in Analog Communication Systems
`422
`6.5.1 Characterization of Thermal Noise Sources, 423
`
`6.2
`
`6.3
`
`6.4
`
`6.5
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`xi
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`6.5.2 Effective Noise Temperature and Noise Figure, 424
`6.5.3 Transmission Losses, 427
`6.5.4 Repeaters for Signal Transmission, 428
`
`6.6
`
`Further Reading
`
`431
`
`Problems
`
`431
`
`7 Digital Transmission Through
`an Additive White Gaussian Noise Channel
`
`437
`
`sles
`
`Pulse Modulation Signals
`and Their Geometric Representation
`
`438
`
`Pulse Modulation Signals, 438
`7.1.1
`7.1.2 Geometric Representation of Signal Waveforms, 444
`7.1.3 Geometric Representation of M-ary Pulse Modulation Signals, 448
`7.1.4 Modulation Codes and Modulation Signals with Memory, 453
`
`Ved
`
`Optimum Receiver for Pulse-Modulated Signals
`in Additive White Gaussian Noise
`467
`
`7.2.1 Correlation-Type Demodulator, 469
`7.2.2 Matched-Filter-Type Demodulator, 474
`7.2.3 The Optimum Detector, 480
`7.2.4 The Maximum-Likelihood Sequence Detector, 484
`
`Ds
`
`Probability of Error for Signals
`in Additive White Gaussian Noise
`
`488
`
`Probability of Error for Binary Modulation, 488
`7.3.1
`7.3.2. Probability of Error for M-ary Modulation, 492
`7.3.3 Probability of Error for ML Sequence Detection, 502
`7.3.4 Comparison of Modulation Methods, 504
`Regenerative Repeaters and Link Budget Analysis
`7.4.1 Regenerative Repeaters, 507
`7.4.2 Link Budget Analysis for Radio Channels, 509
`
`506
`
`74
`
`7.5
`
`Further Reading
`
`512
`
`Problems
`
`513
`
`Digital PAM Transmission
`Through Bandlimited AWGN Channels
`
`530
`
`8.1
`
`Digital Transmission
`Through Bandlimited Baseband Channels
`8.1.1 Digital PAM Transmission
`Through Bandlimited Baseband Channels, 535
`
`531
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`xii
`
`Contents
`
`8.2
`
`8.3
`
`8.4
`
`8.5
`
`8.1.2 The Power Spectrum of a Digital PAM Signal, 537
`8.1.3 The Power Spectrum of Digital Signals with Memory, 542
`Signal Design for Bandlimited Channels
`547
`8.2.1 Design of Bandlimited Signals
`for Zero ISI—The Nyquist Criterion, 548
`8.2.2 Design of Bandlimited Signals with Controlled ISI—
`Partial Response Signals, 555
`8.2.3 Data Detection for Controlled ISI, 558
`Probability of Error in Detection of Digital PAM 564
`8.3.1
`Probability of Error for Detection
`of Digital PAM with Zero ISI, 565
`8.3.2 Probability of Error for Detection of Partial Response Signals, 566
`System Design in the Presence of Channel Distortion
`570
`8.4.1 Design of Optimum Transmitting and Receiving Filters, 572
`8.4.2 Channel Equalization, 577
`
`595
`Symbol Synchronization
`8.5.1 Spectral-Line Methods, 597
`8.5.2 Early—Late Gate Synchronizers, 600
`8.5.3 Minimum Mean-Square-Error Method, 603
`8.5.4 Maximum-Likelihood Methods, 603
`
`8.6
`
`Further Reading
`
`606
`
`Problems
`
`606
`
`Digital Transmission via Carrier Modulation
`
`617
`
`9.1
`
`Carrier-Amplitude Modulation
`
`618
`
`9.1.1 Amplitude Demodulation and Detection, 621
`9.1.2 Probability of Error for PAM in an AWGN Channel, 624
`9.1.3 Signal Demodulation in the Presence of Channel Distortion, 626
`
`oz
`
`Carrier-Phase Modulation
`
`628
`
`9.2.1 Phase Demodulation and Detection, 633
`9.2.2 Probability of Error for Phase Modulation in
`an AWGNChannel, 636
`9.2.3 Carrier Phase Estimation, 640
`9.2.4 Differential-Phase Modulation and Demodulation, 643
`9.2.5 Probability of Error for DPSK in an AWGN Channel, 645
`
`9.3
`
`Quadrature Amplitude Modulation
`
`646
`
`9.3.1 Demodulation and Detection of QAM, 649
`9.3.2 Probability of Error for QAM in AWGN Channel, 652
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`xiii
