Apple Inc. v. Cellular Communications Equipment LLC
`APPL-1015 / Page 1 of 41
`
`

`
`
`
`Library of Congress Caraioging-in-Publication Dam
`
`SKLAR, BERNARD (date)
`Digital communications.
`
`Bibliography: 13.
`Includes index.
`I. Title.
`1. Digital communications.
`TK510J.7.SS5
`1988
`62l.3B'D413
`ISBN D-13-2ll939—0
`
`8?-1316
`
`
`
`Editorialiproduction supervision and
`interior design: Reynold Rieger
`Cover design: Wanda Lubelska Design
`Manufacturing buyers: Gordon Osbourne and Paula Benevento
`
`; © 1988 by P T R Prentice-Hall. Inc.
`_.=
`A Simon & Schuster Company
`—
`Englewood Cliffs, New Jersey 07632
`
`All rights reserved. No part 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
`
`10
`
`ISBN El-1.3-El1.“lEI‘l-El
`
`DES
`
`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
`
`
`
` APPL-1015 / Page 2 0f41
`
`APPL-1015 / Page 2 of 41
`
`

`
`
`
`Contentsk
`
`PREFACE
`
`SIGNALS ANDDSPECTRA
`
`'
`
`ll1 II
`
`1
`
`xxi
`
`1
`
`vii
`
`1.1
`
`1.2
`
`1.3
`
`1.5
`
`12
`13
`
`14
`15
`
`18
`20
`
`Digital Communication Signal Processing,
`1.1.1 Why Digital?,
`3
`1.1.2
`Typical Block Diagram and Transformations, 4
`1.1.3 Basic Digital Communication Nomenclature,
`9
`1.1.4 Digital versus Analog Performance Criteria,
`11
`Classification of Signals,
`11
`1.2.1 Deterministic and Random Signals,
`1.2.2
`Periodic and Nonperiodic Signals,
`1.2.3 Analog and Discrete Signals,
`12
`1.2.4
`Energy and Power Signals,
`1.2.5
`The Unit Impulse Function,
`Spectral Density,
`14
`1.3.1
`Energy Spectral Density,
`1.3.2
`Power Spectral Density,
`1.4 Autocorrelation,
`17
`17
`1.4.1 Autocorrelation ofan Energy Signal,
`1.4.2 Autocorrelation of a Periodic (Power) Signal,
`Random Signals,
`18
`1.5.1
`Random Variables,
`1.5.2 Random Processes,
`
`3
`
`11
`12
`
`17
`
`APPL-1015 / Page 3 0f41
`
`APPL-1015 / Page 3 of 41
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`

`
`23
`
`30
`
`22
`Time Averaging and Ergodicity,
`1.5.3
`Power Spectral Density ofa Random Process,
`1.5.4
`1.5.5 Noise in Communication Systems,
`27
`Signal Transmission through Linear Systems,
`1.6.]
`Impulse Response,
`31
`31
`I.6.2
`Frequency Transfer Function,
`32
`1.6.3 Distortionless Transmission,
`1.6.4
`Signals, Circuits, and Spectra,
`Bandwidth of Digital Data,
`41
`«
`1.7.1
`Baseband versus Bandpass,
`41
`1.7.2
`The Bandwidth Dilemma,
`Conclusion,
`46
`References,
`46
`Problems,
`47
`
`38
`
`43
`
`2 FORMATTING AND BASEBAND TRANSMISSION
`
`
`
`51
`
`1.6
`
`1.7
`
`1.8
`
`2.1
`2.2
`2.3
`
`2.4
`
`2.5
`
`2.7
`
`2.8
`
`2.9
`
`
`
`59
`
`69
`
`70
`
`74
`
`74
`
`77
`
`54
`Baseband Systems,
`Formatting Textual Data (Character Coding),
`Messages, Characters, and Symbols,
`55
`2.3.]
`Example of Messages, Characters, and
`Symbols,
`55
`Formatting Analog Information,
`2.4.1
`The Sampling Theorem,
`59
`2.4.2 Aliasing,
`66
`2.4 .3
`Signal Interface for a Digital System,
`Sources of Corruption,
`70
`2.5.1
`Sampling and Quantizing Effects,
`-
`2.5.2
`Channel Effects,
`7]
`2.5.3
`Signal-to-Noise Ratio for Quantized Pulses,
`Pulse Code Modulation,
`73
`Uniform and Nonuniform Quantization,
`2.7.1
`Statistics of Speech Amplitudes,
`2.7.2 Nonuniform Quantization,
`76
`2.7.3
`Companding Characteristics,
`Baseband Transmission,
`78
`2.8.1 Waveform Representation of Binary Digits,
`2.8.2
`PCM Waveform Types,
`78
`82
`2.8.3
`Spectral Attributes of PCM Waveforms,
`Detection of Binary Signals in Gaussian Noise,
`2.9.1 Maximum Likelihood Receiver Structure,
`2.9.2
`The Matched Filter,
`88
`2.9.3
`Correlation Realization of the Matched Filter,
`2.9.4 Application of the Matched Filter,
`91
`2.9.5
`Error Probability Performance of Binary
`Signaling,
`92
`
`55
`
`72
`
`78
`
`83
`
`85
`
`90
`
`Contents
`
`
`
`APPL-1015 / Page 4 0f41
`
`APPL-1015 / Page 4 of 41
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`

