David E. Root

Bias-dependent linear, scalable millimeter-wave FET model

This paper describes a measurement-based, bias-dependent, linear equivalent circuit FET/HEMT model that is accurate to at least 100 GHz and scalable up to 12 parallel gate fingers and from 100-1000 /spl mu/m total gate width. The equivalent circuit element values are determined at each bias point in V/sub gs/-V/sub ds/ space.

New Trends for the Nonlinear Measurement and Modeling of High-Power RF Transistors and Amplifiers With Memory Effects

Power amplifier (PA) behavior is inextricably linked to the characteristics of the transistors underlying the PA design. All transistors exhibit some degree of memory effects, which must therefore be taken into account in the modeling and design of these PAs. In this paper, we will present new trends for the characterization, device modeling, and behavioral modeling of power transistors and amplifiers with strong memory effects. First the impact of thermal and electrical memory effects upon the performance of a transistor will be revealed by comparing continuous wave and pulsed RF large-signal measurements. Pulsed-RF load-pull from the proper hot bias condition yields a more realistic representation of the peak power response of transistors excited with modulated signals with high peak-to-average power ratio. Next, an advanced device modeling method based on large-signal data from a modern nonlinear vector network analyzer instrument, coupled with modeling approaches based on advanced artificial neural network technology, will be presented. This approach enables the generation of accurate and robust time-domain nonlinear simulation models of modern transistors that exhibit significant memory effects. Finally an extension of the X-parameter (X-parameter is a trademark of Agilent Technologies Inc.) behavioral model to account for model memory effects of RF and microwave components will be presented. The approach can be used to model hard nonlinear behavior and long-term memory effects and is valid for all possible modulation formats for all possible peak-to-average ratios and for a wide range of modulation bandwidths. Both the device and behavioral models have been validated by measurements and are implemented in a commercial nonlinear circuit simulator.

Extension of X-parameters to include long-term dynamic memory effects

A new unified theory and methodology is presented to characterize and model long-term memory effects of microwave components by extending the Poly-Harmonic Distortion (PHD) Model to include dynamics that are identified from pulsed envelope X-parameter measurements on an NVNA. The model correctly predicts the transient RF response to time-varying RF excitations including the asymmetry between off-to-on and on-to-off switched behavior as well as responses to conventional wide-bandwidth communication signals that excite long-term memory effects in power amplifiers. The model is implemented in the ADS circuit envelope simulator.

Large-signal HBT model with improved collector transit time formulation for GaAs and InP technologies

An analytical large-signal HBT model which accurately accounts for the intricate bias dependence of collector delay in devices fabricated in both GaAs and InP material systems is described. The strongly bias dependent collector delay function accounts for the variation of electron velocity with electric field of the collector, which has consequences for both the electron transit time and capacitance. It is shown that the new formulation significantly improves the prediction of the bias dependence of f/sub t/. As a result, simulations over a very wide range of operating conditions match measured data on a wide variety of devices. Distortion predictions are improved since the derivatives of the bias dependent delay are more accurately modeled. This new model is extracted on medium and high breakdown GaAs HBTs, and also on InP DHBTs. Simulation results are verified with comparisons to S-parameter and large-signal measurements.

Load-pull + NVNA = enhanced X-parameters for PA designs with high mismatch and technology-independent large-signal device models

X-parameters are the mathematically correct supersets of S-parameters valid for nonlinear (and linear) components under large-signal (and small-signal) conditions. This work presents an automated application combining a nonlinear vector network analyzer (NVNA) instrument with automated load-pull measurements that extends the measurement and extraction of X-parameters over the entire Smith Chart. The augmented X-parameter data include magnitude and phase as nonlinear functions of power, bias, and load, at each harmonic generated by the device and measured by the NVNA. The X-parameters can be immediately used in a nonlinear simulator for complex microwave circuit analysis and design. This capability extends the applicability of measurement-based X-parameters to highly mismatched environments, such as high-power and multi-stage amplifiers, and power transistors designed to work far from 50 ohms. It provides a powerful and general technology-independent alternative, with improved accuracy and speed, to traditional large-signal device models which are typically slow to develop and typically extrapolate large-signal operation from small-signal and DC measurements.

