`
`Addison-Wesley Wireless Communications Series
`
`V
`
`
`
`Andrew J. Viterbi
`
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`

`

`Principles of
`Spread Spectrum
`Communication
`
`Andrew J. Vi’rerbi
`
`A
`VV
`
`ADDISON-WESLEY PUBLISHING COMPANY
`
`Reading, Massachusetts . Menlo Park, California - New York - Don Mills, Ontario
`Wokingham, England . Amsterdam - Bonn . Sydney - Singapore - Tokyo - Madrid
`San Juan . Paris - Seoul . Milan - Mexico City - Taipei
`
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`

`

`Many of the designations used by manufacturers and sellers to distinguish their
`products are claimed as trademarks. Where those designations appear in this book
`and Addison-Wesley was aware of a trademark claim, the designations have been
`printed in initial caps or all caps.
`
`The publisher offers discounts on this book when ordered in quantity for Special
`sales. For more information please contact:
`Corporate 6: Professional Publishing Group
`Addison-Wesley Publishing Company
`One Jacob Way
`Reading, Massachusetts 01867
`
`Library of Congress Cataloging-in-Publication Data
`Viterbi, Andrew].
`CDMA : principles of spread spectrum communication / Andrew I, Viterbi.
`p. cm.
`Includes bibliographical references and index.
`ISBN 0-201—63374-4
`
`1. Code division multiple access. I. Title.
`TK5103.45.V57 1995
`321 .3845—dc20
`
`94-23800
`CIP
`
`Copyright © 1995 by Addison-Wesley Publishing Company
`All rights reserved. No part of this publication may be reproduced, stored in a
`retrieval system, or transmitted, in any form, or by any means, electronic, mechan-
`ical, photocopying, recording, or otherwise, without the prior consent of the pub-
`lisher. Printed in the United States of America. Published simultaneously in Can-
`ada.
`
`Text design by Wilson Graphics 6: Design (Kenneth ]. Wilson)
`
`ISBN 0-201-63374-4
`
`Text printed on recycled and acid-free paper.
`12345678910MA979695
`
`First Printing, April 1995
`
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`

`

`CONTENTS
`
`List of Figures and Tables xiii
`Preface xvii
`
`1 INTRODUCTION
`
`1.1 Definition and Purpose 1
`
`1.2 Basic Limitations of the Conventional Approach 2
`1.3 Spread Spectrum Principles 4
`
`1.4 Organization of the Text 8
`
`2 RANDOM AND PSEUDORANDOM SIGNAL
`GENERATION
`
`2.1 Purpose 11
`
`2.2 Pseudorandom Sequences 12
`
`2.2.1 Maximal Length Linear Shift Register Sequences 12
`2.2.2 Randomness Properties of MLSR Sequences 19
`2.2.3 Conclusion 22
`
`2.3 Generating Pseudorandom Signals (Pseudonoise) from
`Pseudorandom Sequences 23
`
`23.1 First- and Second-Order Statistics of Demodulator Output
`in Multiple Access Interference 26
`
`2.3.2 Statistics for QPSK Modulation by Pseudorandom
`Sequences 29
`
`2.3.3 Examples 31
`
`2.3.4 Bound for Bandlimited Spectrum 33
`
`2.4 Error Probability for BPSK or QPSK with Constant Signals in
`Additive Gaussian Noise and Interference 34
`
`Appendix 2A: Optimum Receiver Filter for Bandlimited Spectrum 37
`
`3 SYNCHRONIZATION OF PSEUDORANDOM SIGNALS
`
`3.1 Purpose 39
`
`3.2 Acquisitiou of Pseudorandom Signal Timing 39
`
`3.2.1 Hypothesis Testing for BPSK Spreading 40
`
`vli
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`viii
`
`Contents
`
`3.2.2 Hypothesis Testing for QPSK Spreading 44
`
`3.2.3 Effect of Frequency Error 45
`
`3.2.4 Additional Degradation When N 15 Much Less Than One
`Period 48
`
`3.3 Detection and False Alarm Probabilities 48
`
`3.3.1 Fixed Signals in Gaussian Noise (L = 1) 49
`
`3.3.2 Fixed Signals in Gaussian Noise with Postdetection
`Integration (L > 1) 50
`
`3.3.3 Rayleigh Fading Signals (L 2 1) 51
`
`3.4 The Search Procedure and Acquisition Time 52
`
`3.4.1 Single-Pass Serial Search (Simplified) 53
`
`3.4.2 Single-Pass Serial Search (Complete) 56
`
`3.4.3 Multiple Dwell Serial Search 58
`
`3.5 Time Tracking of Pseudorandom Signals 60
`
`3.5.1 Early-Late Gate Measurement Statistics 61
`
`3.5.2 Time Tracking Loop 63
`
`3.6 Carrier Synchronization 67
`
`Appendix 3A: Likelihood Functions and Probability Expressions 68
`
`3A.1 Bayes and Neyman—Pearson Hypothesis Testing 68
`
`3A2 Coherent Reception in Additive White Gaussian Noise 69
`
`3A.3 Noncoherent Reception in AWGN for Unfaded Signals 70
`
`3A.4 Noncoherent Reception of Multiple Independent
`Observations of Unfaded Signals in AWGN 72
`
`3A5 Noncoherent Reception of Rayleigh-Faded Signals in
`AWGN 74
`
`4 MODULATION AND DEMODULATION OF SPREAD
`
`SPECTRUM SIGNALS IN MULTIPATH AND MULTIPLE
`
`ACCESS INTERFERENCE
`
`' 4.1 Purpose 77
`
`4.2 Chemoff and Bhattacharyya Bounds 77
`4.2.1 Bounds for Gaussian Noise Channel 79
`
`4.2.2 Chernoff Bound for Time—Synchronous Multiple Access
`Interference with BPSK Spreading 80
`
`4.2.3 Chernoff Bound for Time-Synchronous Multiple Access
`Interference with QPSK Spreading 82
`
`4.2.4 Improving the Chernoff Bound by a Factor of 2 83
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`