`
`2.11
`
`2.10 Multilevel Baseband Transmission,
`2.10.1 PCM Word Size,
`97
`98
`Intersymbol Interference,
`2.11.1 Pulse Shaping to Reduce IS1,
`2.11.2 Equalization,
`104
`2.12 Partial Response Signaling,
`2.12.1 Daobinary Signaling,
`2.12.2 Duobinary Decoding,
`2.12.3 Precoding,
`108
`2.12.4 Duobinary Equivalent Transfer Function,
`2.12.5 Comparison ofBinary with Duobinaiy
`Signaling,
`111
`2.12.6 Polybinary Signaling,
`2.13 Conclusion,
`112
`References,
`113
`Problems,
`113
`
`95
`
`100
`
`106
`106
`107
`
`112
`
`109
`
`3 BANDPASS MODULATION AND DEMODULATION
`
`117
`
`118
`3.1 Why Modu1ate?,
`119
`3.2
`Signals and Noise,
`3.2.1 Noise in Radio Communication Systems,
`3.2.2 A Geometric View of Signals and Noise,
`
`119
`I20
`
`3.3
`
`Digital Bandpass Modulation Techniques,
`
`127
`
`fl
`
`.
`1
`
`3.5
`
`132
`132
`
`133
`
`138
`
`145
`
`130
`Phase Shift Keying,
`3.3.1
`130
`Frequency Shift Keying,
`3.3.2
`131
`3.3.3 Amplitude Shift Keying,
`131
`3.3.4 Amplitude Phase Keying,
`3.3.5 Waveform Amplitude Coefficient,
`3.4 Detection of Signals in Gaussian Noise,
`3.4.1 Decision Regions,
`132
`3.4.2
`Correlation Receiver,
`Coherent Detection,
`138
`3.5.1
`Coherent Detection ofPSK,
`3.5.2
`Sampled Matched Filter,
`139
`3.5.3
`Coherent Detection of Multiple Phase Shift
`Keying,
`142
`Coherent Detection ofFSK,
`3.5.4
`3.6 Noncohercnt Detection,
`146
`146
`3.6.1 Detection ofD|]ferential PSK,
`148
`3.6.2 Binary Differential PSK Example,
`150
`3.6.3 Noncoherent Detection ofFSK,
`3.6.4 Minimum Required Tone Spacing for Noncoherent
`Orthogonal FSK Signaling,
`152
`
`Contents
`
`Contents
`
`ix
`
`APPL-1015 / Page 5 0f41
`
`APPL-1015 / Page 5 of 41
`
`

`
`
`
`167
`
`182
`
`176
`
`137
`
`4 COMMUNICATIONS LINK ANALYSIS
`
`4.1 What the System Link Budget Tells the System
`Engineer,
`188
`189
`The Channel,
`189
`4.2.1
`The Concept ofFree Space,
`4.2.2
`Signal-to-Noise Ratio Degradation,
`4.2.3
`Sources of Signal Loss and Noise,
`Received Signal Power and Noise Power,
`4.3.1
`The Range Equation,
`195
`4.3.2
`Received Signal Power as a Function of
`Frequency,
`199
`Path Loss Is Frequency Dependent,
`Thermal Noise Power,
`202
`
`4.2
`
`4.3
`
`4.3.3
`4.3.4
`
`190
`190
`195
`
`200
`
`
`
`APPL-1015 / Page 6 0f41
`
`Error Performance for Binary Systems,
`3.7.1 .
`Probability of Bit Error for Coherently Detected
`BPSK,
`I55
`
`3.7
`
`3.7.2
`
`3.7.3
`
`3.7.4
`
`155
`
`Probability ofBit Error for Coherently Detected
`Differentially Encoded PSK,
`I60
`Probability of Bit Error for Coherently Detected
`FSK.
`16]
`
`Probability of Bit Error for Noncoherently Detected
`1
`FSK,
`I62
`
`3.8
`
`3.9
`
`3.7.5
`3.7.6
`
`3.9.4
`
`.
`!
`I
`
`I64
`Probability ofBit Error for DPSK,
`Comparison ofBit Error Performance for Various
`Modulation Types,
`I66
`167
`M—ary Signaling and Performance,
`3.8.1
`Ideal Probability of Bit Error Performance,
`3.8.2 M-ary Signaling,
`167
`170
`3.8.3
`Vectorial View of MPSK Signaling,
`3.8.4 BPSK and QPSK Have the Same Bit Error
`Probability,
`171
`172
`Vectorial View ofMFSK Signaling,
`3.8.5
`Symbol Error Performance for M-ary Systems (M > 2),
`3.9.]
`Probability of Symbol Error for MPSK,
`I 76
`3.9.2
`Probability of Symbol Error for MFSK,
`I 77
`3.9.3 Bit Error Probability versus Symbol Error Probability
`for Orthogonal Signals,
`180
`Bit Error Probability versus Symbol Error Probability
`for Multiple Phase Signaling,
`I81
`Effects oflntersymbol Interference,
`3.9.5
`3.10 Conclusion,
`182
`References,
`182
`Problems,
`183
`
`APPL-1015 / Page 6 of 41
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`