`
`9.3.3 Carrier-Phase Estimation, 658
`
`9.4
`
`Carrier-Frequency Modulation
`
`659
`
`Frequency-Shift Keying, 659
`9.4.1
`9.4.2 Demodulation and Detection of FSK Signals, 661
`9.4.3 Probability of Error for Noncoherent Detection of FSK, 667
`9.4.4 Continuous-Phase FSK, 671
`9.4.5 Spectral Characteristics of CPFSK Signals, 678
`
`9.5
`
`Continuous-Phase Carrier Modulation
`
`681
`
`9.6
`
`9.5.1 Demodulation and Detection of CPM Signals, 686
`9.5.2 Performance of CPM in an AWGN Channel, 691
`9.5.3 Spectral Characteristics of CPM Signals, 694
`695
`Digital Transmission on Fading Multipath Channels
`9.6.1 Channel Model for Time-Variant Multipath Channels, 697
`9.6.2 Signal Design for Fading Multipath Channels, 703
`9.6.3 Performance of Binary Modulation
`in Rayleigh Fading Channels, 706
`
`OFT.
`
`Further Reading
`
`713
`
`Problems
`
`714
`
`10 Channel Capacity and Coding
`
`726
`
`10.1
`
`10.2
`
`10.3
`
`10.4
`
`10.5
`
`10.6
`
`10.7
`
`Modeling of Communication Channels
`Channel Capacity
`729
`10.2.1 Gaussian Channel Capacity, 733
`
`726
`
`736
`Bounds on Communication
`10.3.1 Transmission of Analog Sources by PCM, 740
`Coding for Reliable Communication
`742
`10.4.1 A Tight Bound on Error Probability of Orthogonal Signals, 743
`10.4.2 The Promise of Coding, 746
`
`753
`Linear Block Codes
`10.5.1 Decoding and Performance of Linear Block Codes, 757
`10.5.2 Burst-Error-Correcting-Codes, 767
`
`769
`Cyclic Codes
`10.6.1
`The Structure of Cyclic Codes, 769
`
`777
`Convolutional Codes
`10.7.1 Basic Properties of Convolutional Codes, 779
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`17
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`10.7.2 Optimum Decoding
`of Convolutional Codes—TheViterbi Algorithm, 784
`10.7.3 Other Decoding Algorithms for Convolutional Codes, 789
`10.7.4 Bounds on Error Probability of Convolutional Codes, 789
`Coding for Bandwidth Constrained Channels
`792
`10.8.1 Combined Coding and Modulation, 794
`10.8.2 Trellis Coded Modulation, 796
`Practical Applications of Coding
`803
`10.9.1 Coding for Deep-Space Communications, 803
`10.9.2. Coding for Telephone-Line Modems, 804
`10.9.3 Coding for Compact Disks, 805
`Further Reading
`809
`Problems
`809
`
`10.8
`
`10.9
`
`10.10
`
`Contents
`
`822
`
`Spread-Spectrum Communication Systems
`11.1
`Modelof
`a Spread-Spectrum Digital Communication Systems
`Direct-Sequence Spread Spectrum Systems
`825
`11.2.1 Probability of Error, 829
`11.2.2 Some Applications ofDS Spread-Spectrum Signals, 837
`11.2.3 Generation of PN Sequences, 844
`Frequency-Hopped Spread Spectrum 848
`11.3.1
`Slow Frequency-Hopping Systems, 85]
`11.3.2 Fast Frequency-Hopping Systems, 853
`11.3.3 Applications of FH Spread Spectrum, 855
`Other Types of Spread-Spectrum Signals
`856
`Synchronization of Spread-Spectrum Systems
`Further Reading
`865
`Problems
`865
`
`Ble2
`
`11.3
`
`11.4
`11.5
`11.6
`
`823
`
`857
`
`Appendix A: The Probability of Error
`for Multichannel Reception of Binary Signals
`References
`Index
`
`869
`873
`881
`
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`
`
`Ionosphere
`-
`
`~
`
`Introduction
`
`
`Every day, in our work and in our leisure time, we come in contact with and we use
`a variety of modern communication systems and communication media, the most
`common being the telephone, radio, and television. Through these media we are
`able to communicate (nearly) instantaneously with people on different continents,
`transact our daily business, and receive information about various developments
`and events of note that occurall around the world. Electronic mail and facsimile
`transmission have madeit possible to rapidly communicate written messages across
`great distances.