`Contents
`
`ix
`
`4.3 Multipath Propagation: Signal Structure and Exploitation 84
`
`4.4 Pilot-Aided Coherent Multipath Demodulation 87
`
`4.4.1 Chemoff Bounds on Error Probability for Coherent
`Demodulation with Known Path Parameters 92
`
`4.4.2 Rayleigh and Rician Fading Multipath Components 93
`
`4.5 Noncoherent Reception 96
`
`4.5.1 Quasi-optimum Noncoherent Multipath Reception for
`M-ary Orthogonal Modulation 97
`4.52 Performance Bounds 105
`
`4.6 Search Performance for Noncoherent Orthogonal M-ary
`Demodulators 108
`
`4.7 Power Measurement and Control for Noncoherent Orthogonal
`M-ary Demodulators 113
`
`4.7.1 Power Control Loop Performance 116
`
`4.7.2 Power Control Implications 118
`
`Appendix 4A: Chernoff Bound with Imperfect Parameter
`Estimates 120
`
`5 CODING AND INTERLEAVING
`
`5.1 Purpose 123
`
`5.2 Interleaving to Achieve Diversity 123
`5.3 Forward Error Control Coding—Another Means to Exploit
`Redundancy 126
`
`5.3.1 Convolutional Code Structure 127
`
`5.3.2 Maximum Likelihood Decoder—Viterbi Algorithm 132
`
`5.3.3 Generalization of the Preceding Example 139
`
`5.4 Convolutional Code Performance Evaluation 140
`
`5.4.1 Error Probability for Tailed-off Block 140
`
`5.4.2 Bit Error Probability 142
`
`5.4.3 Generalizations of Error Probability Computation 143
`
`5.4.4 Catastrophic Codes 149
`5.4.5 Generalization to Arbitrary Memoryless Channels—
`Coherent and Noncoherent 151
`
`5.4.6 Error Bounds for Binary-Input, Output-Symmetric
`Channels with Integer Metrics 152
`5.5 A Near-Optimal Class of Codes for Coherent Spread Spectrum
`Multiple Access 155
`5.5.1 Implementation 155
`
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`x
`
`Contents
`
`5.5.2 Decoder Implementation 157
`
`5.5.3 Generating Function and Performance 159
`
`5.5.4 Performance Comparison and Applicability 164
`
`5.6 Orthogonal Convolutional Codes for Noncoherent Demodulaticm
`of Rayleigh Fading Signals 167
`
`5.6.1 Implementation 167
`
`5.6.2 Performance for L-Path Rayleigh Fading 168
`5.6.3 Conclusions and Caveats 171
`
`Appendix 5A: Improved Bounds for Symmetric Memoryless
`Channels and the AWGN Channel 173
`
`Appendix 58: Upper Bound on Free Distance of Rate 1/n
`Convolutional Codes 176
`
`6 CAPACITY, COVERAGE, AND CONTROL OF SPREAD
`SPECTRUM MULTIPLE ACCESS NETWORKS
`
`6.1 General 179
`
`6.2 Reverse Link Power Control 182
`
`6.3 Multiple Cell Pilot Tracking and Soft Handoff 183
`
`6.4 Other—Cell Interference 185
`
`6.4.1 Propagation Model 185
`
`6.4.2 Single-Cell Reception—Hard Handoff 186
`6.4.3 Soft Handoff Reception by the Better of the Two Nearest
`Cells 189
`
`6.4.4 Soft Handoff Reception by the Best of Multiple Cells 193
`6.5 Cell Coverage Issues with Hard and Soft Handoff 196
`6.5.1 Hard Handoff 196
`
`6.5.2 Soft Handoff 198
`
`6.6 Erlang Capacity of Reverse Links 199
`6.6.1 Erlang Capacity for Conventional Assigned—Slot Multiple
`Access 199
`
`6.6.2 Spread Spectrum Multiple Access Outage—Single Cell and
`Perfect Power Control 203
`
`6.6.3 Outage with Multiple-Cell Interference 207
`6.6.4 Outage with Imperfect Power Control 208
`6.6.5 An Approximate Explicit Formula for Capacity with
`Imperfect Power Control 212
`6.6.6 Designing for Minimum Transmitted Power 214
`6.6.7 Capacity Requirements for Initial Accesses 215
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`