`
`l
`
`l I
`
`4.4
`
`204
`Link Budget Analysis,
`205
`4.4 .1
`Two Eb/No Values of Interest,
`4.4.2
`Link Budgets Are Typically Calculated in
`Decibels,
`206
`4.4.3 How Much Link Margin Is Enough?,
`
`207
`
`209
`Link Availability,
`4.4.4
`4.5 Noise Figure, Noise Temperature, and System
`Temperature,
`213
`213
`4.5.1 Noise Figure,
`4.5.2 Noise Temperature,
`4.5.3
`Line Loss,
`216
`4.5.4
`Composite Noise Figure and Composite Noise
`Temperature,
`218
`System Effective Temperature,
`4.5.5
`Sky Noise Temperature,
`224
`4.5.6
`Sample Link Analysis,
`228
`228
`4.6.1
`Link Budget Details,
`230
`4.6.2
`Receiver Figure-of-Merit,
`231
`4.6.3
`Received Isotropic Power:
`Satellite Repeaters,
`232
`232
`4.7.1 Nonregenerative Repeaters,
`4.7.2 Nonlinear Repeater Amplifiers,
`System Trade-Offs,
`238
`Conclusion,
`239
`References,
`239
`Problems,
`240
`
`215
`
`p
`
`‘
`
`,
`
`220
`
`236
`
`4.6
`
`4.7
`
`4.8
`4.9
`
`’
`
`3’
`
`1
`
`76
`
`5
`
`.
`
`187
`
`5 CHANNEL CODING: PART 1
`
`245
`
`249
`
`246
`5.1 Waveform Coding,
`5.1.1 Antipodal and Orthogonal Signals, 247
`5.1.2 M-ary Signaling,
`249
`5.1.3 Waveform Coding with Correlation Detection,
`5.1.4 Orthogonal Codes,
`251
`5.1.5 Biorthogonal Codes,
`255
`5.1.6
`Transorthogonal (Simplex) Codes,
`Types of Error Control,
`258
`258
`5 .2.1
`Terminal Connectivity,
`5.2.2 Automatic Repeat Request,
`Structured Sequences,
`260
`5.3.1
`Channel Models,
`261
`5.3.2
`Code Rate and Redundancy,
`5.3.3
`Parity—Check Codes,
`263
`5.3.4
`Coding Gain,
`266
`
`257
`
`259
`
`263
`
`5.2
`
`5.3
`
`Contents
`
`Contents
`
`xl
`
`APPL-1015 / Page 7 0f41
`
`APPL-1015 / Page 7 of 41
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`

`
`271
`
`273
`
`280
`281
`
`288
`
`269
`Linear Block Codes,
`269
`5.4.1
`Vector Spaces,
`270
`5.4.2
`Vector Subspaces,
`5.4.3 A (6, 3) Linear Block Code Example,
`5.4.4 Generator Matrix,
`272
`5.4.5
`Systematic Linear Block Codes,
`5.4.6
`Parity-Check Matrix,
`275
`5.4.7
`Syndrome Testing,
`276
`5.4.8
`Error Correction,
`277
`,
`Coding Strength,
`280
`5.5.1 Weight and Distance of Binary Vectors,
`5.5.2 Minimum Distance of a Linear Code,
`5.5.3
`Error Detection and Correction, 28]
`5.5.4
`Visualization of a 6-Tuple Space,
`285
`5.5.5
`Erasure Correction,
`287
`Cyclic Codes,
`288
`5.6.1 Algebraic Structure of Cyclic Codes,
`5.6.2
`Binary Cyclic Code Properties,
`290
`5.6.3
`Encoding in Systematic Form,
`290
`5.6.4
`Circuit for Dividing Polynomials,
`292
`5.6.5
`Systematic Encoding with an (n — k)-Stage Shift
`Register,
`294
`Error Detection with an (n - k)-Stage Shift
`Register,
`296
`Well-Known Block Codes,
`5.7.1 Hamming Codes,
`298
`5.7.2
`Extended Golay Code,
`5.7.3
`BCH Codes,
`301
`5.7.4
`Reed—Solomon Codes,
`Conclusion,
`308
`References,
`308
`Problems,
`309
`
`5.6.6
`
`298
`
`301
`
`304
`
`5.4
`
`5.5
`
`5.6
`
`5.7
`
`5.8
`
`
`
`6 CHANNEL CODING: PART 2
`
`314
`
`
`
`6.3
`
`315
`Convolutional Encoding,
`Convolutional Encoder Representation,
`6.2.1
`Connection Representation,
`318
`6.2.2
`State Representation and the State Diagram,
`6.2.3
`The Tree Diagram,
`324
`6.2.4
`The Trellis Diagram,
`326
`Formulation of the Convolutional Decoding Problem,
`6.3.] Maximum Likelihood Decoding,
`327
`6.3.2
`Channel Models: Hard versus Soft Decisions,
`6.3.3
`The Viterbi Convolutional Decoding Algorithm,
`
`317
`
`322
`
`_
`
`327
`
`329
`333
`
`
`
`APPL-1015 / Page 8 0f41
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`APPL-1015 / Page 8 of 41
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`