`Can you imagine a world without telephones, radio, and TV? Yet, when you
`think aboutit, most of these modern-day communication systems were invented and
`developed during the past century. Below, we present a brief historical review of
`major developments within the last two hundred years that have had a major role in
`the development of modern communication systems.
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`
`2
`1.1 HISTORICAL REVIEW
`
`Introduction
`
`Chap.
`
`1
`
`Oneof the earliest inventions of major signif-
`Telegraphy and telephony.
`icance to communications was the invention of the electric battery by Alessandro
`Volta in 1799. This invention made it possible for Samuel Morse to develop the
`electric telegraph, which he demonstrated in 1837. The first telegraph line linked
`Washington with Baltimore and became operational in May 1844. Morse devised
`the variable-length binary code given in Table 1.1,
`in whichletters of the English
`alphabet are represented by a sequence of dots and dashes (code words). In this
`code, more frequently occurring letters are represented by short code words, while
`letters occurring less frequently are represented by longer code words.
`The Morse code was the precursor to the variable-length source coding meth-
`ods that are described in Chapter 4.
`It
`is remarkable that
`the earliest form of
`electrical communication that was developed by Morse, namely,
`telegraphy, was
`a binary digital communication System in whichtheletters of the English alpha-
`
`TABLE 1-1 MORSE CODE
`ee
`eeeee
`1 Nig ==
`BY —-
`Oy
`-=— =
`Ca ==.
`Pe 422: St
`D —..
`Oh re be
`Bi:
`Re
`Die ae EN
`Be
`ene.
`Se
`ides:
`3
`— ea
`Ge.
`qe
`ee
`Ay
`ip 29
`[SP
`eae
`Dy oo
`Bait cas
`ae
`ee
`VE
`cians Te
`a Th ees
`K se Xess
`Re eres
`ae
`Veet Ts Quien
`ia Deena
`OY ee
`eeeeSe=eeeay
`(a) Letters
`(b) Numbers
`
`Halt— Wait sign (AS)
`Comma(,)
`Bean Doubledash (b
`Interrogation (2)
`..___..
`sn
`(break)
`Errorsign
`Quotation Mark @ aS
`Fraction bar (/)
`Colon (:)
`—
`—--.
`End of message (AR)
`Semicolon(;)
`=
`_—-—.
`End of transmission (SK)
`Parenthesis ( )
`
`(c) Punctuation and Special Characters
`
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`
`Sec. 1.1
`
`Historical Review
`
`3
`
`bet were efficiently encoded into corresponding variable-length code words having
`binary elements.
`in 1875, Emile Baudot developed a code for teleg-
`Nearly forty years later,
`raphy in which each letter was encoded into fixed-length binary code words of
`length 5. In the Baudot code,
`the binary code elements were of equal length and
`designated as mark and space.
`An important milestone in telegraphy was the installation of the first transat-
`lantic cable in 1858 that linked the United States and Europe. This cable failed
`after about four weeks of operation. A second cable waslaid a few years later and
`becameoperational in July 1866.
`Telephony came into being with the invention of the telephone in the 1870’s.
`Alexander Graham Bell patented his invention of the telephone in 1876 and in
`1877 established the Bell Telephone Company. Early versions of telephone commu-
`nication systems were relatively simple and provided service over several hundred
`miles. Significant advances in the quality and range of service during thefirst two
`decades of this century resulted from the invention of the carbon microphone and
`the induction coil.
`The invention of the triode amplifier by Lee DeForest in 1906 madeit pos-
`sible to introduce signal amplification in telephone communication systems and
`thus to allow for telephone signal transmission over great distances. For example,
`transcontinental telephone transmission became operational in 1915.
