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Systematic Modeling and Analysis of Telecom Frontends and their Building Blocks 2005 ed. [Kõva köide]

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nalog circuits are fascinating artifacts. They manipulate signals whose informa- Ationcontentisrichcomparedtodigitalsignalsthatcarryminimalamountofinf- mation;theyaredelicateinthatanyperturbationduetoparasiticelements,todelays,to interactionswithotherelementsandwiththeenvironmentmaycauseasigni cantloss ofinformation. Thedif cultyindealingwiththeseartifactsistoprotectthemfromall possibleattacks, evenminorones, fromthephysicalworld. Theironyisthattheyare oftenusedtofunnelinformationfromandtothephysicalworldtoandfromtheabstr- tionofthedigitalworldandforthisfunction, theyareirreplaceable. Nowonderthen that analog designers form a club of extraordinary gentlemen where art (or magic?) ratherthanscienceisthesharedtrade. Theyaredif culttotrainsinceexperienceand intuitionarethetraitsthat characterize them. Andthey have dif cultiesinexplaining what is the process they use to reach satisfactory results. Tools used for design (s- ulation) are mainly replacing the test benches of an experimental lab. However, the growing complexity of the integrated systems being designed today together with the increasing fragility of analog components brought about by shrinking geometries and reducedpowerconsumptionisposingseverechallengestotraditionalanalogdesigners to produce satisfactory results in a short time. At the same time, the need for expe- enced analog designers has increased constantly since almost all designs, because of integration,docontainanalogcomponents. Thissituationhascreatedastronginterest in developing design methodologies and supporting tools that are based on rigorous, mathematically literate, approaches. Doing so will make it possible to leverage the expertiseofseasonedanalogdesignersandtotrainnewgenerationsfasterandbetter. Inthepast, severalattemptshavebeenmadeinacademia andindustrytocreatethese methodologies and to extend the set of tools available. They have had questionable acceptance in the analog design community. However, recently, a ?urry of start-ups andincreasedinvestmentbyEDAcompaniesinnoveltoolssignalasigni cantchange inmarketattentiontotheanalogdomain. Ipersonallybelievethattosubstantially- prove quality and design time, tools are simply insuf cient. A design methodology based on a hierarchy of abstraction layers, successive re nement between two ad- cent layers, and extensive veri cation at every layer is necessary. To do so, we need to build theories and models that have strong mathematical foundations. The analog design technology community is as strong as it has ever been.

Arvustused

"This book has a good tutorial dimension. In particular, the idea of describing in plain words the essence of the approaches before diving into the mathematical details, makes reading this book a pleasant experience without sacrificing precision and rigor."