`
`6.3.4 An Example of Viterbi Convolutional
`Decoding,
`333
`Path Memory and Synchronization,
`6.3.5
`Properties of Convolutional Codes,
`338
`6.4.1 Distance Properties of Convolutional Codes,
`6.4.2
`Systematic and Nonsystematic Convolutional
`Codes,
`342
`Catastrophic Error Propagation in Convolutional
`Codes,
`342
`Performance Bounds for Convolutional Codes,
`6.4.4
`Coding Gain,
`345
`‘
`6.4.5
`6.4.6 Best Known Convolutional Codes,
`6.4.7
`Convoiutional Code Rate Trade-015”,
`6.5 Other Convolutional Decoding Algorithms,
`6.5.1
`Sequential Decoding,
`350
`6.5.2
`Comparisons and Limitations of Viterbi and
`Sequential Decoding,
`354
`Feedback Decoding,
`355
`6.5.3
`Interleaving and Concatenated Codes,
`6.6.1
`Block Interleaving,
`360
`6.6.2
`Convolutional Interleaving,
`6.6.3
`Concatenated Codes,
`365
`
`6.4.3
`
`6.4
`
`6.6
`
`338
`
`344
`
`337
`
`347
`348
`350
`
`357
`
`362
`
`6.7
`
`6.8
`
`Coding and Interleaving Applied to the Compact Disc Digital
`Audio System,
`366
`367
`6.7.1
`CIRC Encoding,
`369
`6.7.2
`CIRC Decoding,
`6.7.3
`Interpolation and Mating.
`Conclusion,
`374
`References,
`374
`Problems,
`376
`
`371
`
`MODULATION AND CODING TRADE-OFF S
`
`381
`
`i
`385
`
`382
`
`391
`
`7.1
`Goals of the Communications System Designer,
`7.2
`Error Probability Plane,
`383
`385
`7.3 Nyquist Minimum Bandwidth,
`7.4
`Sharmon—Hartley Capacity Theorem,
`7.4.I
`Shannon Limit,
`387
`7.4.2
`Entropy,
`389
`7.4.3
`Equivocation and Effective Transmission Rate,
`Bandwidth-Efficiency Plane,
`393
`7.5.1
`Bandwidth Efficiency ofMPSK and MFSK
`Modulation,
`395
`7.5.2 Analogies between Bandwidth-Efliciency and Error
`Probability Planes,
`396
`Power-Limited Systems,
`396
`
`7.5
`
`7.6
`
`314
`
`327
`
`Contents
`
`Contents
`
`
`
`APPL-1015 / Page 9 0f41
`
`APPL-1015 / Page 9 of 41
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`

`
`
`
`410
`
`7.7
`7.8
`7.9
`
`7.10
`
`7.11
`
`397
`Bandwidth-Lirnited Systems,
`397
`Modulation and Coding Trade-Offs,
`399
`Bandwidth—Efficient Modulations,
`7.9.1
`QPSK and Ofiset QPSK Signaling,
`7.9.2 Minimum Shift‘ Keying,
`403
`407
`7.9.3 Quadrature Amplitude Modulation,
`Modulation and Coding for Bandlimited Channels,
`7.10.1 Commercial Telephone Modems,
`411
`7.10.2 Signal Constellation Boundaries,
`412
`7.10.3 Higher-Dimensional Signal Conslellations,
`7.10.4 Higher-Density Lattice Structures,
`415
`7.10.5 Combined-Gain: N-Sphere Mapping and Dense
`Lattice,
`416
`7.10.6 Trellis—Coded Modulation,
`7.10.7 Trellis-Coding Example,
`Conclusion,
`424
`References,
`425
`Problems ,
`426
`
`399
`
`412
`
`417
`420
`
`
`
`8 SYNCHRONIZATION
`Maurice A. King, Ir.
`
`8.1
`
`8.2
`
`8.3'
`
`8.4
`
`Synchronization in the Context of Digital
`Communications,
`430
`430
`8.1.1 What It Means to Be Synchronized,
`8.1.2
`Costs versus Benefits of Synchronization
`Levels,
`432
`434
`Receiver Synchronization,
`8.2.1
`Coherent Systems: Phase-Locked Loops,
`8.2.2
`Symbol Synchronization,
`453
`8.2.3
`Frame Synchronization,
`460
`Network Synchronization,
`464
`8.3.1
`Open-Loop Transmitter Synchronization,
`8.3.2
`Closed-Loop Transmitter Synchronization,
`Conclusion,
`470
`References,
`471
`Problems,
`472
`
`9 MULTIPLEXING AND MULTIPLE ACCESS
`
`429
`
`475
`
`434
`
`465
`468
`
`9.1
`
`Allocation of the Communications Resource,
`9.1.1
`Frequency-Division MultiplexinglMultiple
`Access,
`478
`
`4'76:
`
`
`
`APPL-"1015 / Page 10 0f41
`
`APPL-1015 / Page 10 of 41
`
`