`Two world wars and the Great Depression during the 1930’s must have been
`a deterrent to the establishment of transatlantic telephone service. It was not until
`1953, when the first transatlantic cable was laid,
`that telephone service became
`available between the United States and Europe.
`Automatic switching was another important advance in the development of
`telephony. The first automatic switch, developed by Strowger in 1897, was an
`electromechanical step-by-step switch. This type of switch was used for several
`decades. With the invention of the transistor, electronic (digital) switching became
`economically feasible. After several years of development at the Bell Telephone
`Laboratories, a digital switch was placed in service in Illinois in June 1960.
`During the past thirty years, there have been numeroussignificant advancesin
`telephone communications. Fiber optic cables are rapidly replacing copper wire in
`the telephone plant, and electronic switches have replaced the old electromechanical
`systems.
`
`The development of wireless communications
`Wireless communications.
`stems from the works of Oersted, Faraday, Gauss, Maxwell, and Hertz during the
`nineteenth century. In 1820, Oersted demonstrated that an electric current produces
`a magnetic field. On August 29, 1831, Michael Faraday showed that an induced
`current is produced by moving a magnet in the vicinity of a conductor. Thus, he
`demonstrated that a changing magnetic field produces an electric field. With this
`early work as background, James C. Maxwell in 1864 predicted the existence of
`
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`
`4
`
`Introduction
`
`Chap. 1
`
`electromagnetic radiation and formulated the basic theory that has been in use for
`Over a century. Maxwell’s theory was verified experimentally by Hertz in 1887.
`In 1894, a sensitive device that could detect radio signals, called the coherer,
`was used byits inventor Oliver Lodge to demonstrate wireless communication over
`a distance of 150 yards at Oxford, England. Guglielmo Marconiis credited with
`the development of wireless telegraphy. Marconi demonstrated the transmission of
`radio signals at a distance of approximately 2 kilometers in 1895. Two yearslater, in
`1897, he patented a radio telegraph system and established the Wireless Telegraph
`and Signal Company. On December12, 1901, Marconireceived a radio signal at
`Signal Hill
`in Newfoundland, which was transmitted from Cornwall, England—a
`distance of about 1700 miles.
`The invention of the vacuum tube was especially instrumental
`in the devel-
`opment of radio communication systems. The vacuum diode was invented by John
`Fleming in 1904 and the vacuum triode amplifier was invented by Lee DeForest
`in 1906, as previously indicated. The invention of the triode made radio broad-
`Cast possible in the early part of the twentieth century. AM (amplitude modulation)
`broadcast was initiated in 1920 when radio station KDKA,Pittsburgh, went on the
`air. From that date, AM radio broadcasting grew very rapidly across the country and
`around the world. The superheterodyne AM radio receiver, as we knowit today, was
`invented by Edwin Armstrong during World War I. Another significant development
`in radio communications was the invention of FM (frequency modulation), also by
`Armstrong. In 1933, Armstrong built and demonstrated the first FM communication
`system. However, the use of FM was slow to develop compared with AM broadcast.
`It was not until the end of World War II that FM broadcast gained in popularity and
`developed commercially.
`
`Thepastfifty years. The growth in communicatio
`NS services over the past
`fifty years has been phenomenal. The invention of thetr.
`ansistor in 1947 by Walter
`Brattain, John Bardeen, and William Shockley;
`the integrated circuit in 1958 by
`Jack Kilby and Robert Noyce; and the laser by
`Townes and Schawlow in 1958,
`have made possible the development of small-si
`ze,
`low-power,
`low-weight, and
`high-speed electronic circuits which are used in th
`
`Currently, most of the wireline communication s
`5
`d
`:
`fiber optic cables which provide extremely high bandwidth and wae oNble the
`
`ystemsare being
`
`replaced b
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`transmission of a wide variety of information sources, including voice, data, and
`video. Cellular radio has been developed to provide telephone service to people in
`automobiles. High-speed communication networks link computers and a variety of
`peripheral devicesliterally around the world.
`Today we are witnessing a significant growth in the introduction and use
`of personal communications services,
`including voice, data, and video transmis-
`sion. Satellite and fiber optic networks provide high-speed communication services
`around the world. Indeed, this is the dawn of the modern telecommunicationsera.