`Contents
`
`XI
`
`6.7 Erlang Capacity of Forward Links 218
`6.7.1 Forward Link Power Allocation 218
`
`6.7.2 Soft Handoff Impact on Forward Link 222
`
`6.8
`
`6.7.3 Orthogonal Signals for Same-Cell Users 224
`Interference Reduction with Multisectored and Distributed
`Antennas 227
`
`6.9
`
`Interference Cancellation 229
`
`6.10 Epilogue 232
`
`References and Bibliography 235
`
`Index 239
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`

`xviii
`
`Preface
`
`In Chapters 2 to 5, this book covers all aspects of .SPread spectrum
`transmission over a physical multiple-access channel: Signal gerfiegatlo?
`synchronization, modulation, and error—correcting codingl o 1 irec
`sequence spread spectrum signals. Chapter 6 relates these Pp y51ca ayer
`functions to link and network layer properties mvolvmg cellular cover-
`age, Erlang capacity, and network control. This out-line lS unusual in
`bringing together several wide—ranging technical disc1plrnes, rarely cov-
`ered in this sequence and in one text. However, the presentation is well
`integrated by a number of unifying threads. First, the entire text 15 de-
`voted to the concept of universal frequency reuse by multiple users of
`multiple cells. Also, two fundamental techniques are used in a variety of
`different forms throughout the text. The first is the finite-state machine
`representation of both deterministic and random sequences; the second is
`the use of simple, elegant upper bounds on the probabilities of a wide
`range of events related to system performance.
`However, given the focus on simultaneous wideband transmission for
`all users over a common frequency spectrum, the text purposely omits
`two important application areas: narrowband modulation and coding
`methods, including multipoint signal constellations and trellis codes; and
`frequency hopped multiple access, where modulation waveforms are in—
`stantaneously narrowband over the duration of each hop. It also generally
`avoids digressions into principles of information theory. In short, al-
`though the material covered through Chapter 5 mostly also applies to
`narrowband digital transmission systems, the book mainly covers topics
`that apply to WidEband spread spectrum multiple access.
`Three motivating forces drove me to write this book. It began with my
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`

