Parameter Extraction and Complex Nonlinear Transistor Models (Microwave)

✍ Scribed by Günter Kompa

• Publisher: Artech House
• Year: 2020
• Tongue: English
• Leaves: 609
• Edition: Unabridged
• Category: Library

✦ Synopsis

All model parameters are fundamentally coupled together, so that directly measured individual parameters, although widely used and accepted, may initially only serve as good estimates. This comprehensive resource presents all aspects concerning the modeling of semiconductor field-effect device parameters based on gallium-arsenide (GaAs) and generative adversarial network (GaN) technology. Metal-semiconductor field-effect transistors (MESFETs), high electron mobility transistors (HEMTs) and heterojunction bipolar transistors (HBTs), their structures and functions, and existing transistor models are also classified. The Shockley model is presented in order to give insight into semiconductor field-effect transistor (FET) device physics and explain the relationship between geometric and material parameters and device performance. Extraction of trapping and thermal time constants is discussed. A special section is devoted to standard nonlinear FET models applied to large-signal measurements, including static-/pulsed-DC and single-/two-tone stimulation. High power measurement setups for signal waveform measurement, wideband source-/load-pull measurement (including envelope source-/load pull) are also included, along with high-power intermodulation distortion (IMD) measurement setup (including envelope load-pull). Written by a world-renowned expert in the field, this book is the first to cover of all aspects of semiconductor FET device modeling in a single volume.

✦ Table of Contents

Parameter Extraction and Complex
Nonlinear Transistor Models
Contents
Preface
Chapter 1 Introduction
REFERENCES
Chapter 2
Transistor Concepts: MESFET, HEMT, and HBT
2.1 INTRODUCTION
2.2 EVOLUTION OF FET DEVICES
2.2.1 Field-Effect Transistors
2.2.2 Heterojunction Bipolar Transistors
2.3 BASIC DEVICE STRUCTURES AND FUNCTIONING
2.3.1 MESFET
2.3.2 HEMT
2.3.3 HBT
2.5 SUMMARY
REFERENCES
Chapter 3
Classification of Transistor Models
3.1 INTRODUCTION
3.2 PHYSICAL MODELS
3.2.1 Numerical Physical Models
3.2.2 Analytical Physical Models
3.3 EMPIRICAL MODELS
3.4 EXPERIMENTAL MODELS
3.5 BEHAVIORAL MODELS
3.5.1 ANN-Based Models
3.5.2 X-Parameter-Based Models
3.6 SUMMARY
REFERENCES
Chapter 4 Classical Shockley Model and Enhanced Modifications
4.1 INTRODUCTION
4.2 LONG-CHANNEL (SHOCKLEY) MODEL
4.3 EXPERIMENTAL AND ANALYTICAL v(E)-CHARACTERISTICS
4.4 IMPROVED SHOCKLEY MODEL INCLUDING CARRIER VELOCITY SATURATION
4.5 TWO-REGION MODEL
4.6 SHORT-CHANNEL SATURATION MODEL
4.7 RELATIONSHIPS BETWEEN MESFET AND HEMT DC CHARACTERISTICS
4.7.1 Transconductance
4.7.2 Gate-Source Capacitance
4.7.3 MESFET and HEMT Transconductance Comparison
4.8 PROBLEMS AND SOLUTIONS
4.9 SUMMARY
REFERENCES
Chapter 5 Extrinsic Transistor Network at DC
5.1 INTRODUCTION
5.2 INTRINSIC CONTROL VOLTAGES FROM RESISTIVE NETWORK DE-EMBEDDING
5.3 REGRIDDING OF NONORTHOGONAL INTRINSIC VOLTAGES
5.4 REGRIDDING ISSUES WITH MATLAB
5.5 SUMMARY
REFERENCES
Chapter 6 Estimation of Model Element Values Based on
Device Physical Data
6.1 INTRODUCTION
6.2 RESISTANCES
