Ee
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`7
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`DIGITAL
`COMMUNICATIONS
`Fundamentals and Applications
`
`BERNARD SKLAR
`The Aerospace Corporation, E/ Segundo, California
`dan
`University of California, Los Angeles
`
`P T R Prentice Hall
`Englewood Cliffs, New Jersey 07632
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`
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`HTC/ZTE Exhibit 1015
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`

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`Library of Congress Cataloging-in-Publication Data
`
`Skvar, Bernarp (date)
`Digital communications.
`
`Bibliography: p.
`Includes index.
`[. Title.
`1. Digital communications.
`TK5103.7.555
`1988
`621.38'0413
`ISBN 0-13-211939-@
`
`87-1316
`
`
`
`Editorial/production 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 O-135-211939-0
`
`O25
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`Prentice-Hall International (UK) Limited, London
`Prentice-Hall of Australia Pty. Limited, Sydney
`Prentice-Hall Canada Inc., Toronto
`Prentice-Hall Hispanoamericana, $.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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`HTC/ZTE Exhibit 1015-2
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`HTC/ZTE Exhibit 1015-2
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`Contents :
`
`PREFACE
`
`1
`
`SIGNALS AND SPECTRA
`
`1.1
`
`1.2
`
`1.3.
`
`1.5
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`Digital Communication Signal Processing,
`Lid) Why Digital?,
`3
`i.d.2
`Typical Block Diagram and Transformations, 4
`14.3 Basic Digital Communication Nomenclature,
`9
`14.4 Digital versus Analog Performance Criteria,
`11
`Classification of Signals,
`11
`121 Deterministic and Random Signals,
`1.2.2
`Periodic and Nonperiodic Signals,
`1.2.3 Analog and Discrete Signals,
`12
`124
`Energy and Power Signals,
`12.5
`The Unit Impulse Function,
`Spectral Density,
`14
`13.1
`Energy Spectral Density,
`13.2
`Power Spectral Density,
`1.4 Autocorrelation,
`17
`17
`1.4.1 Autocorrelation of an Energy Signal,
`£4.2 Autocorrelation of a Periodic (Power) Signal,
`Random Signals,
`18
`135.1
`Random Variables,
`15.2 Random Processes,
`
`3
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`11
`12
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`17
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`12
`13
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`14
`15
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`18
`20
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`xxi
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`1
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`1.7
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`1.8
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`38
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`43
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`22
`Time Averaging and Ergodicity,
`1.5.3
`
`23
`Power Spectral Density of a Random Process,
`134
`
`L5,.5|Noise in Communication Systems, 27
`
`
`1.6
`Signal Transmission through Linear Systems,
`30
`1.6.2
`Impulse Response,
`31
`
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`31
`1.6.2
`Frequency Transfer Function,
`
`32
`1.6.3 Distortionless Transmission,
`
`1.6.4
`Signals, Circuits, and Spectra,
`
`Bandwidth of Digital Data,
`41
`‘
`i.7,1
`Baseband versus Bandpass,
`41
`
`
`1.7.2
`The Bandwidth Dilemma,
`
`Conclusion,
`46
`References,
`46
`
`Problems,
`47
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`2 FORMATTING AND BASEBAND TRANSMISSION
`
`51
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`55
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`Contents HTC/ZTE Exhibit 1015-4
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`54
`Baseband Systems,
`2.1
`Formatting Textual Data (Character Coding),
`2.2
`2.3 Messages, Characters, and Symbols,
`55
`2.3.1
`Example of Messages, Characters, and
`Symbols,
`55
`Formatting Analog Information,
`24.1
`The Sampling Theorem,
`24,2
` 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,
`71
`2.5.3
`Signal-to-Noise Ratio for Quantized Pulses,
`Pulse Code Modulation,
`73
`2.6
`2.7 Uniform and Nonuniform Quantization,
`2.7.1
`Statistics of Speech Amplitudes,
`74
`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,
`2.9 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
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`2.4
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`2.5
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`2.8
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`59
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`59
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`69
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`70
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`74
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`77
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`72
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`2.11
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`2.10 Multilevel Baseband Transmission,
`2.10.1 PCM Word Size,
`97
`98
`Intersymbol Interference,
`2411 Pulse Shaping to Reduce ISI,
`2.41.2 Equalization,
`104
`2.12 Partial Response Signaling,
`2.12.1 Duobinary Signaling,
`2.12.2 Duobinary Decoding,
`2.12.3 Precoding,
`108
`2.12.4 Duobinary Equivalent Transfer Function,
`2.12.5 Comparison ofBinary with Duobinary
`Signaling,
`[11
`2.12.6 Polybinary Signaling,
`2.13 Conclusion,
`112
`References,
`113
`Problems,
`113
`
`95
`
`100
`
`106
`106
`107
`
`112
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`109
`
`51
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`3
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`BANDPASS MODULATION AND DEMODULATION
`
`117
`
`3.3
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`3.5
`
`118
`3.1 Why Modulate?,
`119
`3.2
`Signals and Noise,
`119
`3.2.1 Noise in Radio Communication Systems,
`120
`3.2.2.
`A Geometric View of Signals and Noise,
