Shen Ye

Microstrip filter design using direct EM field simulation

For the first time, we present minimax filter design with electromagnetic (EM) simulations driven directly by a gradient-based optimizer. Challenges of efficiency, discretization of geometrical dimensions, and continuity of optimization variables are overcome by a three-stage attack: 1) efficient on-line response interpolation with respect to geometrical dimensions of microstrip structures simulated with fixed grid sizes; 2) smooth and accurate gradient evaluation for use in conjunction with the proposed interpolation; and 3) storing the results of expensive EM simulations in a dynamically updated database. Simulation of a lowpass microstrip filter illustrates the conventional use of EM simulation for design validation. Design optimization of a double folded stub bandstop filter and of a millimeter-wave 26-40 GHz interdigital capacitor bandpass microstrip filter illustrates the new technique. >

Integrated physics-oriented statistical modeling, simulation, and optimization (MESFETs)

Physics-based modeling of MESFETs is addressed from the point of view of efficient simulation, accurate behavior prediction and robust parameter extraction. A novel integration of a large-signal physics-based model into the harmonic balance equations for simulation of nonlinear circuits, involving an efficient Newton update, is presented and exploited in a gradient-based FAST (feasible adjoint sensitivity technique) circuit optimization technique. For yield-driven MMIC design a relevant physics-based statistical modeling methodology is presented. Quadratic approximation of responses and gradients suitable for yield optimization is discussed. The authors verify their theoretical contributions and exemplify their computational results using built-in and user-programmable modeling capabilities of the CAE systems OSA90/hope and HarPE. Results of device modeling using a field-theoretic nonlinear device simulator are reported. >

Yield-driven electromagnetic optimization via multilevel multidimensional models

The authors present the foundation of a sophisticated hierarchical multidimensional response surface modeling system for efficient yield-driven design. The scheme dynamically integrates models and database updating in real optimization time. The method facilitates a seamless, smart, optimization-ready interface. It has been specially designed to handle circuits containing complex subcircuits or components whose simulation requires significant computational effort. This approach makes it possible, for the first time, to perform direct gradient-based yield optimization of circuits with components or subcircuits simulated by an electromagnetic simulator. The efficiency and accuracy of the technique are demonstrated by yield optimization of a three-stage microstrip transformer and a small-signal microwave amplifier. The authors also perform yield sensitivity analysis for the three-stage microstrip transformer. >

Minimax microstrip filter design using direct EM field simulation

A comprehensive approach to microwave filter design which exploits accurate filed simulations driven directly by a gradient-based minimax optimizer is presented. Challenges of efficiency, discretization of geometrical dimensions, and continuity of optimization variables are reconciled by a three-stage attack: (1) efficient response interpolation; (2) smooth gradient estimation; and (3) dynamic database updating. The design optimization of two microstrip filters illustrates the technique described.<<ETX>>

Gradient quadratic approximation scheme for yield-driven design

A novel approach to the modeling of circuit response and gradients is proposed. The multidimensional quadratic approximation is exploited, and full advantage is taken of available gradient information. Efficiency and accuracy are demonstrated by gradient-based yield optimization of a filter and an MMIC (monolithic microwave integrate circuit) amplifier.<<ETX>>

Analytically unified DC/small-signal/large-signal circuit design

The authors examine the inherent analytical relationship between the DC, small-signal, and harmonic balance circuit equations. This provides the basis for unified DC, small-signal, and large-signal analyses using a single nonlinear circuit description. This approach ensures consistent circuit simulation results and permits simultaneous optimization of DC, small-signal, and large-signal responses with multidimensional specifications. Applying this concept to field effect transistor (FET) parameter extraction leads to nonlinear device models suitable for both small-signal and large-signal analyses. The authors also demonstrate simultaneous small-signal and large-signal minimax optimization of an FET broadband amplifier to extend the dynamic operating range. >

Integrated model parameter extraction using large-scale optimization concepts

A robust approach to modelling parameter extraction in microwave circuit design is presented. The approach not only attempts to match DC and AC measurements under different bias conditions simultaneously, but also employs the DC characteristics of the device as constraints on Bias-dependent parameters, this improving the uniqueness and reliability of the solution. The approach is an expansion of the hierarchical modeling techniques recently proposed J.W. Bandler and S.H. Chen (1988). Based on J.W. Bandler and Q.J. Zhangs (1987) automatic decomposition concepts for large-scale optimization, a sequential model building method is proposed which can be combined with powerful l/sub 1/ optimization techniques to establish a model with simple topology and sufficient accuracy. Practical FET models are used to illustrate the formulation. A detailed numerical example is presented to show the effectiveness of the approach. >

Statistical modeling of GaAs MESFETs

The authors contrast the statistical extraction of GaAs MESFET equivalent circuit model parameters and physical model parameters from wafer measurements. It is observed that the equivalent-circuit model of A. Materka and T. Kacprzak (1985) provides a better match for individual devices but the model based on physical parameters of P.H. Ladbrooke (1989) provides a better estimate of device statistics. It is also shown that the Materka and Kacprzak equivalent-circuit model can accurately fit the data from which the model parameters are extracted, because it has fewer constraints than the physical model.<<ETX>>

Efficient large-signal FET parameter extraction using harmonics

The authors present a novel approach to large-signal nonlinear parameter extraction of GaAs metal-semiconductor field-effect transistor (MESFET) devices measured under harmonic conditions. Powerful nonlinear adjoint-based optimization simultaneously processes multibias, multi-power-input, multi-fundamental-frequency excitations and multiharmonic measurements to reveal the parameters of the intrinsic FET. One test successfully processed 111 error functions of 20 model parameters. The technique was implemented in a program called HarPE (harmonic balance driven model parameter extractor).<<ETX>>

Predictable yield-driven circuit optimization

The authors present a comprehensive approach to predictable yield optimization. They utilize a new physics-based statistical GaAs MESFET model which combines the advantages of the DC Khatibzadeh and Trew model and the small-signal Ladbrooke formulas. The yield of a broadband amplifier was significantly improved after optimization. Predicted yield over a range of specifications was verified by device data. The benefits of simultaneous circuit-device yield optimization assisted by yield sensitivity analysis are demonstrated.<<ETX>>