Complete parasitic‐capacitance‐shell extraction of high‐frequency switch‐HEMT equivalent‐circuit model

This paper presents a new solution to a particular problem of high electron‐mobility transistor (HEMT) equivalent‐circuit modeling, that is, complete parasitic‐capacitance‐shell extraction of high‐frequency single‐gate and dual‐gate switch‐based HEMTs, which is very important to the accuracy of high‐frequency HEMT switch models, but not important in the conventional common‐source HEMT modeling for amplifier‐applications. A full‐wave electromagnetic (EM) analysis based method is proposed to analytically extract the complete parasitic‐capacitance‐shell of single‐gate and dual‐gate switch‐based HEMTs. All the 6 parasitic capacitances of the single‐gate switch‐based HEMT and all the 10 parasitic capacitances of the dual‐gate switch‐based HEMT are extracted by linear equations. No resistance parameter is needed to calculate the capacitance‐to‐ground and the interelectrode‐capacitance, and for the first time, all the 10 parasitic capacitances of the dual‐gate switch‐based HEMT are completely considered and analytically extracted. Then, a consistent and systematic modeling procedure of single‐gate and dual‐gate switch‐based HEMT is verified. With the complete parasitic‐capacitance‐shells extracted, the accurate intrinsic model of the single‐gate HEMT can be directly embedded into the parasitic‐shell of the dual‐gate HEMT. The predicted scattering parameters of the single‐gate and dual‐gate series switches fit well with the measurements up to 40 GHz, and accurate linear scalability are also found.     

Direct extraction method of HEMT switch small‐signal model with multiparasitic capacitive current path

It has been found that the analytical extraction methods cannot be applied to the usual test structure of the switch high electron‐mobility transistor (HEMT) with a large‐value gate grounded resistor. The significant effect of the precise multicapacitive current path on switch model precision has also been found. The multicapacitive current path here is different from the seemingly similar hypothesis proposed for the distributed parasitic effects at high frequencies (eg, D‐band). In fact, for switch based HEMT, it is important to distinguish between the capacitive current paths accurately even at relatively low frequencies. Due to the existing of the large gate resistance, the usual capacitance mix decreases the accuracy of the switch model significantly. Thus an analytical method has been developed to calculate parasitic capacitances (the capacitance to ground and the interelectrode capacitance) through full‐wave electromagnetic analysis. For practical applications and further verification, the whole HEMT switch small‐signal models and the direct extraction methods are presented. The simulated results fit well with the measurements up to 40 GHz.     

Modeling power and intermodulation behavior of microwave transistors with unified small‐signal/large‐signal neural network models

This article presents a detailed procedure to learn a nonlinear model and its derivatives to as many orders as desired with multilayer perceptron (MLP) neural networks. A modular neural network modeling a nonlinear function and its derivatives is introduced. The method has been used for the extraction of the large‐signal model of a power MESFET device, modeling the nonlinear relationship of drain‐source current I_ds as well as gate and drain charge Q_g and Q_d with respect to intrinsic voltages V_gs and V_ds over the whole operational bias region. The neural models have been implemented into a user‐defined nonlinear model of a commercial microwave simulator to predict output power performance as well as intermodulation distortion. The accuracy of the device model is verified by harmonic load‐pull measurements. This neural network approach has demonstrated to predict nonlinear behavior with enough accuracy even if based only on first‐order derivative information. © 2003 Wiley Periodicals, Inc. Int J RF and Microwave CAE 13: 276–284, 2003.     

An improved empirical large‐signal model for the GaAs‐ and GaN‐based HEMTs

A complete empirical large‐signal model for the GaAs‐ and GaN‐based HEMTs is presented. Three generalized drain current I–V models characterized by the multi‐bias Pulsed I–V measurements are presented along with their dependence on temperature and quiescent bias state. The new I–V equations dedicated for different modeling cases are kept accurate enough to the higher‐order derivatives of drain‐current. Besides, an improved charge‐conservative gate charge Q–V formulation is proposed to extract and model the nonlinear gate capacitances. The composite nonlinear model is shown to accurately predict the S‐parameters, large‐signal power performances as well as the two‐tone intermodulation distortion products for various types of GaAs and GaN HEMTs. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE , 2011.     