`Digital Bandpass Modulation Techniques,
`127
`33.1
`Phase Shift Keying,
`130
`130
`3.3.2
`Frequency Shift Keying,
`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,
`34.1 Decision Regions,
`132
`3.4.2
`Correlation Receiver,
`Coherent Detection,
`138
`138
`3.5.1
`Coherent Detection of PSK,
`3.5.2
`Sampled Matched Filter,
`139
`3.5.3
`Coherent Detection of Multiple Phase Shift
`Keying,
`142
`Coherent Detection of FSK,
`3.5.4
`3.6 Noncoherent Detection,
`146
`146
`3.6.1 Detection of Differential PSK,
`148
`3.6.2 Binary Differential PSK Example,
`150
`3.6.3 Noncoherent Detection of FSK,
`3.64 Minimum Required Tone Spacing for Noncoherent
`Orthogonal FSK Signaling, 52
`
`132
`132
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`133
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`145
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`Contents
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`Contents
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`176
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`3.7.2
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`3.7.3
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`3.7.4
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`3.7.5
`3.7.6
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`3.7.
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`3.9
`
`155
`Error Performance for Binary Systems,
`3.7.1. Probability of Bit Error for Coherently Detected
`BPSK,
`155
`Probability ofBit Error for Coherently Detected
`Differentially Encoded PSK,
`160
`Probability ofBit Error for Coherently Detected
`FSK,
`161
`Probability of Bit Error for Noncoherently Detected
`FSK,
`i162
`‘
`164
`Probability of Bit Error for DPSK,
`Comparison ofBit Error Performance for Various
`Modulation Types,
`166
`167
`3.8 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 ofMPSK Signaling,
`3.84 BPSK and QPSK Have the Same Bit Error
`Probability,
`171
`3.8.5
`Vectorial View ofMFSK Signaling,
`172
`Symbol Error Performance for M-ary Systems (M > 2),
`3.9.1
`Probability of Symbol Error for MPSK,
`176
`3.9.2
`Probability of Symbol Error for MFSK,
`177
`3.9.3 Bit Error Probability versus Symbol Error Probability
`Jor Orthogonal Signals,
`180
`Bit Error Probability versus Symbol Error Probability
`3.9.4
`for Multiple Phase Signaling,
`181
`Effects of Intersymbol Interference,
`182
`3.9.5
`3.10 Conclusion,
`182
`References,
`182
`Problems,
`183
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`167
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`4 COMMUNICATIONSLINK ANALYSIS
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`187
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`What the System Link Budget Tells the System
`188
`Engineer,
`The Channei,
`189
`4.24
`189
`The Concept of Free Space,
`4.2.2
`Signal-to-Noise Ratio Degradation,
`4.2.3
`Sources of Signal Loss and Noise,
`Received Signal Power and Noise Power,
`4.31
`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
`
`190
`196
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`195
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`200
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`4.1
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`4.2
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`4,3
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`4.3.3
`4.3.4
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`4.4
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`4.5
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`4.6
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`4.7
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`4.8
`4.9
`
`207
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`215
`
`4
`
`204
`Link Budget Analysis,
`205
`44.1
`Two E,/No Values of Interest,
`44.2
`Link Budgets Are Typically Catculated in
`Decibels,
`206
`4.43 How Much Link Margin Is Enough?,
`4.44
`Link Availability,
`209
`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,
`4.6.2
`Receiver Figure-of-Merit,
`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
`
`220
`
`236
`
`230
`231
`
`5) CHANNEL CODING: PART 1
`
`245
`
`246
`5.1 Waveform Coding,
`5.1.1 Antipodal and Orthogonal Signals,
`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
`5.34
`Coding Gain,
`266
`
`247
`
`257
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`249
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`259
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`263
`
`5.2
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`5.3.
`
`176
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`187
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`Contents
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`Contents
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`6.1.
`6.2
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`6.3
`
`317
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`;
`322
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`327
`
`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,
`6.3.1 Maximum Likelihood Decoding,
`327
`6.3.2
`Channel Models: Hard versus Soft Decisions,
`6.3.3
`The Viterbi Convolutional Decoding Algorithm,
`
`5.4
`
`5.5
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`5.6
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`5.8
`
`269
`Linear Block Codes,
`269
`5.4.1
`Vector Spaces,
`270
`5.4.2
`Vector Subspaces,
`3.4.3
`A (6, 3) Linear Block Code Example,
`3.4.4 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
`280
`5.3.1 Weight and Distance of Binary Vectors,
`5.5.2 Minimum Distance of a Linear Code,
`281
`5.5.3
`Error Detection and Correction,
`281
`5.5.4
`Visualization of a 6-Tuple Space,
`285
`3.I.5
`Erasure Correction,
`287
`Cyclic Codes,
`288
`3.6.1 Algebraic Structure of Cyclic Codes,
`53.6.2
`Binary Cyclic Code Properties,
`290
`3.6.3
`Encoding in Systematic Form,
`290
`53.6.4
`Circuit for Dividing Polynomials,
`292
`3.6.5
`Systematic Encoding with an (n — k)-Stage Shift
`Register,
`294
`Error Detection with an (n — k)-Stage Shift
`Register,
`296
