COMMUNICATION
`SYSTEMS
`ENGINEERING
`
`Masoud Salehi
`
`John G. Proakis
`
`3:.
`
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`

`

`
`
`
`Systems
`Engineering
`
`Communication
`
`John G. Proakis
`
`Masoud Salehi
`
`Northeastern University
`
`5
`
`PRENTICE HALL, Englewood Cliffs, New Jersey 07632
`
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`

`

`Library of Congress Cataloging-in-hiblication Data
`
`Proakis. John G.
`Communication systems engineering I John G. Proalds. Masoud
`Salehi.
`cm
`p.
`Includes bibliographical references and index.
`ISBN 0-13-l58932—6
`l. Telecommunication
`TKSlOlJ’IS 1994
`621382420
`
`l. Salehi. Masoud.
`
`ll. 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. No pan of this book may be
`reproduced. in any form or by any means.
`without permission in writing from the publisher.
`
`Printed in the United States of America
`
`1098765432
`
`ISBN D-lB-LSE‘lBB-b
`
`Prentice-Hall lntemationa] (UK) Limited, london
`Prentice-Hall of Australia Pry. 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 Janeim
`
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`

`

`l C
`
`Contents
`
`Preface
`
`1
`
`Introduction
`
`1.1
`
`1.2
`
`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, 11
`Communication Channels and Their Characteristics
`Mathematical Models for Communication Channels
`
`13
`21
`
`Organization of the Book
`
`23
`
`Further Reading
`
`25
`
`1.3
`
`1.4
`
`1.5
`
`1.6
`
`XV
`
`vii
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`

`viii
`
`2 Signals and Linear Systems
`
`2.1
`
`Basic Concepts
`
`27
`
`Contents
`
`26
`
`2.1.] 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 LT] Systems in the Time Domain, 45
`
`2.2
`
`Fourier Series
`
`47
`
`Signal Space Concepts, 48
`2.2.1
`2.2.2 Orthogonal Expansion of Signals, 53
`2.2.3 Fourier Series and Its Properties, 55
`2.2.4 Response of LTl Systems to Periodic Signals, 65
`2.2.5 Parseval's Relation, 68
`
`2.3
`
`Fourier Transforms
`
`70
`
`From Fourier Series to Fourier Transforms, 70
`2.3.]
`2.3.2 Basic Properties of the Fourier Transfomt, 78
`2.3.3 Fourier Transform for Periodic Signals, 91
`2.3.4 Transmission over LTl Systems, 94
`
`Power and Energy
`
`97
`
`2.4.1 Energy-Type Signals, 98
`2.4.2
`Power-Type Signals, 101
`
`Sampling of Signals
`and Signal Reconstruction from Samples
`
`104
`
`Ideal Sampling, 104
`2.5.1
`2.5.2 Practical Sampling, 110
`
`Bandpass Signals
`
`112
`
`2.6.] Properties of the Hilbert Transform, 122
`
`Further Reading
`
`125
`
`Problems
`
`125
`
`2.4
`
`2.5
`
`2.6
`
`2.7
`
`3 Random Processes
`
`143
`
`3.1
`
`3.2
`
`3.3
`
`Probability and Random Variables
`
`144
`
`Random Processes: Basic Concepts
`
`160
`
`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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`Contents
`
`ix
`
`3.4
`
`3.5
`
`3.6
`
`3.7
`
`3.3.1 Power Spectrum of Stochastic Processes, 179
`3.3.2 Transmission over LT] Systems, I85
`
`Gaussian and White Processes
`
`188
`
`3.4.1 Gaussian Processes, 188
`3.4.2 White Processes, I90
`
`Bandlimited Processes and Sampling
`
`193
`
`Bandpass Processes
`
`196
`
`Further Reading
`
`204
`
`Problems
`
`204
`
`4 Information Sources and Source Coding
`
`221
`
`4.1
`
`Modeling of Information sources
`
`222
`
`4.2
`
`4.3
`
`4.4
`
`4.1.1 Measure of Information, 223
`4.1.2
`Joint and Conditional Entropy, 225
`
`Source-Coding Theorem 228
`
`Source-Coding Algorithms
`
`230
`
`The Hufi‘rnan Source-Coding Algorithm, 230
`4.3.1
`4.3.2 The Lempel—Ziv Source Coding Algorithm, 235
`
`Rate-Distortion Theory
`
`237
`
`4.4.1 Mutual Information, 238
`4.4.2 Difierential 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
`
`4.7
`
`4.8
`
`4.6.1
`
`Pulse—Code Modulation, 259
`
`4.6.2 Differential Pulse-Code Modulation, 264
`4.6.3 Delta Modulation, 267
`
`Analysis-Synthesis Techniques
`
`270
`
`Digital Audio Transmission and Digital Audio Recording
`
`274
`
`4.8.] Digital Audio in Telephone Transmission Systems, 274
`4.8.2 Digital Audio Recording, 276
`
`4.9
`
`Further Reading
`
`282
`
`Problems
`
`282
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`