`There are several historical
`treatments in the development of radio and
`telecommunications covering the past century. We cite books by McMahon,
`The Making of a Profession—A Century of Electrical Engineering in America
`(IEEE Press, 1984); Ryder and Fink, Engineers and Electronics (IEEE Press,
`1984); and S. Millman, Ed., A History of Engineering and Science in the Bell
`System—Communications Sciences (1925-1980) (AT & T Bell Laboratories, 1984).
`
`1.2 ELEMENTS OF AN ELECTRICAL COMMUNICATION SYSTEM
`
`Electrical communication systems are designed to send messages or information
`from a source that generates the messages to one or more destinations. In general,
`a communication system can be represented by the functional block diagram shown
`in Figure 1.1.
`The information generated by the source may be of the form of voice (speech
`source), a picture (image source), or plain text in some particular language, such
`as English, Japanese, German, French, etc. An essential feature of any source that
`generates information is that its output is described in probabilistic terms; thatis,
`the output of a source is not deterministic. Otherwise, there would be no need to
`transmit the message.
`
`source and
`input transducer
`
`Transmitter
`
`Channel
`
`
` Information
`
`
`
`Output
`signal
`
`ee
`transducer
`
`
`
`Receiver
`
`FIGURE 1.1. Functional block diagram of a communication system.
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`Introduction
`
`Chap.
`
`1
`
`the output of a source into an
`A transducer is usually required to convert
`electrical signal that is suitable for transmission. For example, a microphone serves
`as the transducer that converts an acoustic speech signal into an electrical signal,
`and a video camera converts an imageinto an electrical signal. At the destination, a
`Similar transduceris required to convert the electrical signals that are received into
`a form thatis suitable for the user; for example, acoustic signals, images,etc.
`The heart of the communication system consists of three basic parts, namely,
`the transmitter,
`the channel, and the receiver. The functions performed by these
`three elements are described below.
`
`The transmitter. The transmitter converts the electrical signal into a form
`that
`is suitable for transmission through the physical channel or transmission
`medium. For example,
`in radio and TV broadcast,
`the Federal Communications
`Commission (FCC) specifies the frequency range for each transmitting station.
`Hence, the transmitter must translate the information signal to be transmitted into
`the appropriate frequency range that matches the frequency allocation assigned to
`the transmitter. Thus, signals transmitted by multiple radio stations do not interfere
`with one another. Similar functions are performedin telephone communication sys-
`tems, where the electrical speech signals from many users are transmitted over the
`In general, the transmitter performs the matching ofthe message signal to the
`channel by a process called modulation. Usually, modulation involves the use of the
`information Signal
`to Systematically vary the amplitude, frequency, or phase of a
`sinusoidal Carrier. For example, in AM radio broadcast, the information signal that is
`
`same wire.
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`ulated signal, and in the case of wireless transmission, radiation of the signal by
`means of a transmitting antenna.
`
`The communications channel is the physical medium that is
`The channel.
`used to send the signal from the transmitter to the receiver. In wireless transmission,
`the channel is usually the atmosphere (free space). On the other hand, telephone
`channels usually employ a variety of physical media, including wirelines, optical
`fiber cables, and wireless (microwave radio). Whatever the physical medium for
`signal transmission, the essential feature is that the transmitted signal is corrupted
`in a random mannerbya variety of possible mechanisms. The most common form
`of signal degradation comes in the form of additive noise, which is generated at
`the front end of the receiver, where signal amplification is performed. This noise is
`often called thermal noise. In wireless transmission, additional additive disturbances
`are man-made noise and atmospheric noise picked up by a receiving antenna. Au-
`tomobile ignition noise is an example of man-made noise, and electrical lightning
`discharges from thunderstorms is an example of atmospheric noise. Interference
`from other users of the channel is another form of additive noise that often arises
`in both wireless and wireline communication systems.
`In some radio communication channels, such as the ionospheric channel that
`is used for long-range, short-wave radio transmission, another form of signal
`degradation is multipath propagation. Such signal distortion is characterized as a
`nonadditive signal disturbance which manifests itself as time variations in the signal
`amplitude, usually called fading. This phenomenonis described in more detail in
`Section 1.3.
`Both additive and nonadditive signal distortions are usually characterized as
`random phenomena and described in statistical
`terms. The effect of these signal
`distortions must be taken into account in the design of the communication system.