Microwave frequency small‐signal equivalent circuit parameter extraction for AlInN/GaN MOSHEMT

This article presents an accurate and efficient extraction procedure for microwave frequency small‐signal equivalent circuit parameters of AlInN/GaN metal‐oxide‐semiconductor high electron mobility transistor (MOSHEMT). The parameter extraction technique is based on the combination of conventional and optimization methods using the computer‐aided modeling approach. The S‐, Y‐, and Z‐ parameters of the model are extracted from extensive dynamic AC simulation of the proposed device. From the extracted Y‐ and Z‐ parameters the pad capacitances, parasitic inductances and resistances are extracted by operating the device at low and high frequency pinch‐off condition depending upon requirement. Then, the intrinsic elements are extracted quasi analytically by de‐embedding the extrinsic parameters. S‐parameter simulation of the developed small‐signal equivalent circuit model is carried out and is compared with TCAD device simulation results to validate the model. The gradient based optimization approach is used to optimize the small‐signal parameters to minimize the error between developed SSEC model and device simulation based s‐parameters. The microwave characteristics of optimized SSEC model is carried out (f_T = 169 GHz and f_max = 182 GHz) and compared with experimental data available from literature to validate the model.     

Bayesian inference‐based small‐signal modeling technique for GaN HEMTs

A new modeling methodology for gallium nitride (GaN) high‐electron‐mobility transistors (HEMTs) based on Bayesian inference theory, a core method of machine learning, is presented in this article. Gaussian distribution kernel functions are utilized for the Bayesian‐based modeling technique. A new small‐signal model of a GaN HEMT device is proposed based on combining a machine learning technique with a conventional equivalent circuit model topology. This new modeling approach takes advantage of machine learning methods while retaining the physical interpretation inherent in the equivalent circuit topology. The new small‐signal model is tested and validated in this article, and excellent agreement is obtained between the extracted model and the experimental data in the form of dc I–V curves and S‐parameters. This verification is carried out on an 8 × 125 μm GaN HEMT with a 0.25 μm gate feature size, over a wide range of operating conditions. The dc I–V curves from an artificial neural network (ANN) model are also provided and compared with the proposed new model, with the latter displaying a more accurate prediction benefiting, in particular, from the absence of overfitting that may be observed in the ANN‐derived I–V curves.     

New small‐signal extraction method applied to GaN HEMTs on different substrates

In this article, a new extraction technique is proposed to extract the small‐signal parameters of gallium nitride (GaN) high electron mobility transistors (HEMTs) on three different substrates namely, Si, SiC, and Diamond. This extraction technique used a single small‐signal circuit model to efficiently describe the physical and electrical properties of GaN on different substrates. This technique takes into account any asymmetry between the gate‐source and gate‐drain capacitances on the asymmetrical GaN HEMT structure, charge‐trapping effects, passivation layer inclusion, as well as leakage currents associated with the nucleation layer between the GaN buffer layer and the different substrates. The extracted values were then optimized using the grey wolf optimizer. The proposed technique was demonstrated through a close agreement between simulated and measured S‐parameters.     

Neural network modeling of microwave FETs based on third‐order distortion characterization

A new method for characterization of HEMT distortion parameters, which extracts the coefficents of a Taylor series expansion of I_ds(V_gs, V_ds), including all cross‐terms, is developed from low‐frequency harmonic measurements. The extracted parameters will be used either in a Volterra series model around a fixed bias point for 3^rd‐order characterization of small‐signal I_ds nonlinearity, or in a large‐signal model of I_ds characteristic, where its partial derivatives are locally characterized up to the 3^rd order in the whole bias region, using a novel neural‐network representation. The two models are verified by one‐tone and two‐tone intermodulation distortion (IMD) tests on a PHEMT device. © 2006 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2006.     

A simplification method for capacitance models in AlGaN/GaN high electron mobility transistors under large drain voltage using channel analysis

This article analyzes the bias dependence of gate‐drain capacitance (C_gd) and gate‐source capacitance (C_gs) in the AlGaN/GaN high electron mobility transistors under a high drain‐to‐source voltage (V_ds) from the perspective of channel shape variation, and further simplifies C_gd and C_gs to be gate‐to‐source voltage (V_gs) dependent only at high V_ds. This method can significantly reduce the number of parameters to be fitted in C_gd and C_gs and therefore lower the difficulty of model development. The Angelov capacitance models are chosen for verifying the effectiveness of simplification. Good agreement between simulated and measured small‐signal S‐parameters, large‐signal power sweep, and power contours comprehensively proves the accuracy of this simplification method.     