`x
`
`5 Analog Signal Transmission and Reception
`
`Contents
`
`296
`
`5.1
`
`5.2
`
`Introduction to Modulation
`
`297
`
`Amplitude Modulation
`
`298
`
`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 VestigiaI-Sideband AM, 317
`5.2.5 Implementation of AM Modulators and Demodulators, 320
`5.2.6 Signal Multiplexing, 326
`
`5.3
`
`Angle Modulation
`
`328
`
`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
`
`5.5
`
`5.6
`
`6 Effect of Noise on Analog Communication Systems
`
`385
`
`6.1
`
`Effect of Noise on Linear Modulation Systems
`
`386
`
`6.1.1 Eflect of Noise on a Baseband System, 386
`6.1.2
`Efl‘ect of Noise on DSB-SC AM, 386
`6.1.3 Efiect of Noise on SSB AM, 388
`6.1.4
`Efi’ect of Noise on Conventional AM, 389
`
`6.2
`
`Carrier Phase Estimation with a Phase-Locked Loop
`
`394
`
`6.2.1 Efiect of Additive Noise on Phase Estimation, 398
`
`6.3
`
`Effect of Noise on Angle Modulation
`
`404
`
`6.4
`
`6.5
`
`6.3.1 Threshold Efect 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.] Characterization of Thennal Noise Sources, 423
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`Contents
`
`xi
`
`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
`
`7.1
`
`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
`
`7.2
`
`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
`
`7.3
`
`Probability of Error for Signals
`in Additive White Gaussian Noise
`
`488
`
`Probability of Error for Binary Modulation, 488
`7.3.]
`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
`
`7.4
`
`Regenerative Repeaters and Link Budget Analysis
`
`506
`
`7.4.1 Regenerative Repeaters, 507
`7.4.2 Link Budget Analysis for Radio Channels, 509
`
`7.5
`
`Further Reading
`
`512
`
`Problems
`
`513
`
`8 Digital PAM Transmission
`Through Bandlimited AWGN Channels
`
`530
`
`8.1
`
`Digital Transmission
`Through Bandlimited Baseband Channels
`
`531
`
`8.1.1 Digital PAM Transmission
`Through Bandlimited Baseband Channels, 535
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`xii
`
`Contents
`
`8.1.2 The Power Spectmm of a Digital PAM Signal, 537
`8.1.3 The Power Spectnim of Digital Signals with Memory, 542
`
`8.2
`
`Signal Design for Bandlimited Channels
`
`547
`
`8.2.1 Design of Bandlimited Signals
`for Zero [SI—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 IS], 558
`
`8.3
`
`Probability of Error in Detection of Digital PAM 564
`
`8.3.1
`
`Probability of Error for Detection
`ofDigital PAM with Zero 151, 565
`8.3.2 Probability of Error for Detection of Partial Response Signals, 566
`
`8.4
`
`570
`System Design in the Presence of Channel Distortion
`8.4.1 Design of Optimum Transmitting and Receiving Filters, 572
`8.4.2 Channel Equalization, 577
`
`8.5
`
`Symbol Synchronization
`
`595
`
`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
`
`9 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
`
`9.2
`
`Carrier—Phase Modulation
`
`628
`
`9.2.1 Phase Demodulation and Detection, 633
`
`9.2.2 Probability of Error for Phase Modulation in
`an AWGN Channel, 636
`9.2.3 Carrier Phase Estimation, 640
`
`9.2.4 Difi’erential—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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`Contents
`
`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, 66]
`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
`
`9.5.1 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
`
`9.6
`
`Digital Transmission on Fading Multipath Channels
`
`695
`
`9.6.] 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
`
`9.7
`
`Further Reading
`
`713
`
`Problems
`
`714
`
`10 Channel Capacity and Coding
`
`726
`
`10.1
`
`10.2
`
`Modeling of Communication Channels
`
`726
`
`Channel Capacity
`
`729
`
`10.2.1 Gaussian Channel Capacity, 733
`
`10.3
`
`Bounds on Communication
`
`736
`
`[0.3.] Transmission of Analog Sources by PCM, 740
`
`10.4
`
`742
`Coding for Reliable Communication
`10.4.] A Tight Bound on Error Probability of Orthogonal Signals, 743
`I 0.4.2 The Promise of Coding, 746
`
`10.5
`
`Linear Block Codes
`
`753
`
`10.5.1 Decoding and Performance of Linear Block Codes, 757
`10.5.2 Burst-Ermr-Correcting-Codes, 767
`
`10.6
`
`Cyclic Codes
`
`769
`
`10.6.1
`
`The Structure of Cyclic Codes, 769
`
`10.7
`
`Convolutional Codes
`
`777
`
`10.7.1 Basic Properties of Convolutional Codes, 779
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`xiv
`
`Contents
`
`10.7.2 Optimum Decoding
`of Convolutional Codes—The Viterbi Algorithm, 784
`10.7.3 Other Decoding Algorithms for Convolutional Codes. 789
`10.7.4 Bounds on Error Probability of Convolutional Codes, 789
`
`10.8
`
`Coding for Bandwidth Constrained Channels
`
`792
`
`10.8.1 Combined Coding and Modulation, 794
`10.8.2 Trellis Coded Modulation, 796
`
`10.9
`
`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
`
`10.10
`
`Further Reading
`
`809
`
`Problems
`
`809
`
`1 1 Spread-Spectrum Communication Systems
`
`822
`
`11.]
`
`11.2
`
`11.3
`
`11.4
`11.5
`11.6
`
`823
`
`Model of
`a Spread—Spectrum Digital Communication Systems
`Direct-Sequence Spread Spectrum Systems
`825
`11.2.1 Probability ofError, 829
`11.2.2 Some Applications of DS Spread-Spectmm Signals, 837
`11.2.3 Generation of PN Sequences, 844
`Frequency-Hopped Spread Spectrum 848
`11.3.1
`Slow Frequency-Hopping Systems, 85I
`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
`
`857
`
`Problems
`
`865
`
`Appendix A: The Probability of Error
`for Multichannel Reception of Binary Signals
`
`References
`Index
`
`869
`
`873
`881
`
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`