`In the design of a communication system,
`the system designer works with
`mathematical models thatstatistically characterize the signal distortion encountered
`on physical channels. Often, the statistical description that is used in a mathemati-
`cal model is a result of actual empirical measurements obtained from experiments
`involving signal transmission over such channels. In such case, there is a physi-
`cal justification for the mathematical model used in the design of communication
`systems. On the other hand, in some communication system designs,thestatistical
`characteristics of the channel may vary significantly with time. In such cases, the
`system designer may design a communication system that is robust to the variety
`of signal distortions. This can be accomplished by having the system adapt some of
`its parameters to the channel distortion encountered.
`
`The receiver. The function of the receiver is to recover the message signal
`contained in the received signal. If the message signal
`is transmitted by carrier
`modulation, the receiver performs carrier demodulation to extract the message from
`the sinusoidal carrier. Since the signal demodulation is performed in the presence
`
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`the demodulated message
`of additive noise and possibly other signal distortion,
`signal is generally degraded to some extent by the presence of these distortions in
`the received signal. As weshall see, the fidelity of the received message signalis
`a function of the type of modulation, the Strength of the additive noise,
`the type
`and strength of any other additive interference, and the type of any nonadditive
`interference.
`Besides performing the primary function of signal demodulation, the receiver
`also performs a numberofperipheral functions, including signalfiltering and noise
`suppression.
`
`1.2.1 Digital Communication System
`
`Up to this point, we have described anelectrical communication system in rather
`broad terms based onthe implicit assumption that the message signal is a continuous
`time-varying waveform. We refer to such continuous-time signal waveforms as
`analog signals and to the corresponding information sources that produce such
`Signals as analog sources. Analog signals can be transmitted directly via carrier
`modulation over the communication channel and demodulated accordingly at the
`receiver. We call such a communication system an analog communication system.
`Alternatively, an analog source output may be converted into a digital form
`and the message can be transmitted via digital modulation and demodulated as a
`digital signal at the receiver. There are some potential advantages to transmitting
`an analog signal by means of digital modulation. The most important reason is that
`signal fidelity is better controlled through digital
`transmission than analog trans-
`mission. In particular, digital transmission allows us to regenerate the digital signal
`in long-distance transmission,
`thus eliminating effects of noise at each regenera-
`
`cessing, redundancy may be removed prior to modulation
`bandwidth. Yet a third reason may bethat digital communi
`cheaper to implement.
`In someapplications, the information to be transmitted is inherently digital,
`e.g., in the form of English text, computer data, etc. In such cases, the information
`source that generates the data is called a discrete (digital) source.
`In a digital communication System, the functional operations performed at the
`transmitter and receiver must be expanded to include message signal discretization
`the transmitter and message signal synthesis or interpolation at
`the receiver.
`at
`Additional functions include redundancy removal, and channel coding and decoding.
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`Sec. 1.2
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`
`
`
`Information
`
`
`
`
`Source
`Channel
`source and
`
`
`
`
`Digital
`encoder
`encoder
`modulator
`
`
`
`
`
`
`input transducer
`
`Channel
`
`
`decoder Digital
`Channel
`decoder
`demodulator
`
`
`Output
`transducer
`
`Source
`
`Output
`signal
`
`FIGURE1.2. Basic elementesof a digital communication system.
`
`a digital communication system, the messages produced by the source are usually
`converted into a sequence of binary digits. Ideally, we would like to represent
`the source output (message) by as few binary digits as possible. In other words,
`we seek an efficient representation of the source output that results in little or no
`redundancy. The processofefficiently converting the output of either an analog or
`a digital source into a sequence ofbinary digits is called source encoding or data
`compression. We shall describe source encoding methods in Chapter 4.
`The sequence of binary digits from the source encoder, which wecall the
`information sequence, is passed to the channel encoder. The purpose of the channel
`encoder is to introduce in a controlled manner some redundancy in the binary
`information sequence which can be used at the receiver to overcome the effects
`of noise and interference encountered in the transmission of the signal
`through
`the channel. Thus,
`the added redundancy serves to increase the reliability of the
`received data and improvesthe fidelity of the received signal. In effect, redundancy
`in the information sequence aids the receiver in decoding t