`Pilot—Aided Coherent Mufflpofh Demoduloflon
`
`87
`
`The pilot sequence can be searched by the hypothesis testing device of
`Figure 3.1 with time (delay) hypotheses separated b
`
`tion. The pilot pseudorandom sequence is unmodulated, and the carrier
`frequency is assumed to be accurately tracked. Thus, the number of chips
`used for estimation can be made as large as desired, limited only by the
`rate of change of amplitude and phase. Also, unlike the last chapter where
`the initial acquisition search ended when the correct hypothesis was de-
`tected, the search here will not end. Once a path is detected and verified,
`the search continues indefinitely, since new multipath components will
`appear and old ones disappear frequently, particularly for users in mo—
`tion. Once found, the component sequence timing must be tracked by an
`early—late gate, both to refine the time estimate and to adjust for distance
`and velocity of users in motion.
`We will explore this mechanization more fully. However, we first note
`that whereas the multipath propagation model of Figure 4.1 has long been
`accepted in the communication theory literature, it has been traditionally
`associated with a static receiver, in which it was assumed that each of the
`
`components (and even their number, I.) remained at a constant delay,
`although their amplitudes and phases might vary. Employing a receiver
`that takes a static number of paths, in place of the varying number as—
`sumed here, complicates the form of the optimum receiver: L must gener-
`ally be taken to be larger than if only the Currently active path delays are
`being demodulated. Also, with a static receiver, motion causes a transition
`fTom one delay path to another with possible discontinuity of amplitude
`and phase.
`In the next section we explore the optimum PilOt'aidEd demodulator
`based 0n tracking each multipath component. In the following subsection,
`We consider its performance.
`
`4.4 Pilot-Aided Coherent Multipath
`Demodulation
`A pilot sequence for determining multipath component
`characteristics is
`h as the forward
`WenJlllstified for one-to-many transmission channels, suc
`idem-) link from a base station to multiple users. This is because the
`Saint? pilot sequence is shared among the ku users controlled by that base
`station. For the same reason, the energy devoted to the pilot canlbe grits:
`:lian that deVoted to the individual users. Thus, if Xklf) glven m (:1.
`i)l(1)t
`e receiVEd Signal for the kth user, let Xo(t) be the unmodulate p
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`

`M dulafion and Demodulaflon of Spread Spectrum Signal;
`0
`
`83
`
`native“):
`
`Mulllpalh
`Propagation
`
`Figure 4.2 Multiuser (base station) modulator and multipoth channel.
`
`signal, so that xn(0) = 1 for all 11. Also, we assume that the pilot’s pseudo-
`random sequence is shared by all users by multiplying the pilot pseudo-
`random (: 1) Sequence with all the user-specific sequences (Figure 4-2)-
`Hence, the received signal containing ku users and a pilot sequence, all
`orlglnating from a comxnon base station, will be
`
`Xolt) + g: Xk(t).
`
`k=1
`
`scal
`
`, k“, but X00?) is further
`.
`.
`.
`Here, Xk(t) is given by (4.24) for k = 1, 2,
`Ed by A0, the addmonal gain allotted to the pilot signal-
`sefiilown in Figure 4-1 m0) and new) are the pilot’s QPSK Spreadlgr
`9- The users’ sequences are the product5 of those 0f the p10
`
`.
`
`.
`
`
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`

`Pilot—Aided Coherent Multlporh Demodulofion
`
`B9
`
`and of the user-specific sequences b$,1)(k) and (75,0100. That is
`
`£7906) = at,“(0)bfi”(k),
`
`(£5906) = Hi?)(0)bf9’(k),
`
`k = 1, 2,
`
`.
`
`.
`
`.
`
`, k
`
`sequence.
`The optimum demodulator structure for L multipath propagation
`paths (as assumed in Figure 4.1) is known as a Rake receiver [Price and
`Green, 1958]. It was first implemented in static form in the late 1950s. This
`is shown in Figure 4.3 for the kth user. Figure 4.3a consists of the parallel
`combination of L elements, one of which is shown in Figure 4.3b. Each
`multipath compOnent demodulator is called a ”finger” of the rake. The
`pilot sequence tracking loop of a particular demodulator is started by
`the timing delay estimation of a given path, as determined by the
`pilot’s pseudorandom sequence searcher. This is then used to remove the
`pilot QPSK spreading, giving rise to the quadrature outputs (Figure
`4.3}:
`
`«E [A0 + xi(k)bs.”(k)1ae cos a + v5.1),
`
`4:: [A0 + x.(k)b§e(k)1aesin a + vie.
`
`Ao is the pilot gain, and 12$,” and vi?) are the contributions of all other
`(Uncorrelated) multipath components as well as those of all other users.
`1:me this the relative path values orf cos the and 0’s sin 9b,? can be estimated
`by Simply averaging over an arbitrary number of chips, Np. This number
`ShOUId be as large as possible Without exceeding the period over which a,
`and ¢e rEmain relatively constant.
`The OPfimm (maximum likelihood) demodulator forms the weighted,
`phase'adlus‘kid, and delay-adjusted sum of the L components. This
`amounts to taking the inner product of the modulated received I and Q
`COmPOIIents with the I and Q unmodulated component magmtude esti-
`mates at C05 (3),; and Ere sin (333. The result for the nth chip of the 6th path,
`after mul’fiplication by the quadrature-user-specific pseudorandom se-
`CIllences as show in Figure 43b, is
`
`n k = «Exam (1 COSC¢e ’ 325)
`ye ( )
`+a,(y5,1)ccfs it, + v5?) sin 3»)-
`
`(4.26)
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`