`Ionosphere \
`’
`
`\
`
`4/ ////E/?h
`
`.
`
`\\
`
`
`
`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 occur all around the world. Electronic mail and facsimile
`transmission have made it possible to rapidly communicate written messages across
`great distances.
`Can you imagine a world without telephones, radio, and TV? Yet, when you
`think about it, most of these modem-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
`
`Telegraphy and telephony. One of the earliest inventions of major signif-
`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 which letters 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.
`
`\ A
`
`N _.
`-—
`o ___
`B _...
`p
`.__. \
`c _._.
`Q __._
`1 _____
`D _..
`R
`._.
`2 _____
`E
`.
`S
`3
`__
`F
`--.—
`T _
`4
`...._
`G __.
`U
`.._
`5
`.....
`H
`V .-._
`5 _....
`--
`I
`-——— W .——
`7 __
`J
`K —-—
`X ~--—
`3 _____
`L ~
`Y —-——
`9 _____
`M ~——
`Z __..
`0 _____
`\ \
`(a) Letters
`(b) Numbers
`
`Comma (,)
`,,____
`Interrogation ('2)
`Quotation Mark (") ------
`Colon (:)
`—~
`Semicolon (;)
`_
`Parenthesis ( )
`
`'
`— Wait
`Slgn (AS)
`““““ Doubl
`Error :iESSh (break)
`Fraction bar (I)
`End of message (AR)
`End f tr
`.
`.
`0
`ansmiss10n (SK)
`
`.—._.
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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 was laid a few years later and
`became operational 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 the first two
`decades of this century resulted from the invention of the carbon microphone and
`the induction coil.
`
`The invention of the triode amp1ifier by Lee DeForest in 1906 made it 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 numerous significant advances in
`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 by its inventor Oliver Lodge to demonstrate wireless communication over
`a distance of 150 yards at Oxford, England. Guglielmo Marconi
`is credited with
`the development of wireless telegraphy. Marconi demonstrated the transmission of
`radio signals at a distance of approximately 2 kilometers in 1895. Two years later, in
`1897, he patented a radio telegraph system and established the Wireless Telegraph
`and Signal Company. On December 12, 1901, Marconi received a radio signal at
`Signal Hill
`in Newfoundland, which was transmitted from Cornwall, England—a
`distance of about 1700 miles.
`in the devel-
`The invention of the vacuum tube was especially instrumental
`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 pan 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
`
`,
`
`ansistor in 1947 by Walter
`the integrated circuit in 1958 by
`.Townes and Schawlow in 1958,
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`Elements of an Electrical Communication System
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`5
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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 devices literally 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 telecommunications era.
`
`treatments in the development of radio and
`There are several historical
`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; that is,
`the output of a source is not deterministic. Otherwise, there would be no need to
`transmit the message.
`
`input transducer
`
`Information
`source and
`
`
`
`
`
`
`
`Output
`signal
`
`Output
`transducer
`
`
`
`Receiver
`
`
`
`FIGURE 1.1. Functional block diagram of a communication system.
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`Introduction
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`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 image into an electrical signal. At the destination, a
`similar transducer is required to convert the electrical signals that are received into
`a form that is 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
`is suitable for transmission through the physical channel or transmission
`that
`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
`wrth one another. Similar functions are performed in telephone communication sys-
`tems, where the electrical speech signals from many users are transmitted over the
`same wrre.
`
`In general, the transmitter performs the matching of the 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
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`Elements of an Electrical Communication System