An improved millimeter‐wave small‐signal modeling approach for HEMTs

An improved method to determine the small‐signal equivalent circuit model for HEMTs is presented in this study, which is combination of the analytical approach and empirical optimization procedure. The parasitic inductances and resistances are extracted under pinch‐off condition. The initial intrinsic elements are determined by conventional analytical method. Advanced design system (agilent commercial circuit simulator) is used to optimize the whole model parameters with small deviation of initial values. An excellent agreement between measured and simulated S‐parameters is obtained for 2 × 20 μm² gate width HEMT up to 40 GHz. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:464–469, 2014.     

A de‐embedding method with matrix rectification and influences of residual errors on model parameters extraction of InP HEMTs

As the cutoff frequency of InP HEMTs enters the terahertz band, high frequency measurement and modeling techniques in hundreds of gigahertz become urgent needs for further millimeter monolithic integrated circuits design. We proposed a new de‐embedding method linking device measurements and modeling based on full EM simulation data acquired from HFSS and advanced design system (ADS). The simulation results for passive dummy structures are well consistent with experiments, and the de‐embedding method is proved very effective for a resistive passive device with high distributed embedding surroundings in frequency range below 40 GHz. Based on these experimental facts, the EM simulations were extended up to 300 GHz and corresponding de‐embedding deviation was further investigated. Results show that the proposed de‐embedding method has very high accuracy in the whole frequency region with a maximum S‐parameters deviation of only 2.58%. However, further analysis proves that the small residual errors still significantly affect extracted small signal model parameters of InP HEMTs especially for transit time τ. Thus, further improvements on de‐embedding accuracy or careful considerations of more error functions in modeling process are necessary for obtaining physically meaningful model parameters.     

Multifingers capacitances modeling of 65‐Nm CMOS transistor by unit cell method

The multifingers' parasitic capacitances modeling of 65‐nm CMOS transistors for millimeter‐wave application is presented. The modeling is based on simulation approach, which is done by building the devices true dimension in high‐frequency structure simulator environment. The material properties of the devices as given by the foundry are used during simulation and then full electromagnetic simulations are carried out to extract the Y‐parameters of the model. Unit‐cell parameters extraction method is carried out in order to save memory and simulation time. In this case, the multifinger transistors are divided into unit‐cells and then the parasitic capacitances of the unit‐cells are calculated from the extracted Y‐parameter. Based on linear scaling, the parasitic capacitance of the multifingers transistor can be obtained with good accuracy (less than 5% error). © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE , 2012.     

Pulsed I/V and S‐parameters measurement system for isodynamic characterization of power GaN HEMT transistors

This article presents a system capable of performing isodynamic I/V and S‐parameter measurements. It is focused on the necessary characterization signals, laboratory equipment, and pulser (power head). Proper biasing waveforms are developed and used to extract accurate nonlinear measurements that take into account the frequency dispersive phenomena, namely, the drain lag and temperature rise observed in GaN HEMTs. The pulser can drive high power devices (120 V and 45 A) for very fast and accurate pulses (widths between 300 and 800 ns). As validation, a commercial 15 W GaN device (CGH27015P) from Wolfspeed was characterized using this setup. The consistency between the obtained pulsed I/V curves and others obtained by the integration of the small signal transcondutance (g_m) and output conductance (g_ds) proves that the presented system is capable of performing isodynamic characterization of power transistors.     

Large‐signal distributed millimeter‐wave multifinger pHEMT modeling using time‐domain technique

The finite‐difference time‐domain (FDTD) method is used for the large‐signal modeling of a multifinger pHEMT, which is considered as five nonlinear coupled distributed transmission lines. The developed model, which is based on the exact physical layout of multifinger pHEMT, not only accurately describes the propagation effects along the electrodes at higher frequencies but it also includes major nonlinearities of the I–V and Q–V characteristics. Using the transmission line theory, a proper nonlinear equivalent lumped circuit model is allocated for the differential length of the quintuple‐line transistor and the nonlinear active multiconductor transmission line (NAMCTL) equations are derived. These nonlinear, coupled differential equations are numerically solved using the FDTD method. The proposed model is applied to a 100 nm GaAs pHEMT and the simulation results are compared with the results of conventional sliced model in Keysight ADS simulator. The developed transient nonlinear model accurately predicts both the S‐parameters (1–150 GHz) and large‐signal power performances especially at millimeter wave frequency range. The proposed model can be useful in design and analysis of various types of high‐frequency nonlinear integrated circuits.     