`
`
`
`
`Y(k)
`
`
`\w ‘
`
`
`
`
`
`
`SIDUBISwnuoedspoemsJouomnpowaaPUD'“ollm'flpgw'
`
`
`
`
`
`
`
`
`
`
`
`(i): L-Pa'ih-LDIomédulator
`
`dfh firebqgoflm (a)r;'L'-r3d1hf‘de.quuie*or-
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`

`

`
`
`\ at »
`VE;[A0+xn(k) bna) (k)]c:Lr cos ®+vngn
`
`
`
`
`bn(l)(k)
`bnl0) (k)
`Vial/lawn“) bn(0) (knafsin qw n50)
`/ $
`
`fiISin [at
`
`
`
`————»
`
`ate
`
`
`lnmal
`Pilot
`
`Matched
`ary— ale
`From
`Timing
`(E SleQEenca
`)
`-
`fom ”>
`-
`
`mars
`Trigggg
`Searcher
`4’
`
`
`
`Pilol
`Sequence
`
`a (I) (0),a (0) (0)
`n
`n
`Desp reading
`
`
`
`
`
`(b) Each of L Parallel Demodulators
`(Rake Fingers) for kth User
`
`Figure 4.3 (b) Each of L parallel demodulators (Rake fingers) for k’rh user,
`
`[6
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`

`

`ad Spectrum Signals
`
`Jul
`
`Summing over t
`
`he N chips over which x,,(k) is constant (: 1), We have
`
`k = :WE: araccosm , am
`YA )
`+ Moos (if 2 1sz + sin 31$ Z 1410)].
`
`(4.27)
`
`Thus,
`
`E[Yc(k) | x,,(k) = *1] Z “ NNE; acér cosw’c '" {ball
`
`(4.28:1)
`
`with a change of Sign if x,,(k) = + 1, and
`
`velar/m] : Natro/ 2,
`
`(4.28b)
`
`where ID is given in (4.16).
`We proceed to obtain Chernoff bounds on the error probability using
`the methods of Section 4.2.
`
`4.4.1 Chernott Bounds on Error Probability for Coherent
`Demodulation with Known Path Parameters
`
`Initially, conditioning on known amplitudes are and phases (fie, we obtain
`the Chernoff bound,
`
`PE(or, ¢;k) = Pr [2L1 Y((k) > Ola, ¢,x(k) = - ]
`< MinE (expl:pi ma] 1 a, a, x(k) = —1)
`= Minexr) [-leEak) 2 agar coswnf — a) + pZN 2 (“lilo/4i
`NEc(k) [2 ago.f cos(d)e — 3%)]2
`
`p>0
`
`P>0
`
`L
`
`e:1
`
`L
`
`3‘1
`
`(4.29)
`
`= exp —
`
`
`
`If w
`'
`'
`'
`He neglect the maccuracy 1n the amplitude and phase estimates: takmg
`e — 05:. Die = cue, we obtain
`
`135(k) < exp [— EL: afiNEc(k)/IO:|
`
`8:1
`
`L
`
`(4.30)
`
`= .9111 exp [ _ O‘l’NEclkVIol
`
`(perfect estimates).
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`

`Pilot—Aided Coherent Multipofh Demodulcflon
`
`93
`
`Further, it is shown in Appendix 4A that if we do not assume Exact phase
`'
`t'
`f
`, b t
`‘
`and amplitude es una es
`u rather estimates based on NP unmodulated
`chips of a pilot whose chip energy is AfiEc (see Figure 4.3), the error proba_
`bility is bounded by
`
`L expl- swan/Io]
`PElk) < 61:11W.
`
`(431)
`
`Generally, if the paths are known and the total received energy per chip is
`Ec(k)’ then we may normalize the relative path gains so that
`
`Thus, for fixed amplitude and phase multipath, the performance bound
`with perfect estimates, (4.30), is the same as for a single—component signal,
`if energy is taken as the sum of the component energies. The explanation
`is simple: When the multipath amplitudes and phases are known, the
`optimal receiver operates as a matched filter to the combination of the
`transmitter filter and the (multipath) channel.
`
`4.4.2 Rayleigh and Rician Fading Multipoth Components
`
`Now we no longer assume constant amplitude. We let the multipath com»
`ponent amplitudes be random variables, mutually independent because
`we assume that each path’s attenuation is unrelated to that of all others.
`Then the error probability for perfect estimates becomes
`L
`
`-
`
`-
`
`PE = ElPE(a1I -
`
`I aL)] < E I: H exp(—ar%NEc/Io):|
`
`i=1
`
`L
`L
`= H Elexpeate/Ione H 2,; 2.
`(i=1
`«i=1
`
`(4.32)
`
`Here, E, g NE, is the N—chip symbol energy, and the expectations are with
`resl’eCt t0 the random variables at. We drop the user index k for conve-
`meflce. We also assume perfect estimates, although by scaling all Zf by the
`denominator of (4.31), we may also obtain a bound for imperfect estimates.
`If each COmponent is the combination of many reflections arriving at
`Marty the same delay but with random phases, we can take the a: variable to
`be Rayleigh-dismbuted. Then the probability density function of a, 15
`
`19(0) = 2a elf/"f,
`
`0'5
`
`a > 0,
`
`(4.33a)
`
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`