`5.7 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
`
`271
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`273
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`288
`
`5.6.6
`
`298
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`301
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`304
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`6 CHANNEL CODING: PART 2
`
`314
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`Contents
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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
`Cades,
`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
`Convolutional Cade Rate Trade-Off,
`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
`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 Muting,
`Conclusion,
`374
`References,
`374
`Problems,
`376
`
`6.4.3
`
`6.4
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`6.6
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`6.7
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`6.8
`
`338
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`344
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`337
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`347
`348
`350
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`357
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`362
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`371
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`7 MODULATION AND CODING TRADE-OFFS
`
`381
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`314
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`327
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`.
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`Goals of the Communications System Designer,
`7.1.
`Exror Probability Plane,
`383
`7.2
`385
`7.3. Nyquist Minimum Bandwidth,
`7.4
`Shannon-Hartley Capacity Theorem,
`7.4.1
`Shannon Limit,
`387
`7.4.2
`Entropy,
`389
`7.4.3
`Equivocation and Effective Transmission Rate,
` Bandwidth-Efficiency Plane,
`393
`7.5.2
`Bandwidth Efficiency of MPSK and MFSK
`Modulation,
`395
`7.5.2 Analogies between Bandwidth-Efficiency and Error
`Probability Planes,
`396
`Power-Limited Systems,
`396
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`385
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`382
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`391
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`7.5
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`7.6
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`Contents
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`429
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`410
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`412
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`434
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`465
`468
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`399
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`417
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`i 7
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`.9
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`7.10
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`7Al
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`SYNCHRONIZATION
`Maurice A. King,Jr.
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`8.1
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`8.2
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`8.3:
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`8.4
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`Synchronization in the Context of Digital
`Communications,
`430
`430
`8.1.4 What It Means to Be Synchronized,
`8.1.2
`Costs versus Benefits af 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
`
`475
`
`9.1
`
`Allocation of the Communications Resource,
`94.
`Frequency-Division Multipiexing/Muttiple
`Access,
`478
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`4761
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`Contents
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`HTC/ZTE Exhibit 1015-10
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`397
`Bandwidth-Limited Systems,
`397
`Modulation and Coding Trade-Offs,
`399
`Bandwidth-Efficient Modulations,
`7.9.1
`QPSK and Offset OPSK Signaling,
`7.9.2 Minimum Shift Keying,
`403
`7.9.3. Quadrature Amplitude Modulation, 407
`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 Constellations,
`7.10.4 Higher-Density Lattice Structures,
`415
`7.10.5 Combined-Gain: N-Sphere Mapping and Dense
`Lattice,
`416
`7.40.6 Trellis-Coded Modulation,
`7.10.7 Trellis-Coding Example,
`Conclusion,
`424
`References,
`425
`Problems,
`426
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`9.1.2
`9.1.3
`9.1.4
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`9.1.5
`9.1.6
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`9.6
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`Time-Division Multiplexing/Multiple Access,
`Communications Resource Channelization,
`Performance Comparison of FDMA and
`TDMA,
`‘488
`491
`Code-Division Multiple Access,
`Space-Division and Polarization-Division Multiple
`Access,
`493
`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,
`93.4
`Performance Comparison of S-ALOHA
`and R-ALOHA,
`503
`305
`Polling Techniques,
`9.3.5
`9.4 Multiple Access Techniques Employed with
`INTELSAT,
`507
`94.1
` Preassigned FDMIFM/IFDMA or MCPC
`Operation,
`508
`9.4.22 MCPC Moades of Accessing an INTELSAT
`Satellite,
`510
`SPADE Operation, 5il
`9.4.3.
`TDMA in INTELSAT,
`S516
`944
`523
` Satellite-Switched TDMA in INTELSAT,
`94.5
`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,
`331
`References,
`532
`Problems,
`333
`
`484
`487
`
`526
`
`429
`
`475°
`
`10 SPREAD-SPECTRUM TECHNIQUES
`
`536
`
`10.1
`
`537
`Spread-Spectrum Overview,
`10.1.1
`The Beneficial Attributes of Spread-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
`
`Contents
`
`Contents
`
`xv
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`HTC/ZTE Exhibit 1015-11
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`HTC/ZTE Exhibit 1015-11
`
`