`
`9.1.2
`9.1.3
`9.1.4
`
`9.1.5
`9.1.6
`
`Time-Division Multiplexinglillultiple Access,
`Communications Resource Channelization,
`Performance Comparison of FDMA and
`TDMA,
`"488
`491
`Code-Division Multiple Access,
`Space-Division and Polarization-Division Multiple
`Access,
`493
`
`484
`487
`
`.
`l
`
`9.2 Multiple Access Communications System and
`Architecture,
`495
`‘
`, 496
`9.2.1 Multiple Access Information Flow,
`9.2.2 Demand-Assignment Multiple Access,
`497
`9.3 Access Algorithms,
`498
`9.3.1 ALOHA,
`498
`500
`9.3.2
`Slotted ALOHA,
`502
`9.3 .3
`Reservation-ALOHA,
`9.3.4
`Performance Comparison of S-ALOHA
`and R-ALOHA,
`503
`Polling Techniques,
`
`9.3.5
`
`505
`
`429
`
`4'75 '
`
`9.4 Multiple Access Techniques Employed with
`INTELSAT,
`507
`9.4.1
`Preassigned FDMlFMlFDMA or MCPC
`
`508
`Operation,
`9.4.2 MCPC Modes ofAccessing an INTELSAT
`Satellite,
`510
`511
`SPADE Operation,
`TDMA in INTELSAT,
`516
`Satellite-Switched TDMA in INTELSAT,
`
`9.4.3
`9.4.4
`9.4.5
`
`523
`
`9.5 Multiple Access Techniques for Local Area Networks,
`9.5.1
`Carrier-Sense Multiple Access Networks,
`526
`9.5.2
`Token-Ring Networks,
`528
`9.5.3
`Performance Comparison of CSMAICD
`and Token-Ring Networks,
`530
`Conclusion,
`531
`References,
`532
`Problems,
`533
`
`9.6
`
`526
`
`10 SPREAD-SPECTRUM TECHNIQUES
`
`535
`
`10.1
`
`537
`Spread-Spectmm Overview,
`10.1.1
`The Beneficial Attributes ofSpread-Spectrum
`Systems,
`538
`10.1.2 Model for Spread-Spectrum Interference
`Rejection,
`542
`10.1.3 A Catalog of Spreading Techniques,
`10.1.4 Historical Background,
`544
`
`543
`
`COMGMS
`
`Contents
`
`xv
`
`APPL-"1015 / Page 11 0f41
`
`APPL-1015 / Page 11 of 41
`
`

`
`
`
`549
`
`I iI I
`
`Q
`
`595
`
`Contents
`
`552
`
`559
`560
`
`546
`Pseudonoise Sequences,
`546
`10.2.1
`Randomness Properties,
`547
`10.2.2
`Shift Register Sequences,
`548
`10.2.3
`PN Autocorreiation Function,
`Direct-Sequence Spread-Spectrum Systems,
`10.3.1
`Example of Direct Sequencing,
`550
`10.3.2
`Processing Gain and Performance,
`Frequency Hopping Systems,
`555
`10.4.1
`Frequency Hopping Example,‘ ‘ 557
`10.4.2
`Robustness,
`558
`‘
`10.4.3
`Frequency Hopping with Diversity,
`10.4.4
`Fast Hopping versus Slow Hopping,
`10.4.5
`FFH/MFSK Demoduiator,
`562
`Synchronization,
`562
`10.5.1 Acquisition,
`563
`10.5.2
`Tracking,
`568
`571
`Spread-Spectrum Applications,
`10.6.1
`Code-Division Multiple Access,
`10.6.2 Multipath Channels,
`573
`10.6.3
`The Jamming Game,
`574
`Further Jamming Considerations,
`10.7.1
`Broadband Noise Jamming,
`10.7.2
`Partial-Band Noise Jamming,
`10.7.3 Multiple-Tone Jamming,
`583
`10.7.4
`Pulse Jamming,
`584
`10.7.5 Repeat-Back Jamming,
`10.7.6 BLADES System,
`588
`Conclusion,
`589
`References,
`589
`Problems,
`591
`
`571
`
`579
`579
`581
`
`586
`
`10.2
`
`10.3
`
`10.4
`
`10.5
`
`10.6
`
`10.7
`
`10.8
`
`
`
`11 SOURCE CODING
`
`Fredric I. Harris
`
`11.1
`
`11.2
`
`11.3
`
`596
`601
`
`596
`Sources,
`11.1.1 Discrete Sources,
`11.1.2 Waveform Sources,
`Amplitude Quantizing,
`603
`11.2.1
`Quantizing Noise,
`605
`11.2.2
`Uniform Quantizing,
`608
`11.2.3
`Saturation,
`611
`11.2.4 Dithering,
`614
`617
`11.2.5 Nonumform Quantizing,
`Differential Pulse Code Modulation,
`11.3.1
`One-Tap Prediction,
`630
`11.3.2
`N-Tap Prediction,
`631
`
`627
`
`APPL-1015 / Page 12 0f41
`
`APPL-1015 / Page 12 of 41
`
`