6.2.1 Ohmic Contact Resistance
6.2.2 Series Resistances
6.2.3 Gate Resistance, Gate Inductance
6.2.4 Gate Charging Resistance
6.3 CONDUCTANCES
6.3.1 Transconductance
6.3.2 Channel Conductance
6.4 CAPACITANCES
6.4.1 Gate-Source Capacitance
6.4.2 Gate-Drain Capacitance
6.4.3 Drain-Source Capacitance
6.5 DELAY TIME
6.6 CONTACT AND INTERCONNECT STRUCTURES
6.6.1 Device Contacting Pads
6.6.2 Bondwire Inductance
6.6.3 Via Hole Inductance
6.6.4 Air Bridge
6.6.5 Field Plate
6.7 SUMMARY
REFERENCES
Chapter 7 Small-Signal Transistor Model Complexity
7.1 INTRODUCTION
7.2 SMALL-SIGNAL TRANSISTOR OPERATION
7.2.1 Two-Port Y-Matrix Transistor Model
7.2.2 Generic Extrinsic Transistor Pi-Model
7.3 TRANSISTOR MODEL COMPLEXITY
7.3.1 Small-Periphery Devices
7.3.2 Large-Periphery Devices
7.3.3 High-Resistivity Silicon Substrates
7.4 SUMMARY
REFERENCES
Chapter 8 Reliable Parameter Estimates from Low-Frequency
Measurements
8.1 INTRODUCTION
8.2 DETERMINATION OF GENERIC PI-MODEL PARAMETERS
8.2.1 Generic Transconductance and Output Conductance
8.2.2 Generic Capacitances
8.3 RELATIONS BETWEEN GENERIC AND PHYSICS-BASED PARAMETERS
8.4 APPROXIMATE DETERMINATION OF PHYSICS-BASED INTRINSIC ELEMENTS FROM GENERIC MODEL PARAMETERS
8.4.1 Output Conductance G
8.4.2 Transconductance G
8.4.3 Gate-Source Capacitance C
8.4.4 Gate-Drain Capacitance C
8.4.5 Drain-Source Capacitance C
8.5 ESTIMATION OF PHYSICS-BASED PARAMETERS FROM
LOW-FREQUENCY S-PARAMETERS
8.6 SUMMARY
REFERENCES
Chapter 9 Static-/Pulsed-DC Measurements for the Analysis of
Thermal and Trapping Effects
9.1 STATIC-DC MEASUREMENTS
9.1.1 Principal DC IV Characteristics and Definitions
9.1.2 Measured DC IV Characteristics
9.1.3 Thermal Resistance from DC Measurements
9.2 PULSED-DC MEASUREMENTS
9.2.1 Implementation of Measurements
9.2.2 Instability Stabilization Techniques
9.2.3 Choice of Quiescent Bias Points
9.2.4 Self-Heating Effects
9.3 THERMAL RESISTANCE EXTRACTION
9.3.1 Pulsed-DC IV Isothermal Curves Overlapping
9.3.2 Pulsed-DC IV and Static-DC Crossing
9.4 TRANSIENTS
9.4.1 Thermal Time Constants
9.4.2 Trapping Time Constants
9.5 THERMAL MODEL
9.6 TRAPPING SUBCIRCUIT
9.7 SUMMARY
REFERENCES
Chapter 10 Vector Network Analyzer:Operation Principle and Error Models
10.1 INTRODUCTION
10.2 EVOLUTION OF THE VECTOR NETWORK ANALYZER
10.3 VECTOR NETWORK ANALYZER CONSTRUCTION AND OPERATION
10.4 ERROR-CORRECTED MEASUREMENTS
10.4.1 Error Models
10.4.2 Calibration
10.5 SUMMARY
REFERENCES
Chapter 11 Uncertainties in the Device Modeling Process
11.1 Introduction
11.2 DEFINITION OF MEASUREMENT TERMS
11.2.1 Uncertainty
11.2.2 Measurement Errors
11.2.3 System Calibration
11.2.4 Accuracy
11.2.5 Precision
11.2.6 Repeatability
11.2.7 Reproducibility
11.2.8 Reliability
11.2.9 Validity
11.2.10 Blunders
11.3 ACCURATE MEASUREMENTS: A KEY CONDITION FOR
SUCCESSFUL DEVICE MODELING
11.3.1 Importance of Diligent System Calibration
11.3.2 Device Measurement Analysis Issues
11.3.3 Choice of Model Topology Complexity
11.3.4 Challenges in the Parameter Extraction Process
11.3.5 Challenges of Consistency in Device Modeling
11.3.6 Model Implementation into Circuit Simulator
11.4 EXTRACTION STRATEGY RECOMMENDATIONS
11.4.1 Check of Measured Data
11.4.2 Choice of Topology
11.4.3 Choice of Extraction Algorithm
11.5 SUMMARY
REFERENCES