`

`
`
`549
`
`552
`
`559
`560
`
`571
`
`579
`579
`581
`
`586
`
`10.2
`
`10.4
`
`10.5
`
`10.6
`
`10.7.
`
`10.8
`
`546
`Pseudonoise Sequences,
`546
`10.2.1
`Randomness Properties,
`547
`10.2.2
`Shift Register Sequences,
`548
`10.2.3
`PN Autocorrelation Function,
`10.3 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
`FFHIMFSK Demodulator,
`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 Neise Jamming,
`10.7.3 Multiple-Tone Jamming,
`583
`10.7.4
`Puise Jamming,
`584
`10.7.5 Repeat-Back Jamming,
`10.7.6 BLADES System,
`588
`Conclusion,
`589
`References,
`589
`Problems,
`591
`
`| || |
`
`595
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
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`
`
`
`
`|
`
`
`
`
`
`
`
`
`
`
`
`
`
`|
`I:
`
`Li
`,
`
` Contents
`
`HTC/ZTE Exhibit 1015-12
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`11 SOURCE CODING
`Fredric J. Harris
`
`11,1
`
`11.2
`
`11.3
`
`596
`601
`
`596
`Sources,
`did. Discrete Sources,
`11.1.2 Waveform Sources,
`Amplitude Quantizing,
`603
`11.2.1
`Quantizing Noise,
`605
`11.2.2
`Uniform Quantizing,
`608
`1.2.3
`Saturation,
`611
`I1.2.4 Dithering,
`614
`617
`112.5 Nonuniform Quantizing,
`Differential Pulse Code Modulation,
`41.3.1
`One-Tap Prediction,
`630
`11.3.2
`N-Tap Prediction,
`631
`
`627
`
`.
`
`HTC/ZTE Exhibit 1015-12
`
`