Professor Alberto Sangiovanni-Vincentelli

Foreword vii
Contributing Authors ix
Contents xi
Symbols and Abbreviations xvii
Introduction
1(10)
Structured analysis, a key to successful design
1(5)
Electronics, a competitive market
1(1)
Analog design: A potential bottleneck
2(1)
Structured analog design
3(2)
Structured analysis
5(1)
This work
6(3)
Main contributions
7(1)
Math, it's a language
8(1)
Outline of this book
9(2)
Modeling and analysis of telecom frontends: basic concepts
11(16)
Models, modeling and analysis
11(9)
Models: what you want or what you have
12(2)
Good models
14(1)
The importance of good models in top-down design
15(2)
Modeling languages
17(1)
Modeling and analysis: model creation, transformation and interpretation
17(3)
Good models for telecommunication frontends: Architectures and their behavioral properties
20(5)
Frontend architectures and their building blocks
20(1)
Properties of frontend building block behavior
21(4)
Conclusions
25(2)
A framework for frequency-domain analysis of linear periodically time-varying systems
27(52)
The story behind the math
28(6)
What's of interest: A designer's point of view
28(1)
Using harmonic transfer matrices to characterize LPTV behavior
29(1)
LPTV behavior and circuit small-signal analysis
30(4)
Prior art
34(3)
Floquet theory
34(2)
Lifting
36(1)
Frequency-domain approaches
36(1)
Contributions of this work
37(1)
Laplace-domain modeling of LPTV systems using Harmonic Transfer Matrices
37(14)
LPTV systems: implications of linearity and periodicity
38(3)
Linear periodically modulated signal models
41(5)
Harmonic transfer matrices: capturing transfer of signal content between carrier waves
46(2)
Structural properties of HTMs
48(2)
On the ∞-dimensional nature of HTMs
50(1)
Matrix-based descriptions for arbitrary LTV behavior
51(1)
LPTV system manipulation using HTMs
51(9)
HTMs of elementary systems
51(2)
HTMs of LPTV systems connected in parallel or in series
53(1)
Feedback systems and HTM inversions
54(4)
Relating HTMs to state-space representations
58(2)
LPTV system analysis using HTMs
60(18)
Multi-tone analysis
61(1)
Stability analysis
61(8)
Noise analysis
69(9)
Conclusions and directions for further research
78(1)
Applications of LPTV system analysis using harmonic transfer matrices
79(56)
HTMs in a nutshell
79(3)
Phase-Locked Loop analysis
82(31)
PLL architectures and PLL building blocks
83(1)
Prior art
84(3)
Signal phases and phase-modulated signal models
87(4)
HTM-based PLL building block models
91(8)
PLL closed-loop input-output HTM
99(4)
Example 1: PLL with sampling PFD
103(8)
Example 2: PLL with mixing PFD
111(1)
Conclusions
112(1)
Automated symbolic LPTV system analysis
113(21)
Prior art
113(2)
Symbolic LPTV system analysis: outlining the flow
115(1)
Input model construction
115(2)
Data structures
117(1)
Computational flow of the SymbolicHTM algorithm
118(4)
SymbolicHTM: advantages and limitations
122(1)
Application 1: linear downconversion mixer
122(6)
Application 2: Receiver stage with feedback across the mixing element
128(6)
Conclusions and directions for further research
134(1)
Modeling oscillator dynamic behavior
135(62)
The story behind the math
136(8)
Earth: a big oscillator
136(1)
Unperturbed system behavior: neglecting small forces
137(1)
Perturbed system behavior: changes in the earth's orbit
138(2)
Averaging: focusing on what's important
140(2)
How does electronic oscillator dynamics fit in?
142(1)
Modeling oscillator behavior
142(2)
Prior art
144(4)
General theory
144(1)
Phase noise analysis
144(2)
Numerical simulation
146(1)
Contributions of this work
146(2)
Oscillator circuit equations
148(4)
Normalizing the oscillator circuit equations
149(1)
Partitioning the normalized circuit equations
150(2)
Characterizing the oscillator's unperturbed core
152(3)
Oscillator perturbation analysis
155(7)
Components of an oscillator's perturbed behavior
155(2)
Motion xs (τ, p(τ)) over the manifold M
157(3)
In summary
160(2)
Averaging
162(8)
Oscillator phase (noise) analysis
170(10)
Capturing oscillator phase behavior
171(1)
Practical application: oscillator injection locking
172(2)
Averaging in the presence of random perturbations
174(4)
Practical application: computing oscillator phase noise spectra
178(2)
Harmonic oscillator behavioral modeling
180(15)
Model extraction theory
181(5)
Numerical computations
186(1)
Experimental results
187(8)
Conclusions and directions for further research
195(2)
Conclusions
197(4)
Main achievements
197(2)
HTM-based LPTV system analysis
198(1)
Modeling oscillator dynamic behavior
199(1)
Leads for further work
199(2)
A HTM norms and the comparison of HTMs
201(4)
A.1 Operator norms and the comparison of operators
201(1)
A.2 Selecting the set of test inputs
202(1)
A.3 Expressing LPTV operator norms in terms of the corresponding HTM elements
202(2)
A.4 Conclusions
204(1)
B The Sherman-Morisson-Woodbury formula
205(2)
C HTM elements of the linear downconversion mixer
207(4)
D Oscillator dynamics: analysis of the deviation from the attracting manifold
211(6)
D.1 Components of the deviation Δx(τ)
211(1)
D.2 Behavior of Δx2(τ)
212(2)
An expression for Δx2(τ)
212(1)
Boundedness of Δx2(τ)
213(1)
D.3 The behavior of Δx3(τ)
214(1)
D.4 Conclusions
215(2)
E Analysis of a harmonic oscillator
217(4)
E.1 Determining the oscillator's averaged dynamics
217(3)
E.2 Phase behavior near operating point
220(1)
E.3 Conclusions
220(1)
Bibliography 221