Chapter 12
Optimization Methods for Model Parameter Extraction
12.1 INTRODUCTION
12.2 LOCAL MINIMUM PROBLEM
12.3 OPTIMIZATION STRATEGIES
12.4 DESCENT METHODS
12.4.1 Steepest Descent Method
12.4.2 Newton´s Method
12.4.3 Davidon-Fletcher-Powell Method
12.5 NONLINEAR LEAST-SQUARES DATA FITTING
12.5.1 Gauss-Newton Method
12.5.2 Levenberg-Marquardt Method
12.6 DIRECT SEARCH METHODS
12.6.1 Hook-Jeeves
12.6.2 Simplex
12.7 GLOBAL OPTIMIZATION
12.7.1 Multistart Methods
12.7.2 Genetic Algorithm
12.7.3 Simulated Annealing
12.7.4 Tree Annealing
12.7.5 Leaping Simplex
12.8 HYBRID OPTIMIZER
12.9 SUMMARY
REFERENCES
Chapter 13
Extraction Methods: An Overview
Chapter 14
All-at-Once Model Parameter Extraction
14.1 INTRODUCTION
14.2 RANDOM SEARCH COMBINED WITH LOCAL OPTIMIZER
14.2.1 Measurement Bandwidth Variation
14.2.2 Measurement Error Simulation
14.3 SEARCH SPACE MINIMIZATION
14.4 REDUCTION OF OPTIMIZATION VARIABLES
14.4.1 Interrelation of Intrinsic and Extrinsic Model Elements
14.4.2 Gate Resistance Allocation to the Intrinsic Elements
14.5 LINEAR RELATIONSHIP AMONG SERIES RESISTANCES
14.6 SUMMARY
REFERENCES
Chapter 15 Decomposition-Based Extraction Methods
15.1 INTRODUCTION
15.2 EMPIRICAL DECOMPOSITION
15.3 AUTOMATIC DECOMPOSITION BASED ON SENSITIVITY ANALYSIS
15.3.1 Principal-Component Sensitivity Analysis
15.3.2 Sensitivity Analysis by Hessian Matrix Diagonalization
15.3.3 Scaling of Variables for Condition Number Adjustment
15.3.4 Decomposition Optimization in Transformed Model Space
15.3.5 Decomposed Optimization of Individual Parameters
15.4 SUMMARY
REFERENCES
Chapter 16 Bidirectional Search Method
16.1 INTRODUCTION
16.2 BIDIRECTIONAL SEARCH STRATEGY
16.3 DEFINITION OF OBJECT FUNCTION
16.3.1 Extrinsic Data Fitting
16.3.2 Intrinsic Data Fitting
16.4 BIDIRECTIONAL SEARCH OPERATION
16.4.1 Starting Vector Analysis at Pinch-Off
16.4.2 Default Starting Vector
16.5 MULTIBIAS EXTRACTION
16.5.1 Three-Bias Measurement and Simulation
16.5.2 Extracted Model Parameters
16.5.3 Confidence Limits on Extracted Parameters
16.6 REPEATIBILITY AND REPRODUCIBILITY CONFIRMATION TEST
16.7 SUMMARY
REFERENCES
Chapter 17 Pure Analytical Model Parameter Extraction
17.1 INTRODUCTION
17.2 THEORETICAL ANALYSIS
17.2.1 Determination of Extrinsic Capacitances and Inductances
17.2.2 Conditioning of Equation System for the 10-Element Model
17.2.3 Iterative Determination of Intrinsic Model Elements
17.3 FREQUENCY BANDWIDTH DEPENDENT EXTRACTION ACCURACY
17.4 SIMULATED MEASUREMENT ERROR DEPENDENT EXTRACTION ACCURACY
17.5 MEASUREMENT-BASED ANALYTICAL MODEL PARAMETEREXTRACTION
17.6 SUMMARY
REFERENCES
Chapter 18 Analytical Model Parameter Extraction Using Rational
Functions
18.1 INTRODUCTION
18.2 RATIONAL FUNCTIONS-BASED PARAMETER EXTRACTION
18.2.1 Least-Squares Approximation by Rational Functions
18.2.2 Extrinsic and Intrinsic Y-Parameters
18.2.3 Direct Model Parameter Extraction
18.2.4 Results
18.3 DISTRIBUTED SMALL-SIGNAL MODEL OF HBT D
18.4 SUMMARY
REFERENCES
Chapter 19 Repetitive Random Optimization andAdaptive Search Space
19.1 INTRODUCTION
19.2 STARTING VALUES
19.2.1 Effective Capacitances
19.2.2 Effective Inductances
19.2.3 Distributed Model Elements
19.3 ADAPTIVE SEARCH SPACE ALGORITHM
19.4 RESULTS: MATHEMATICAL VERSUS PHYSICS-BASED SOLUTION