`
`11.4
`
`11.5
`
`11.6
`
`11.7
`
`633
`639
`
`11.3.3 Delta Modulation,
`11.3.4 Adaptive Prediction,
`Block Coding,
`643
`643
`11.4.1
`Vector Quantizing,
`645
`11.4.2
`Transform Coding,
`11.4.3
`Quantization for Transform Coding,
`11.4.4
`Subband Coding,
`647
`Synthesis/Analysis Coding,
`11.5.1
`Vocoders,
`650
`11.5.2
`Linear Predictive Coding,
`Redundancy-Reducing Coding,
`11.6.1
`Properties of Codes,
`655
`11.6.2 Huffman Code,
`657
`11.6.3
`Run-Length Codes,
`Conclusion,
`663
`References,
`663
`Problems,
`664
`
`649
`
`653
`653
`
`660
`
`647
`
`12 ENCRYPTION AND DECRYPTION
`
`669
`12.1 Models, Goals, and Early Cipher Systems,
`12.1.1
`A Model of the Encryption and Decryption
`Process,
`669
`671
`System Goals,
`12.1.2
`671
`Classic Threats,
`12.1.3
`672
`Classic Ciphers,
`12.1.4
`The Secrecy of a Cipher System,
`12.2.1
`Perfect Secrecy,
`675
`678
`12.2.2
`Entropy and Equivocation,
`12.2.3
`Rate of a Language and Redundancy,
`12.2.4
`Unicity Distance and Ideal Secrecy,
`Practical Security,
`683
`12.3.1
`Confusion and Diflusion,
`12.3.2
`Substitution,
`683
`12.3.3
`Permutation,
`685
`686
`12.3.4
`Product Cipher System,
`12.3.5
`The Data Encryption Standard,
`Stream Encryption,
`694
`12.4.1
`Example of Key Generation Using a Linear
`Feedback Shift Register,
`694
`Vulnerabilities of Linear Feedback Shift
`Registers,
`695
`Synchronous and Self-Synchronous Stream
`Encryption Systems,
`697
`
`12.2
`
`12.3
`
`12.4
`
`12.4.2
`
`12.4.3
`
`675
`
`683
`
`680
`680
`
`687
`
`
`
`595
`
`Contents
`
`Contents
`
`xvii
`
`
`
`APPL-1015 / Page 13 0f41
`
`APPL-1015 / Page 13 of 41
`
`

`
`12.5.2
`12.5.3
`12.5.4
`12.5.5
`
`698
`Public Key Cryptosystems,
`12.5.1
`Signature Authentication Using a Public Key
`Cryptosystem,
`699
`700
`A Trapdoor One-Way Function,
`The Rivest—Shamir—Adelman Scheme,
`The Knapsuclc Problem,
`703
`A Public Key Cryptosystem Based on a Trapdoor
`Knapsack,
`705
`Conclusion,
`707
`References,
`707
`Problems,
`708
`
`701
`
`A A REVIEW OF FOURIER TECHNIQUES
`
`A.1
`A.2
`
`710
`Signals, Spectra, and Linear Systems,
`Fourier Techniques for Linear System Analysis,
`/1.2.1
`Fourier Series Transform,
`713
`A.2.2
`Spectrum ofa Pulse Train,
`716
`A.2.3
`Fourier Integral Transform,
`719
`Fourier Transform Properties,
`720
`/1.3.1
`Time Shifting Property,
`720
`A.3.2
`Frequency Shifting Property,
`Useful Functions,
`721
`A.4.1
`Unit Impulse Function,
`/1.4.2
`Spectrum of u Sinusoid,
`Convolution,
`722
`A.5 .1
`Graphical Illustration of Convolution,
`A.5 .2
`Time Convolution Property,
`726
`726
`A.5 .3
`Frequency Convolution Property,
`A.5 .4
`Convolution of a Function with a Unit
`Impulse,
`728
`Demodulution Application of Convolution,
`A.5.5
`Tables of Fourier Transforms and Operations,
`References,
`732
`
`720
`
`721
`721
`
`711
`
`729
`731
`
`726
`
`B FUNDAMENTALS OF STATISTICAL DECISION
`THEORY
`
`B.1
`
`733
`Bayes’ Theorem,
`B.1.1
`Discrete Form of Bayes’ Theorem,
`B._1.2 Mixed Form of Bayes’ Theorem,
`
`734
`736
`
`APPL-1015 / Page 14 0f41
`
`APPL-1015 / Page 14 of 41
`
`

`
`B.2
`
`B.3
`
`738
`Decision Theory,
`B.2.I
`Components of the Decision Theory Problem,
`B.2.2
`The Likelihood Ratio Test and the Maximum
`A Posteriori Criterion,
`739
`The Maximum Likelihood Criterion,
`13.2.3
`Signal Detection Example,
`740
`B.3.1
`The Maximum Likelihood Binary Decision,
`B.3.2
`Probability ofBi1‘ Error,
`741
`References,
`743
`
`739
`
`738
`
`740
`
`:
`
`;
`i
`
`C RESPONSE OF CORRELATORS TO WHITE NOISE
`
`744
`
`746
`
`743
`
`759
`
`755
`
`710
`
`!
`
`D OFTEN USED IDENTITIES
`
`E A CONVOLUTIONAL ENCODERJDECODER
`COMPUTER PROGRAM
`
`F LIST OF SYMBOLS
`
`INDEX
`
`.
`
`"t
`
`i I
`
`733
`
`Contents
`
`contents
`
`xix
`
`APPL-1015 / Page 15 0f41
`
`APPL-1015 / Page 15 of 41
`
`