Machine learning technique based extremely broadband small‐signal behavioral model for InP DHBTs

A novel modeling methodology for indium phosphide (InP) double heterojunction bipolar transistors (DHBTs) based on the theory of Bayesian inference, a well‐known method from the field of machine learning, is presented in this article. An extremely broadband small‐signal behavioral model, from 200 MHz to 325 GHz, is built, tested, and validated in this work, with excellent agreement obtained between the extracted model and the experimental data in the form of S‐parameters. A single finger InP DHBT device, with emitter size of 0.5 × 5 μm² exhibiting an ft of over 550 GHz, is used in the verification example. Taking advantage of regression techniques based on machine learning concepts, the proposed black‐box behavioral model can more accurately predict the behavior of the device compared with the traditional equivalent circuit modeling method. Several sets of measured vs modeled data are shown, indicating the efficacy of the method.     

On the small signal modeling of advanced microwave FETs: A comparative study

Although many successful techniques have been proposed in the last decades for extracting the small signal equivalent circuit for microwave transistors from scattering parameter measurements, small signal modeling is still object of intense research. Further improvement and development of the proposed methods are incessantly required to take into account the continuous and rapid evolution of the transistor technology. The purpose of this article is to facilitate the choice of the most appropriate strategy for each particular case. For that, we present a brief but thorough comparative study of analytical techniques developed for modeling different types of advanced microwave transistors: GaAs HEMTs, GaN HEMTs, and FinFETs. It will be shown that a crucial step for a successful modeling is to adapt accurately the small signal equivalent circuit topology under “cold” condition to each investigated technology. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2008.     

In‐deep insight into the extrinsic capacitance impact on GaN HEMT modeling at millimeter‐wave band

The extrinsic input and output capacitances of the field effect transistor small‐signal equivalent circuit are typically extracted from the low frequency admittance parameters under “cold” pinch‐off condition. Despite that, these two capacitances play a significant role also at high frequencies. Intuitively, a first hint of explanation stems from the high frequency reduction of their admittance values connected in parallel to the input and the output of the rest of the equivalent circuit. In particular, the extrinsic capacitances can cause an increase of the real parts of the impedance parameters at high frequencies. This article is aimed at developing an extensive experimental and mathematical analysis based on a comparative study of this behavior for GaN high electron mobility transistor (HEMT) devices up to the millimeter‐wave range. The results of this analysis can be applied for estimating the extrinsic capacitances. The main benefit of this modeling technique is that the extrinsic output capacitance can be separated from the intrinsic output capacitance, which can play a significant role especially in case of large devices. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE , 2012.     

Microwave analysis of SiGe heterojunction double‐gate tunneling field‐effect transistor through its small‐signal equivalent circuit

In this study, Si_0.5Ge_0.5 was used as a source junction material in a tunneling field‐effect transistor (TFET), which was analyzed using technology computer‐aided design (TCAD) simulation and a small‐signal non‐quasi static (NQS) equivalent circuit. The NQS equivalent circuit with additional tunneling resistance (R_tunnel) enables more accurate analyses. By using a de‐embedding process, small‐signal parameters in the intrinsic area were obtained. This process was used to analyze the resistance and capacitance in each section, the tendencies of the materials, and the voltage. The error between the NQS equivalent circuit and TCAD device simulation was within 1.9% in the 400‐GHz regime. A cut‐off frequency (f_T) of up to 0.876 GHz and maximum oscillation frequency (f_max) of 146 GHz were obtained.     

Empirical nonlinear modeling for RF MOSFETs

A new empirical model with an external substrate network is proposed to simulate the RF nonlinear characteristics of a MOSFET accurately in the wide range of operating bias points. An accurate drain current equation is developed to model the nonlinear transconductance characteristics of a RF MOSFET, and improved nonlinear capacitance equations are used. The values of modeled S₂₁ parameters using the new drain current equation show much better agreement with measured ones than those using the conventional formula over the wide bias range, thus verifying the accuracy of the new model. © 2004 Wiley Periodicals, Inc. Int J RF and Microwave CAE 14, 182–189, 2004.     

硅微机械陀螺仪结构中的电容分析

为减小杂散电容提高信噪比,分析了硅微机械陀螺仪结构中的电容.并以某硅微机械陀螺仪的理论模型为对象,建立了陀螺仪结构中的电容模型.对每种电容进行了理论分析,并借助电路仿真软件对模型进行了仿真,分析了杂散电容对输出的影响,结果表明布线与活动结构间的电容对输出有很大的影响.提出了采用新工艺和合理的布线方法减小与活动结构间的电容,从而提高信噪比.