`94
`
`Modulation and Demodulafion of Spread specmjm Signa’5
`
`Or, letting )3", = (3%, we obtain the ch1-squared denSIty,
`
`P(fi) =
`
`
`e—me
`2
`0':
`
`I
`
`fl > OI
`
`(4‘33b)
`
`_
`7- = 5m 1 = Has.
`h
`W "Phigcfor Rayleigh-distributed attenuations,
`
`=
`
`ze He
`
`_B(Es/Ifl
`
`-_—
`
`E
`—3
`W1
`—— — —-E 2+
`
`1 LagEXPlag ([006 1)}:3
`
`l
`= ___'
`1 + afiES/IO
`
`(4.34)
`
`Letting
`
`this can be written as
`
`E5! = 6755 = 0% Es,
`
`u
`.
`1
`z _
`e —m (RayleLgh fading component).
`
`(4.35)
`
`If the component is the combination of a specular component and a Ray-
`leigh component, the probability density function of at becomes Rician.
`Its square [35 becomes noncentral chi-squared,
`
`e—(IBr + Til/0'3
`Me) = —2— 90(2V7eBe/Ufil-
`0'6
`
`(4.36)
`
`Then
`
`28 = E[g—B¢E,/Iu]
`
`2
`(If
`
`
`
`0%
`
`d 5
`
`2
`
`lp[_fl_w]l(zfvefie
`(4.37)
`) fi/Ut
`
` = 1
`(H veEs/Io
`1 + ”2255/10 exp W) (Rician fading component)-
`angifli: :1: I'Educes l0 the Rayleigh fading result (4.34) when ‘Yc 5 0’
`own amplitude and phase result when 0% = O.
`equal average Strength, so the: L mUltlpath components are all Raylezg
`f
`Pose that th
`-
`
`N t
`
`-
`
`'
`
`h 0
`
`0% = “2
`
`for all 6,
`
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`

`

`Pilot-Aided Coherent Mumpath Demodulofion
`
`95
`
`and therefore, for each component,
`
`Est = UgEs = 02E =
`
`Then, letting the random variable
`
`L
`
`L
`
`x = Z asz5 Z Z IBCESI
`8:1
`e = 1
`
`it is easily shown (see Appendix 3A5) that since the individual fading
`variables are all independent,
`
`xi. — le—x/EI
`
`”“0 = (—T
`
`(4.38)
`
`which is Lth—order chirsquared. It follows from (4.34) that, in this case,
`
`FZLlelllle
`E< UUI
`e
`1+(o-2Es/Io)
`1+(E5/l’0)
`(
`
`.
`
`)
`
`A
`
`— —— =
`
`-—_— .
`
`We may rewrite (4.39) as
`
`where
`
`E < exp[—ln(1/Z)],
`
`ln(1/Z) = L ln[1 + (Es/Ion.
`
`(4.40)
`
`From (4.40) we obtain Figure 4.4: a plot of the ratio6 of the total average
`Symbol energy—to—interference density LES/I0 over that required for an
`unfaded GauSsian channel to achieve a given exponent value, 111(1 /Z).
`Note from (4.9) or (4.32) that for the latter channel, 111(1/2) = FS/Io- Thus,
`this is the average excess energy (in decibels) required by thlS degraded
`Channel to achieve the same performance as for an unfaded Signal in
`additive Gaussian noise.
`
`\‘___________
`
`6 All ‘lllantifies are in decibels and hence are logarithmic functions. Thus,
`the excess energy, in decibels, required for the faded channel over that requ
`wad“ AWGN channel.
`
`this ratio is actually
`ired for the
`
`
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`