`

`664
`
`11.4
`
`11.5
`
`11.6
`
`11.7
`
`13.3 Delta Modulation,
`11.3.4 Adaptive Prediction,
`Block Coding,
`643
`643
`14d
`Vector Quantizing,
`645
`11.4.2
`Transform Coding,
`114.3
`Quantization for Transform Coding,
`11.4.4
`Subband Coding,
`647
` Synthesis/Analysis Coding,
`ii.5.1
` Vocoders,
`650
`{1.5.2
`Linear Predictive Coding,
`Redundancy-Reducing Coding,
`ii.6.1
`Properties of Codes,
`655
`11.6.2 Huffman Code,
`657
`116.3
` Run-Length Codes,
`Conclusion,
`663
`References,
`663
`Problems,
`
`633
`639
`
`649
`
`660
`
`653
`653
`
`‘
`
`:
`
`,
`
`647
`
`
`
`595
`
`12 ENCRYPTION AND DECRYPTION
`
`_ 668
`
`669
`12.1 Models, Goals, and Early Cipher Systems,
`I2.1.1
`A Modelof the Encryption and Decryption
`Process,
`669
`671
`System Goals,
`12.1.2
`671
`Classic Threats,
`12.1.3
`672
`Classic Ciphers,
`12,14
`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 Diffusion,
`12.3.2
`Substitution,
`683
`12.3.3
`Permutation,
`685
`686
`12.34
`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
`
`Contents
`
`Contents
`
`xvii
`
`HTC/ZTE Exhibit 1015-13
`
`HTC/ZTE Exhibit 1015-13
`
`

`

`Puolic Key Cryptosystems,
`
`2.5
`
`698
`
`12.5.2.
`12.53
`I2.5.4
`12.5.5
`
`Signature Authentication Using a Public Key
`Cryptosystem,
`699
`700
`A Trapdoor One-Way Function,
`The Rivest-Shamir—Adelman Scheme,
`The Knapsack Problem,
`703
`A Public Key Cryptosystem Based on a Trapdoor
`Knapsack,
`705
`Conclusion,
`707
`References,
`707
`Problems,
`708
`
`7601
`
`Or4
`
`
`710
`Signals, Spectra, and Linear Systems,
`Fourier Techniques for Linear System Analysis,
`A.2.1
`Fourier Series Transform,
`713
`A.2.2
`Spectrum of a Pulse Train,
`716
`
`A2.3>Fourier Integral Transform, 719
`Fourier Transform Properties,
`720
`AZ.)
`Time Shifting Property,
`720
`AJ3.2
`Frequency Shifting Property,
`Useful Functions,
`721
`721
`A.4l
`Unit Impulse Function,
`
`A4.29Spectrum of a Sinusoid, 721
`Convolution,
`722
`Graphical Illustration of Convolution,
`Time Convolution Property,
`726
`726
`Frequency Convolution Property,
`Convolution of a Function with a Unit
`Impulse,
`728
`Demodulation Application of Convolution,
`Tables of Fourier Transforms and Operations,
`References,
`732
`
`A A REVIEW OF FOURIER TECHNIQUES
`
`A.l
`A.2
`
`720
`
`711
`
`726
`
`729
`731
`
`FUNDAMENTALS OF STATISTICAL DECISION
`THEORY
`
`B.1
`
`733
`Bayes’ Theorem,
`Bi
`Discrete Form of Bayes’ Theorem,
`BuI.2 Mixed Form of Bayes’ Theorem,
`
`734
`736
`
`Contents
`
`HTC/ZTE Exhibit 1015-14
`
`

`

`B.2
`
`B.3
`
`738
`Decision Theory,
`B.2.1
`Components of the Decision Theory Problem,
`B.2.2.
`The Likelihood Ratio Test and the Maximum
`A Posteriori Criterion,
`739
`The Maximum Likelihood Criterion,
`B.2.3.
`Signal Detection Example,
`740
`B.3.1
`The Maximum Likelihood Binary Decision,
`B.3.2
`Probability ofBit Error,
`74!
`References,
`743
`
`739
`
`738
`
`740
`
`RESPONSE OF CORRELATORS TO WHITE NOISE
`
`710
`
`OFTEN USED IDENTITIES
`
`A CONVOLUTIONAL ENCODER/DECODER
`COMPUTER PROGRAM
`
`LIST OF SYMBOLS
`
`INDEX
`
`744
`
`746
`
`748
`
`759
`
`765
`
`733
`
`Contents
`
`Contents
`
`xix
`
`HTC/ZTE Exhibit 1015-15
`
`HTC/ZTE Exhibit 1015-15
`
`

