Achieve accurate and reliable parameter extraction using this complete survey of state-of-the-art techniques and methods. A team of experts from industry and academia provides you with insights into a range of key topics, including parasitics, intrinsic extraction, statistics, extraction uncertainty, nonlinear and DC parameters, self-heating and traps, noise, and package effects. Learn how similar approaches to parameter extraction can be applied to different technologies. A variety of real-world industrial examples and measurement results show you how the theories and methods presented can be used in practice. Whether you use transistor models for evaluation of device processing and you need to understand the methods behind the models you use, or you want to develop models for existing and new device types, this is your complete guide to parameter extraction.
Author(s): Matthias Rudolph, Christian Fager, David E. Root
Series: Cambridge RF and Microwave Engineering Series
Edition: 1
Publisher: Cambridge University Press
Year: 2011
Language: English
Pages: 368
Tags: Приборостроение;Полупроводниковые приборы;Транзисторы;
Cover......Page 1
Nonlinear Transistor Model Parameter Extraction Techniques......Page 3
The Cambridge RF and Microwave Engineering Series......Page 4
Title......Page 5
Copyright......Page 6
Contents......Page 9
List of contributors......Page 12
Preface......Page 15
1 Introduction......Page 17
1.1.1.1 Circuit application......Page 18
1.1.1.2 Measurement uncertainty......Page 22
1.1.1.3 Process variations......Page 24
1.1.2 Numerical convergence......Page 25
1.1.2.1 Breakdown......Page 26
1.1.2.2 Self-heating......Page 27
1.1.3 Choice of the modeling transistor......Page 29
1.2 Model extraction workflow......Page 31
References......Page 33
2.1 Introduction......Page 34
2.2 Basic DC characteristics......Page 35
2.3 FET DC parameters and modeling......Page 37
2.4 HBT DC parameters and modeling......Page 41
2.5 Process control monitoring......Page 43
2.6 Thermal modeling overview......Page 44
2.7 Physics-based thermal scaling model for HBTs......Page 47
2.8 Measurement-based thermal model for FETs......Page 48
2.9 Transistor reliability evaluation......Page 52
Acknowledgments......Page 56
References......Page 57
3.2 Test structures with calibration and de-embedding......Page 59
3.3.1 Equivalent circuit topology......Page 65
3.3.2 Physical description of contact resistances and overlap capacitances......Page 66
3.3.3 Extrinsic resistance and inductance extraction......Page 69
3.4.1 Cold FET technique......Page 76
3.4.2 Unbiased technique......Page 80
3.4.3 GaN HEMTs exceptions......Page 82
3.5 Scaling for multicell arrays......Page 88
References......Page 99
4.1.1 Sources of uncertainty in modeling......Page 102
4.1.2 Measurement uncertainty......Page 103
4.2.1 Simple direct extraction example......Page 104
4.2.1.2 Uncertainty analysis......Page 105
4.2.1.3 Parameter estimation......Page 108
4.2.2.1 Uncertainty contributions......Page 109
4.2.2.2 Intrinsic model parameter sensitivities......Page 110
4.2.2.3 Intrinsic model parameter uncertainties......Page 111
4.2.2.4 Multibias extraction results......Page 112
4.3 Optimizer-based estimation techniques......Page 113
4.3.1.1 Simple example......Page 114
4.3.2 MLE of small-signal transistor model parameters......Page 116
4.3.2.1 Parasitic parameter estimation......Page 117
4.3.2.2 Application to parasitic FET model extraction......Page 118
4.3.2.3 MLE of intrinsic model parameters......Page 121
4.3.3 Comparison between MLE and the direct extraction method......Page 123
4.3.4 Application of MLE in RF-CMOS de-embedding......Page 126
4.3.4.1 Method description......Page 127
4.3.4.2 Example using 130 nm RF-CMOS measurements......Page 128
4.3.4.3 Comparison between different de-embedding methods......Page 129
4.3.5 Discussion......Page 130
4.4.1 Finding an optimum model topology......Page 132
4.4.2.1 MSE estimation procedure......Page 133
4.4.2.2 Results......Page 134
References......Page 136
5.2.1 Intrinsic and extrinsic elements......Page 139
5.2.2 The intrinsic nonlinear model: dynamics, constitutive relations, and parameter values......Page 141
5.2.4 Scaling with frequency and geometry......Page 142
5.3.2 Properties of well-defined constitutive relations......Page 143
5.3.3 Regularizing poorly defined constitutive relations: an example......Page 144
5.3.5 Comments on optimization-based parameter extraction......Page 145
5.4.1 Nonlinear re-referencing for table-based models......Page 146
5.4.2 Issues with table-based models......Page 147
5.5 Models based on artificial neural networks (ANNs)......Page 151
5.6 Extrapolation of measurement-based models......Page 153
5.7 Charge modeling......Page 155
5.7.1 Measurement-based approach to charge modeling......Page 156