Multi-tone, Multi-port, and Dynamic Memory Enhancements to PHD Nonlinear Behavioral Models from Large-signal Measurements and Simulations

The PHD nonlinear behavioral model is extended to handle multiple large tones at an arbitrary number of ports, and enhanced for dynamic long-term memory. New capabilities are exemplified by an amplifier model, derived from large-signal network analyzer (LSNA) data, valid for arbitrary impedance environments, and a model of a 50GHz integrated mixer, including leakage terms and IF mismatch dependence. Dynamic memory is demonstrated by an HBT amplifier model identified from up-converted band-limited noise excitations. The models are validated with independent LSNA component data or, for simulation-based models, with the corresponding circuit models.

GaN Device Modeling with X-Parameters

Arbitrary-load-dependent X-parameters, automatically measured with a load-tuner working with an NVNA, are used to characterize and model a packaged 10W GaN transistor. A full nonlinear two-port functional block model for PA and other circuit design is immediately available for nonlinear simulation. It is demonstrated that the model predicts well the independent effects of harmonic load tuning without having to independently control harmonic loads during characterization. The nonlinear model can be used effectively to obtain optimal fundamental and harmonic impedances for device operation, as well as predict, accurately, other nonlinear FOMs including PAE and harmonic distortion. Source-pull is shown to be unnecessary except for efficient power transfer, yet the model is fully capable of predicting correct device response when embedded in any source and load impedance at the fundamental and harmonics.

Large-signal FET model with multiple time scale dynamics from nonlinear vector network analyzer data

A non-quasi static large-signal FET model is presented incorporating self-heating and other multiple timescale dynamics necessary to describe the large-signal behavior of III–V FET technologies including GaAs and GaN. The model is unique in that it incorporates electro-thermal and trapping dynamics (gate lag and drain lag) into both the model current source and the model nonlinear output charge source, for the first time. The model is developed from large-signal waveform data obtained from a modern nonlinear vector network analyzer (NVNA), working in concert with an output tuner and bias supplies. The dependences of Id and Qd on temperature, two trap states, and instantaneous terminal voltages are identified directly from NVNA data. Artificial neural networks are used to represent these constitutive relations for a compiled implementation into a commercial nonlinear circuit simulator (Agilent ADS). Detailed comparisons to large-signal measured data are presented.

Dynamic FET model - DynaFET - for GaN transistors from NVNA active source injection measurements

A complete nonlinear characterization and modeling flow for modern GaN transistors is presented. Features include a new active-source injection based waveform measurement HW/SW system built around an NVNA, an extended artificial neural network (ANN) training infrastructure for coupled electro-thermal and trap-dependent model constitutive relations, and the native implementation in a commercial simulator. The model is validated by detailed comparisons to measured data for an advanced mm-wave 150 nm 6×60μm GaN HFET manufactured by Raytheon Integrated Defense Systems. Excellent results are achieved for DC, S-parameters, harmonic and intermodulation distortion, and load-pull figures of merit, over a very wide range of bias conditions, complex loads, powers, and frequencies.

The construction and evaluation of behavioral models for microwave devices based on time-domain large-signal measurements

We present a new procedure for creating nonlinear behavioral models of microwave devices, based on techniques developed in time-series analysis. We illustrate this procedure by creating a model for a HEMT device. Large-signal time-domain microwave measurements are used to generate the time-series data of the terminal currents and voltages. The dynamical model of the HEMT is defined by fitting multivariate polynomials to the terminal voltages and their higher-order derivatives. The model accurately predicts DC, small-signal, and large-signal behavior.