`

`HTC/ZTE Exhibit 1015-16
`
`‘Whenwetalk 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.
`Whatis 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 poweravailable 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
`throughoutthe link. Someofthe 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 E,/No curves having a ‘‘waterfall-
`like’? shape, such as the one shown in Figure 3.21. We thereby related error
`probability to E,/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 ofE,/No that must be made available
`
`4.1 WHAT THE SYSTEM LINK BUDGET TELLS THE
`SYSTEM ENGINEER
`
`188
`
`Communications Link Analysis
`
`Chap. 4
`
`HTC/ZTE Exhibit 1015-16
`
`

`

`at the receiver in order to meet that performance. The primary purposeofa 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 aboutoverall sys-
`tem design and performance. For example, from the link margin, one learns
`whether the system will meet its requirements comfortably, 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 budgetis
`often used as a ‘‘score sheet’’ in considering system trade-offs and configuration
`changes, and in understanding subsystem nuances and interdependencies. From
`a quick examinationof the link budget and its supporting documentation, one can
`judge whether the analysis was doneprecisely orif 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
`budgetis 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 mostterrestrial
`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 occurat altitudes up
`to 100 km, the budk of the atmosphere extendsto an altitude of 20 km. Therefore,
`only a small part (0.05%) of the total synchronousaltitude (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 channelfree 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 meetall 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 groundresults in ab-
`
`Sec. 4.2
`
`The Channel
`
`189
`
`the system are we
`nitter and receiver?
`re communications
`d modulation steps,
`he receiver with all
`1 sink,
`in the development
`ut, the link budget,
`| power and the in-
`-t is a balance sheet
`of transmission and
`‘ffects of processes
`cal (e.g., allowances
`dget is therefore an
`formance. In Chap-
`having a ‘“‘waterfall-
`ereby related error
`noise. Once a mod-
`articular error prob-
`in other words, the
`st be made available
`
`Analysis
`
`Chap. 4
`
`HTC/ZTE Exhibit 1015-17
`
`HTC/ZTE Exhibit 1015-17
`
`

`

`
`
`
`
`
`
`
`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 baseband 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 a portion ofthe 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 Joss and noise fre-
`quently confuses the underlying degradation mechanism; however, the net effect
`on the SNRis 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. Bandlimiting loss. All systems usefilters 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. Suchfiltering reduces the total amount
`of energy that would otherwise have been transmitted; the result is a loss
`in signal.
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
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`
`
`
`
`
`
`
`
`
`
`
`
`
`
`Communications Link Analysis Chap. 4
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`Or i oe
`
`HTC/ZTE Exhibit 1015-18
`
`

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`HTC/ZTE Exhibit 1015-19
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`HTC/ZTE Exhibit 1015-20
`
`. Intersymbol interference (ISI). As discussed in Chapter2, filtering through-
`out the system—inthe 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 symbolintervals so as to interfere with the detection
`process. Evenin the absenceof thermal noise, imperfectfiltering and system
`bandwidth constraints lead to ISI degradation.
`. Local oscillator (LO) phase noise. When an ‘LOis used in signal mixing,
`phasefluctuationsorjitter adds phase noise to the signal. When used as the
`reference signal in a receiver correlator, phase jitter can cause detector
`degradation and hencesignal Joss. At the transmitter, phasejitter can cause
`out-of-band signal spreading, which, in turn, will be filtered out and cause
`@ 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
`amplitudefluctuations (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 /oss
`or a signal gain [2].
`. Multipie-carrier intermodulation (IM) products. Whenseveralsignals having
`different carrier frequencies are simultancously 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 Joss in signal energy. In ad-
`dition, if these IM products appear within the bandwidth region of these or
`othersignals, the effect is that of added noise for those signals,
`. Modulation loss. The link budgetis a calculation of received useful power
`(or energy). Only the power associated with information-bearingsignals is
`useful. Error performanceis a function of energy per transmitted symbol.
`Any powerusedfor transmitting the carrier rather than the modulating signal
`(symbols)iis a modulation /oss. (However, energy in the carrier may be useful
`in aiding synchronization.)
`. Antenna efficiency. Antennasare transducersthat 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 theratio of its effective
`aperture to its physical aperture. Mechanisms contributing to a reduction in
`efficiency (/oss in signal strength) are