`
`4.1 WHAT THE SYSTEM LINK BUDGET TELLS THE
`SYSTEM ENGINEER
`
`_When we talk about a communications link, to what part of the system are we
`referring? Is it simply the channel or region between the transmitter and receiver?
`No, it is far more than that. The link-encompasses the entire communications
`path, from the information source, through all the encoding and modulation steps,
`through the transmitter and the channel, up to and including the receiver with all
`its signal processing steps, and terminating at the information sink.
`What is a link analysis, and what purpose does it serve in the development
`of a communication system? The link analysis, and its output, the link budget,
`consist of the calculations and tabulation of the useful signal power and the in-
`terfering noise power available at the receiver. The link budget is a balance sheet
`of gains and losses; it outlines the detailed apportionment of transmission and
`reception resources, noise sources, signal attenuators, and effects of processes
`throughout the link. Some of the budget parameters are statistical (e.g. , allowances
`for the fading of signals due to meteorological events); the budget is therefore an
`estimation technique for evaluating communication system performance. In Chap-
`ter 3 we examined probability of error versus Eb/No curves having a “waterfall-
`like” shape, such as the one shown in Figure 3.21. We thereby related error
`probability to Eb/No for various modulation types in Gaussian noise. Once a mod-
`ulation scheme has been chosen, the requirement to meet a particular error prob-
`ability dictates a particular operating point on the curve; in other words, the
`required error performance dictates the value ofEb/No that must be made available
`
`188
`
`Communications Link Analysis
`
`Chap. 4
`
`APPL-1015 / Page 16 0f41
`
`APPL-1015 / Page 16 of 41
`
`

`
`at the receiver in order to meet that performance. The primary purpose of a link
`analysis is to determine the actual system operating point in Figure 3.21 and to
`establish that the error probability associated with that point is less than or equal
`to the system requirement. Of the many specifications, analyses, and tabulations
`that are used in the development of a communication system, the link budget
`stands out as a basic tool for providing the system engineer with overall system
`insight.
`By examining the link budget, one can learn many things about overall sys-
`tem design and performance. For example, from the link margin, one learns
`whether the system will meet its requirements conifortably, marginally, or not at
`all. It will be evident if there are any hardware constraints, and whether such
`constraints can be compensated for in other parts of the link. The link budget is
`often used as a “score sheet” in considering system trade—0ffs and configuration
`changes, and in understanding subsystem nuances and interdependencies. From
`a quick examination of the link budget and its supporting documentation, one can
`judge whether the analysis was done precisely or if it represents a rough estimate.
`Together with other modeling techniques, the link budget can help predict equip-
`ment Weight, size, prime power requirements, technical risk, and cost. The link
`budget is one of the system manager’s most useful documents; it represents the
`“bottom-line” tally in the search for optimimum system performance.
`
`4.2 THE CHANNEL
`
`The propagating medium or electromagnetic path connecting the transmitter and
`receiver is called the channel. In general, a communications channel might consist
`of wires, coaxial cables, fiber optic cables, and in the case of radio—frequency
`(RF) links, waveguides, the atmosphere, or empty space. For most terrestrial
`communication links, the channel space is occupied by the atmosphere and par-
`tially bounded by the earth‘s surface. For satellite links, the channel is occupied
`mostly by empty space. Although some atmospheric effects occur at altitudes up
`to 100 km, the bulk of the atmosphere extends to an altitude of 20 km. Therefore,
`only a small part (0.05%) of the total synchronous altitude (35,800 km) path is
`occupied by significant amounts of atmosphere. Most of this chapter is presented
`in the context of such a satellite communications link.
`
`4.2.1 The Concept of Free Space
`
`The concept of free space assumes a channel free of all hindrances to RF prop-
`agation, such as absorption, reflection, refraction, or diffraction. If there is any
`atmosphere in the channel, it must be perfectly uniform and meet all these con-
`ditions. Also, we assume that the earth is infinitely far away or that its reflection
`coefficient is negligible. The RF energy arriving at the receiver is assumed to be
`a function only of distance from the transmitter (following the inverse-square law
`of optics). A free-space channel characterizes an ideal RF propagation path; in
`practice, propagation through the atmosphere and near the ground results in ab-
`
`Sec. 4.2
`
`The Channel
`
`189
`
`the system are we
`uitter and receiver?
`re communications
`:1 modulation steps,
`zhe receiver with all
`.1 sink.
`
`}in the development
`ut, the link budget,
`1 power and the in-
`st is a balance sheet
`Jf transmission and
`
`affects of processes
`cal (e.g., allowances
`idget is therefore an
`rformance. In Chap-
`having a “waterfall-
`lereby related error
`. noise. Once a mod-
`
`articular error prob-
`in other words, the
`LS1. be made available
`
`Analysis
`
`Chap. 4
`
`APPL-1015 / Page 17 0f41
`
`APPL-1015 / Page 17 of 41
`
`