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`7
`
`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 manner by a 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 phenomenon is 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 that statistically 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, the statistical
`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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`8
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`Introduction
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`Chap.
`
`1
`
`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 we shall see, the fidelity of the received message signal is
`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 number of peripheral functions, including signal filtering and noise
`suppression.
`
`1.2.1 Digital Communication System
`
`Up to this point, we have described an electrical communication system in rather
`broad terms based on the 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
`
`, or a digital signal, such as the output of a teletype
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`Sec. 1.2
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`Elements of an Electrical Communication System
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`9
`
`
`
`
`Information
`
`
`Source
`Channel
`source and
`Digital
`
`
`
`
`encoder
`encoder
`modulator
`
`
`
`
`
`input transducer
`
`
`
`
`
`
`
`Channel
`
`Output
`signal
`
`
`Output
`
`Digital
`transducer
`
`demodulator
`
`
`FIGURE 1.2. Basic elementes of 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 process of efficiently converting the output of either an analog or
`a digital source into a sequence of binary 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 we call 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 improves the fidelity of the received signal. In effect, redundancy
`in the information sequence aids the receiver in decoding the desired information
`sequence. For example, a (trivial) form of encoding of the binary information
`sequence is simply to repeat each binary digit m times, where m is some positive
`integer. More sophisticated (nontrivial) encoding involves taking k information bits
`at a time and mapping each k-bit sequence into a unique n-bit sequence, called
`a code word. The amount of redundancy introduced by encoding the data in this
`manner is measured by the ratio It / k. The reciprocal of this ratio, namely, k/n. is
`called the rate of the code or, simply, the code rate.
`The binary sequence at the output of the channel encoder is passed to the
`digital modulator, which serves as the interface to the communications channel.
`Since nearly all of the communication channels encountered in practice are capable
`of transmitting electrical signals (waveforms),
`the primary purpose of the digital
`modulator is to map the binary information sequence into signal waveforms. To
`elaborate on this point,
`let us suppose that
`the coded information sequence is
`to be transmitted one bit at a time at some uniform rate R bits/s. The digital
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`Introduction
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`Chap.
`
`1
`
`modulator may simply map the binary digit 0 into a waveform so(t) and the binary
`digit 1
`into a waveform 510). In this manner, each bit from the channel encoder is
`transmitted separately. We call this binary modulation. Alternatively, the modulator
`may transmit b coded information bits at a time by using M = 2" distinct waveforms
`s,-(t), i = 0, l, .
`. ., M — 1, one waveform for each of the 2” possible b-bit sequences.
`We call this M -ary modulation (M > 2). Note that a new b-bit sequence enters the
`modulator every b/R seconds. Hence, when the channel bit rate R is fixed,
`the
`amount of time available to transmit one of the M waveforms corresponding to a
`b-bit sequence is b times the time period in a system that uses binary modulation.
`At
`the receiving end of a digital communications system,
`the digital de-
`modulator processes the channel-corrupted transmitted waveform and reduces each
`waveform to a single number that represents an estimate of the transmitted data
`symbol (binary or M -ary). For example, when binary modulation is used,
`the
`demodulator may proces