`

`96
`
`Modulation and Demodulofion of Spread SpectrUm Signals
`
`Exponent In (112) (dB)
`
`
`
`
`
`EE
`
`Z ‘
`
`3’('uD'D
`EI:
`
`DB3 EDC
`
`LIJ
`
`38)
`
`1
`Lu
`3»E
`g4:
`
`Figure 4.4 Required excess energy (dB) for L equal—strength multipoth fading
`relative to unfoded coherent AWGN.
`
`Note that as L —) 00 (so that each component’s average energy E_-s—>0,
`but LE5 is finite), the bound approaches
`
`PE < e-LEs/[Of
`
`so that the excess energy approaches zero. This shows that with an
`asymptotically large number of independent Rayleigh components/P6P
`formance approaches that of unfaded propagation. This is an extreme
`and unrealistic example of the beneficial effect of independent diversiW
`components. We shall return to these results in Chapter 5 when we
`Consider interleaving, With delay, to produce more independent com-
`ponents.
`
`4.5 Noncoherent Reception
`
`
`
`|PR2018—01474
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`

`

`Multiple Cell Pilot Tracking and Soft Hand ff
`
`o
`
`1
`
`83
`
`
`
`ration may be estimated a priori to lie between 3 and 7 d
`B, according to
`5 ea“alyses in chapters 4 and 5. However, conditions Will
`Vary according
`lo the mulfipath fading. envn‘onrnent, particularly if man
`y paths are in—
`\rolved- Thus, as noted in Section 4.7, it IS useful to add a power Control
`mechanism called an outer loop, which adjusts the desired Eb/I0 level
`according to the 1nd1v1dual user's error rate measured at
`the base
`station This then guarantees a given error rate per coded voice frame or
`message packet (typically‘set at or below 1%). However, the resulting
`lib/lo parameter, which 15 already a log-normal random variable_
`or normal in decibels—because of power control inaccuracy, will have
`greater variability, manifested as a larger standard deviatiOn of its
`normally distributed decibel measure. Thus, while Section 4.7 arrives
`ata typical standard deviation for the closed—loop system between 1_1
`and 1.5 dB, the standard deviation caused by the outer loop variations
`is of the same order of magnitude. Hence,
`the combination of these
`two independent components leads to an estimate of total standard
`deviation on the order of 1.5 to 2.1 dB. It has been measured experimen-
`tally [Viterbi and Padovani, 1992; Padovani, 1994] to be between 1.5
`and 2.5 dB. We shall assess the effect of variability on capacity in Sec-
`tion 6.6.
`
`6.3 Multiple Cell Pilot Tracking and Soft Hondofi
`
`The forward link for each cell or sector generally employs a pilot modu-
`lated 0111)! by the cell—specific, or sector-specific, pseudorandom sequence,
`added or multiplexed with the voice or data traffic. This is described in
`Chapter 4 and shown in Figure 4.2. The pilot provides for time reference
`and phase and amplitude tracking. It also can be used to identify DEWIY
`fWailable Pilots in adjacent cells or sectors. Specifically, while a user
`Bhatking the pilot of a particular cell, it can be searching for pilots
`Ufadlacmt cells (using-the searching mechanism of its multiPalth rake
`Wiverl- To make this simple and practical, all Pfiot pseudoran-
`film Sequences can use the same maximum length generator sequencer
`illlth diffEEIent initial vectors and hence timing offsets. The “Blame
`e-offsets 0f Pilots for neighboring cells and sectors are either kIIOWtI;
`apnori Or brOiiclcast to all users of the given cell or sector on a separa
`
`511301109}, Performlance. One simple method is to puncture (599
`. mhequentiy (9-8.: one symbol in 12) and dediCate the p
`d in rate (es-r
`3315530“ 0f Commands. The punctured code is then redufie t1
`y degraded.
`2 If one in 12 Symbols is punctured). Its performance 15 s Eh
`
`A!
`
`|PR2018—01474
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`