19.5 SUMMARY
REFERENCES
Chapter 20 Bias Dependence of Source and Drain Resistances
20.1 INTRODUCTION
20.2 BIAS-DEPENDENT VERSUS BIAS-INDEPENDENT SERIES RESISTANCES
20.3 PRACTICAL EXPERIENCES IN THE EXTRACTION OF SERIES RESISTANCES OF GaAs FETs
20.3.1 Frequency Scanning Extraction Method
20.3.2 Extracted Bias-Dependent Source Resistances
20.4 BIAS-DEPENDENT ACCESS RESISTANCES IN GaN HEMTs
20.5 FREQUENCY AND TEMPERATURE DEPENDENCE OF SERIES RESISTANCES
20.6 SUMMARY
REFERENCES
Chapter 21 Model Parameter Extraction with Measurement-Correlated Parameter Starting Values
21.1 INTRODUCTION
21.2 MODEL PARAMETER EXTRACTION CONDITIONS
21.2.1 Heuristically Defined Capacitance Ratio Values
21.2.2 Reliable Determination of Capacitance Ratio Values from Top-View
Device Images
21.2.3 Definition of Pinch-Off Voltage
21.2.4 Definition of Minimum Measurement Range
21.2.5 Definition of Object Function
21.3 CONCEPT OF MEASUREMENT-CORRELATED STARTING VALUEGENERATION
21.3.1 Description of the Extraction Algorithm
21.3.2 Determination of Series Inductances and Resistances at Pinch-Off
21.3.3 Error Analysis
21.4 ESTIMATION OF TOTAL BRANCH CAPACITANCES FROM LOWFREQUENCY MEASUREMENTS
21.5 ESTIMATION OF DISTRIBUTED CAPACITANCES
21.6 ESTIMATION OF INDUCTANCES BY LINEAR CURVE FITTING
21.7 CLOSED-FORM ANAYLTICAL DETERMINATION OF INDUCTANCES
21.7.1 Measurement-Like S-Parameters Based on VNA Uncertainty Specifications
21.7.2 Validation of Inductance Determination Based on Noisy S-Parameters
21.8 ESTIMATION OF RESISTANCES
21.8.1 Cold Pinch-Off Measurement
21.8.2 Cold Forward Measurement
21.8.3 Standard Cold Reverse Measurement
21.8.4 Modified Cold Reverse Measurement
21.9 MODEL PARAMETER EXTRACTION WITH MEASURED
S-PARAMETERS
21.9.1 Extraction Based on Linear Curve Fitting of Inductances
21.9.2 Extraction Based on Analytical Determination of Inductances
21.10 DETERMINATION OF INTRINSIC MODEL PARAMETERS
21.11 SMALL-SIGNAL MODEL VERIFICATION
21.12 SUMMARY
REFERENCES
Chapter 22 Basics of Nonlinear FET Modeling
22.1 TERMS AND DEFINITIONS
22.1.1 Types of Model Elements in Equivalent Circuits
22.1.2 Quasi-Static Assumption
22.1.3 Definition of Voltages
22.1.4 Modes of Operation
22.2 NONLINEAR EQUIVALENT CIRCUIT ELEMENTS
22.3 NONLINEAR MODEL CONDUCTANCE
22.3.1 Single-Controlled Model Conductance
22.3.2 Multicontrolled Model Conductance
22.4 NONLINEAR MODEL CAPACITANCE
22.4.1 Single-Controlled Model Capacitance
22.4.2 Multicontrolled Model Capacitance
22.5 SUMMARY
REFERENCES
Chapter 23 Non-Quasi-Static Transistor Model
23.1 INTRODUCTION
23.2 TRANSISTOR BEHAVIORAL MODEL
23.2.1 Nonlinear N-Port Network
23.2.2 Nonlinear Two-Port
23.3 QUASI-STATIC TRANSISTOR MODEL
23.3.1 Symmetric Equivalent Pi Network
23.3.2 Asymmetric Equivalent Pi Network
23.4 DISPERSIVE DRAIN CURRENT MODEL
23.4.1 Drain Current Source with Bias-Dependent Conductances
23.4.2 Gate Charging Resistance
23.5 ELECTROTHERMAL DRAIN CURRENT MODELING
23.5.1 Pulsed-DC Related Drain Current Model
23.5.2 Transistor Thermal Model
23.6 EXTRACTION OF ELECTROTHERMAL DRAIN CURRENT MODEL
23.6.1 Extraction of Isothermal Drain Current and Trapping Correction Functions
23.6.2 Extraction of Thermal Parameters f and f
23.7 EXTRACTION OF TRAPPING AND THERMAL TIME CONSTANTS
23.8 SUMMARY
REFERENCES