`
`sorption, reflection, refraction, and diffraction, which modify the free—space trans-
`mission. Atmospheric absorption is treated in later sections. Reflection, refrac-
`tion, and diffraction, which play an important role in determining terrestrial
`communications performance, are not treated here; Panter [1] provides a com-
`prehensive treatment of these mechanisms.
`
`4.2.2 Signal-to-Noise Ratio Degradation
`
`The signal—to—noise power ratio (SNR) defined below is a convenient measure of
`performance at various points in the link.
`
`SNR =
`
`signal power
`.
`noise power
`
`Unless otherwise stated, SNR refers to average signal power and average noise
`power. The signal can be an information signal, a basehand waveform, or a mod-
`ulated carrier. The SNR can degrade in two ways: (1) through the decrease of
`the desired signal power, and (2) through the increase of noise power, or the
`increase of interfering signal power. Let us refer to these degradations as loss
`and noise (or interference), respectively. Losses occur when aportion of the signal
`is absorbed, diverted, scattered, or reflected along its route to the intended re-
`ceiver; thus a portion of the transmitted energy does not arrive at the receiver.
`There are four primary noise sources: (1) thermal noise can be generated within
`the link, (2) sky noise (e.g., galaxy noise, atmospheric noise) can be introduced
`into the link, (3) system nonlinearities can cause spurious signals to be created
`within the link, and (4) interfering signals from other users of the same frequency
`can be introduced into the link. Industry usage of the terms loss and noise fre-
`quently confuses the underlying degradation mechanism; however, the net effect
`on the SNR is the same.
`
`4.2.3 Sources of Signal Loss and Noise
`
`Figure 4.1 is a block diagram of a satellite communications link, emphasizing the
`sources of signal loss and noise. In the figure a signal loss is distinguished from
`a noise source by a dot pattern or line pattern, respectively. The contributors of
`both signal loss and noise are identified by a crosshatched line pattern. The fol-
`lowing list of 21 sources of degradation represents a partial catalog of the major
`contributors to SNR degradation. The numbers correspond to the numbered cir-
`cles in Figure 4.1.
`
`1. Bandiimiting loss. All systems use filters in the transmitter to ensure that
`the transmitted energy is confined to the allocated or assigned bandwidth.
`This is to avoid interfering with other channels or users and to meet the
`requirements of regulatory agencies. Such filtering reduces the total amount
`of energy that would otherwise have been transmitted; the result is a loss
`in signal.
`
`
`
`Communications Link Analysis
`
`Chap. 4
`
`
`
`APPL-1015 / Page 18 0f41
`
`APPL-1015 / Page 18 of 41
`
`

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`APPL-1015 / Page 19 of 41
`
`
`
`
`
`
`
`

`
`. Intersymbol interference (ISI). As discussed in Chapter 2, filtering through-
`out the system—in the transmitter, in the receiver, and in the channel—can
`result in ISI. The received pulses overlap one another; the tail of one pulse
`“smears” into adjacent symbol intervals so as to interfere with the detection
`process. Even in the absence of thermal noise, imperfect filtering and system
`bandwidth constraints lead to ISI degradation.
`. Local oscillator (LO) phase noise. When an ‘L0 is used in signal mixing,
`phase fluctuations or jitter adds phase noise to the signal. When used as the
`reference signal in a receiver correlator, phase jitter can cause detector
`degradation and hence signal loss. At the transmitter, phase jitter can cause
`out—of—band signal spreading, which, in turn, will be filtered out and cause
`a loss in signal.
`
`. AM/PM conversion. AM-to—PM conversion is a phase noise phenomenon
`occurring in nonlinear devices such as traveling-wave tubes (TWT). Signal
`amplitude fluctuations (amplitude modulation) produce phase variations that
`contribute phase noise to signals that will be coherently detected. AM-to-
`PM conversion can also cause extraneous sidebands, resulting in signal loss.
`. Limiter loss or enhancement. A hard limiter can enhance the stronger of
`two signals, and suppress the weaker; this can result in either a signal loss
`or a signal gain [2].
`
`. Mnltipie—carrier intermodulation (IM) products. When several signals having
`different carrier frequencies are simultaneously present in a nonlinear de-
`vice, such as a TWT, the result is a multiplicative interaction between the
`carrier frequencies which can produce signals at all combinations of sum
`and difference frequencies. The energy apportioned to these spurious signals
`(intermodulation or IM products) represents a loss in signal energy. In ad-
`dition, if these IM products appear within the bandwidth region of these or
`other signals, the effect is that of added noise for those signals.
`. Modulation loss. The link budget is a calculation of received useful power
`(or energy). Only the power associated with information-bearing signals is
`useful. Error performance is a function of energy per transmitted symbol.
`Any power used for transmitting the carrier rather than the modulating signal
`(symbols) is a modulation loss. (However, energy in the carrier may be useful
`in aiding synchronization.)
`‘
`
`. Antenna efliciency. Antennas are transducers that convert electronic signals
`into electromagnetic fields, and vice versa. They are also used to focus the
`electromagnetic energy in a desired direction. The larger the antenna ap-
`erture (area), the larger is the resulting signal power density in the desired
`direction. An antenna’s efficiency is described by the ratio of its effective
`aperture to its physical aperture. Mechanisms contributing to a reduction in
`efficiency (loss in signal strength) are known as amplitude tapering, aperture
`blockage, scattering, re-radiation, spillover, edge diffraction, and dissipative
`loss [3]. Typical efficiencies due to the combined effects of these mechanisms
`range between 50 and 30%.
`
`9. Radome loss and noise. A radome is a protective cover, use