5.7.2 Constructing model nonlinear charges from small-signal data......Page 161
5.7.4 Practical considerations for nonlinear charge modeling......Page 162
5.7.5 Charge functions from adjoint ANN training......Page 163
5.7.6 Transcapacitances and energy conservation......Page 164
5.7.7 Capacitance-based nonlinear models and their consequences......Page 168
5.8.1 Measurement-based HBT models......Page 169
5.8.3 Delay and diffusion capacitance in physically based and empirical III–V HBT models......Page 170
5.9 FET modeling in terms of a drift charge concept......Page 172
5.10 Parameter extraction of compact models from large-signal data......Page 174
5.10.1 Identification of advanced FET models from large-signal NVNA data......Page 176
References......Page 182
6.1 Introduction......Page 187
6.2 Thermal modeling......Page 191
6.3 EM simulation......Page 194
6.3.1 Geometry of package and simulated structure......Page 195
6.3.2 The internal ports......Page 197
6.3.3 The bondwires......Page 199
6.3.4 Discretization of the package......Page 201
6.4 Equivalent-circuit package model......Page 203
6.4.1 Analytic parameter extraction strategy......Page 206
6.4.1.1 Lead inductance and capacitance......Page 208
6.4.1.2 Bondwire and spreading inductances......Page 209
6.4.1.3 Mutual inductances of gate and drain bondwires......Page 212
6.4.1.4 Feedback mutual inductances......Page 215
6.4.2 Deriving a lumped package model......Page 216
6.4.3 Testing the model......Page 218
References......Page 220
7.1 Introduction......Page 222
7.2.1 Electrothermal model extraction......Page 223
7.2.2.1 Definition of the thermal admittance......Page 227
7.2.2.2 Model-order reduction......Page 228
7.2.2.3 Implementation and equivalent circuit......Page 229
7.3 Trapping effects......Page 231
7.3.1 Physical mechanisms of trapping effects in power FETs......Page 233
7.3.1.1 Drain-lag (DL) effects......Page 235
7.3.1.2 Gate-lag (GL) effects......Page 237
7.3.2 Pulsed-IV characterizations for the trapping effects quantification and FETs modeling......Page 238
7.3.2.1 Trapping effects quantification......Page 239
7.3.2.2 Measurement issues......Page 240
7.3.2.3 Characterizations for nonlinear modeling......Page 244
7.3.3.1 Overview of the published models......Page 245
7.3.4 Parameter extraction......Page 254
7.3.5 Improvements in transistor model accuracy......Page 256
7.4 Characterization tools......Page 259
7.4.1.1 I–V measurements......Page 260
7.4.1.2 Pulsed S-parameter measurements......Page 261
7.4.2.1 Frequency domain load pull measurements......Page 262
7.4.2.2 Time-domain load-pull (TDLP) waveform measurements......Page 263
7.5 Conclusions......Page 265
References......Page 266
8.1 Introduction......Page 273
8.2.1 Linear versus nonlinear microwave measurements......Page 274
8.2.2 De-embedding......Page 275
8.3 Measurements for linear model construction......Page 280
8.4 Measurements for model validation......Page 282
8.4.1 Linear model validation......Page 283
8.4.2 Nonlinear model validation......Page 285
8.5.1 Time-domain measurements-based model construction......Page 290
8.5.2 Frequency domain measurements-based model construction......Page 296
References......Page 300
9.1 Introduction......Page 303
9.2.1.1 Physics-based “unified” modeling......Page 305
9.2.1.2 DOE circuit simulation......Page 306
9.2.1.3 High-level single-tool integration and implementation......Page 308
Epitaxial wafer parameter selection and impact on PCMs......Page 309
PA module level validation of parameter selection......Page 313
Model parameter selection for statistical simulation......Page 316
Connecting PCM (technology variations) to model parameters using device physics......Page 318
Device model level validation and recentering......Page 319
Module level statistical model validation......Page 321
Numerical performance of DOE implementation compared to MC implementation......Page 323
DOE implementation compared to “sensitivity analysis”......Page 325
Integrated design flow in ADS......Page 327
9.3.2 WCDMA FEM......Page 328
9.4 Summary......Page 330
Acknowledgments......Page 331
References......Page 332
Trademarks......Page 333
10.1.1 Probability distribution function......Page 334
10.1.3 Correlation functions......Page 337
10.1.4 Fourier analysis of fluctuating quantities......Page 338
10.1.5 Noise response of noiseless linear time-invariant circuits......Page 340
10.2.1 Thermal noise......Page 341
10.2.2 Shot noise......Page 343
10.2.3 Low-frequency noise......Page 344
10.3 Noise analysis in linear network theory......Page 347
10.4 Noise measurement setups......Page 352
10.5.1 RF noise extracted using correlation matrices......Page 355
10.5.2 1/f noise sources and 50 Ohm noise measurement......Page 358
References......Page 364
Index......Page 366