Chapter 24 Large-Signal Measurement Techniques for Device Characterization and Model Verification
24.1 OVERVIEW OF LARGE-SIGNAL MEASUREMENT METHODS
24.2 EVOLUTION OF COMBINED FREQUENCY/TIME-DOMAIN SIGNAL WAVEFORM MEASUREMENT
24.2.1 Pure Signal Waveform Measurement
24.2.2 Fundamental Active Load-Pull Measurement
24.2.3 Harmonic Load-Pull Measurement with Electronic Tuner
24.3 OVERVIEW OF HIGH-POWER WIDEBAND SOURCE-/LOAD PULL MEASUREMENT TECHNIQUES
24.3.1 Setup Costs for High-Power Large-Signal Measurements
24.3.2 Advanced Signal Waveform Measurement Concepts for Wideband Applications
24.4 HIGH-POWER TIME-DOMAIN SOURCE-/LOAD-PULL MEASUREMENT SETUPS
24.4.1 High-Power Harmonic Source-/Load-Pull System with Passive Envelope Tuning
24.4.2 Issues Arising with Wideband Load-Pull Terminations
24.4.3 100W Broadband Passive Harmonic and Envelope Source-/Load-Pull Ssytem
24.5 HIGH-POWER FREQUENCY-DOMAIN IMD MEASUREMENT SYSTEM INCLUDING ENVELOPE LOAD-PULL
24.5.1 System Description
24.5.2 Envelope and RF Bias Networks
24.5.3 Issues in IMD Measurement Arising with Setup Configuration
24.5.4 System Calibration
24.5.5 P -PAE-IMD Load-Pull Optimization
24.5.6 Sweet-Spot Measurement
24.6 SUMMARY
REFERENCES
Chapter 25 Popular Nonlinear FET Models: Capabilities and Limitations
25.1 WIDELY USED 15-ELEMENT SMALL-SIGNAL EQUIVALENT CIRCUIT
25.1.1 Extraction of Pad Capacitances C and C
25.1.2 Extraction of Parasitic Resistances and Inductances
25.2 POPULAR NONLINEAR FET MODELS
25.2.1 Curtice Quadratic Nonlinear Model (1980)
25.2.2 Curtice-Ettenberg Cubic Nonlinear Model (1985)
25.2.3 Materka-Kacprzak Model (1983, 1985)
25.2.4 Statz Model (1987)
25.2.5 Angelov Model (1992/96)
25.2.6 TOM Model (TriQuint Nonlinear Model) (1990)
25.2.7 Tajima Model (1981/84)
25.2.8 ROOT Model (1991)
25.2.9 TOPAS Model (1996)
25.3 MODEL IMPLEMENTATION IN COMMERCIAL SIMULATION SOFTWARE
25.3.1 Implementation of Analytical Models
25.3.2 Implementation of Table-Based Models
25.4 SIMULATION RESULTS
25.4.1 Static DC Simulations
25.4.2 Pulsed-DC Simulations
25.4.3 Single-Tone Input Power Sweep
25.4.4 Two-Tone Input Power Sweep
25.5 SUMMARY
REFERENCES
Chapter 26 Nonlinear Transistor Model Verification
26.1 COMPLETE LARGE-SIGNAL DEVICE MODEL
26.2 MODEL IMPLEMENTATION
26.3 SIMULATION AND COMPARISON WITH MEASURED DEVICE DATA
26.3.1 Simulation of Bias-Dependent S-Parameters
26.3.2 Simulation of Pulsed-DC IV Characteristics
26.3.3 Simulation of Single- and Two-Tone Device Response
26.4 SUMMARY
REFERENCES
Appendix A Generic Two-Port Matrix Transistor Model
Appendix B
Direct Measurement of Series Resistances
B.1 INTRODUCTION
B.2 DC METHOD AFTER WILLIAMS
B.3 DC METHOD AFTER FUKUI
B.4 RF METHOD AFTER DAMBRINE ET AL.
B.5 COMPARATIVE EXPERIMENTAL RESULTS
REFERENCES
Appendix C
Parameter Extraction Relations for Inner FET Branch Topologies
C.1 R-L-C SERIES CIRCUIT
C.2 R-C SERIES CIRCUIT
C.3 G-C PARALLEL CIRCUIT
C. R-C PARALLEL CIRCUIT CONNECTED TO SERIES R
C.5 VOLTAGE-CONTROLLED CURRENT SOURCE
Appendix D Embedding the Intrinsic Model into an Extrinsic Network
D.1 EMBEDDING INTO AN IMPEDANCE NETWORK
D.2 EMBEDDING INTO AN ADMITTANCE NETWORK
Appendix E Derivation of Riccati Equation
REFERENCE
Appendix F
General N-Port Network and Two-Port Admittance Matrix
About the Author
Index