`

`84
`
`1
`
`C (7ch Coverage and Control of spread spectrum Multiple Access Networks
`an
`-
`'
`
`CDMA channel, employing its own pseudorandom sequence or time-
`t.
`Offgence a new Pilot is detected by the searcher and found to have suffi-
`cient signal strength (usually relative to the first pilot already beling
`tracked), the mobile will signal this event to its original base station.
`This in turn will notify the switching center, Wthh enables the second
`cell’s base station to both send and receive the same traffic to and from
`the given mobile. This process is called soft flflIIdOfiIFOI‘ forward link
`transmission to the mobile, the Rake demodulator (Figure 4.3) demod—
`ulates both cells’ transmission in two fingers of the rake and combines
`them coherently, with appropriate delay adjustments, Just as is done
`for time-separated multipath components. For the reverse llnk, nor-
`mally each base station demodulates and decodes each frame or packet
`independently. Thus, it is up to the switching center to arbitrate be-
`tween the two base stations’ decoded frames.2 Soft handoff operation
`has many advantages. Qualitatively,
`transition of a mobile between
`cells is much smoother: The second cell can be brought into use gradu—
`ally, starting early in the transition of a mobile from one cell
`to its
`neighbor cell. Similarly, when the first cell’s signal is so weak relative
`to the second that it cannot be demodulated and decoded correctly, it
`will be dropped either in response to the mobile’s pilot strength mea-
`surement or by action of the first cell. Moreover, for any given frame,
`the better cell’s decision will generally be used, with no need to enable a
`new cell or disable an old one as in classical ”hard” handoff. In fact, to
`avoid frequent handoffs 0n the boundary between cells (which reqUiI'e
`excessive control signaling), systems with hard handoff only enable
`a second cell when its signal strength is considerably above (es-r
`6 dB) that of the first cell. This further degrades performance on the
`boundary.
`Most importantly, however, soft handoff considerably increases both
`the capacity of a heavily loaded multicellular system and the coverage
`(area size) of each individual cell in a lightly loaded system. We shall
`demonstrate this quantitatively, following Viterbi, Viterbi, Gilhousen, and
`Zehavi [1994]. It is first necessary to determine the mutual interferenCe
`among cells of a multicellular system.
`
`R2
`
`Generally, each frame is provided with an error-
`detecting code (consisting 01: a modem:
`number, c, of check bits at the tail end of
`the frame) which allows detection of one 01' m0
`errors with probability on the order of 1—-
`2"E [Wolf et (11., 1982].
`
`|PR2018—01474
`
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`

`

`Electrical Engineering/Telecommunications
`CDMA
`Principles of Spread Spectrum Communication
`
`
`
`Spread spectrum multiple access communication, known commercially as CDMA
`(Code Division Multiple Access), is a driving technology behind the rapidly advancing
`personal communications industry. Its greater bandwidth efficiency and multiple
`access capabilities make it the leading technology for relieving spectrum congestion
`caused by the explosion in popularity of cellular mobile and fixed wireless telephones
`and wireless data terminals.
`
`CDMA has been adopted by the Telecommunications Industry Association
`(TIA) as a wireless standard. As an electrical or communications engineer, you
`must acquire a thorough grasp of CDMA fundamentals in order to develop systems,
`products, and services for this demanding but rewarding market.
`Written by a leader in the creation of CDMA and an internationally recognized
`authority on wireless digital communication, this book gives you the technical
`information you need. It presents the fundamentals of digital communications and
`covers all aspects of commercial direct-sequence spread spectrum technology,
`incorporating both physical-level principles and network concepts. You will find
`detailed information on signal generation, synchronization, modulation, and
`coding of direct-sequence spread spectrum signals. In addition, the book shows
`how these physical layer functions relate to link and network properties involving
`cellular coverage, Erlang capacity, and network control.
`With this book, you will attain a deeper understanding of personal commu-
`nications system concepts and will be better equipped to develop systems and
`products at the forefront of the personal wireless communications market.
`Andrew J. Viterbi is a pioneer of wireless digital communications technology.
`He is best known as the creator of the digital decoding technique used in direct-
`broadcast satellite television receivers and in wireless cellular telephones, as
`well as numerous other applications. He is co—founder, Chief Technical Officer,
`and Vice Chairman of QUALCOMM Incorporated, developer of mobile satellite
`and wireless land communication systems employing CDMA technology.
`Dr. Viterbi has received numerous awards, including the Christopher Columbus
`Medal, the IEEE Alexander Graham Bell Award, the Marconi International
`Fellowship Award, the IEEE Information Society Shannon Lecturer Award, and
`awards from the NEC C&C Foundation and the Eduard Rhein Foundation.
`
`h—hI
`
`x001 DMDSKJ
`
`Cover photo © Hewlett—Packard Compan:
`Cover design by Simone R. Payment
`aText printed on recycled paper
`Corporate & Professmnal Publishing Group
`v‘v Addison-Wesley Publishing Company
`
`CDMA: PRINCIPLES OF SPREAD SPECT
`Use‘i 600d
`,
`
`. vucu . mu. -.u
`I S B N D _ E [I L _ l: 3 3 7 ll _ Ll
`
`r.~
`
`‘"
`
`|PR2018—01474
`
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`
`