Modeling Of Microwave Circuits Research Articles

Improved efficacy behavioral modeling of microwave circuits through dimensionality reduction and fast global sensitivity analysis

Behavioral models have garnered significant interest in the realm of high-frequency electronics. Their primary function is to substitute costly computational tools, notably electromagnetic (EM) analysis, for repetitive evaluations of the structure under consideration. These evaluations are often necessary for tasks like parameter tuning, statistical analysis, or multi-criterial design. However, constructing reliable surrogate models faces several challenges, including the nonlinearity of circuit characteristics and the vast size of the parameter space, encompassing both dimensionality and design variable ranges. Additionally, ensuring the validity of the model across broad geometry/material parameter and frequency ranges is crucial for its utility in design. The purpose of this paper is to introduce an innovative approach to cost-effective and dependable behavioral modeling of microwave passives. Central to our method is a fast global sensitivity analysis (FGSA) procedure, which is devised to identify correlations between design parameters and quantify their impacts on circuit characteristics. The most significant directions identified through FGSA are utilized to establish a reduced-dimensionality domain. Within this domain, the model may be constructed using a limited amount of data samples while capturing a significant portion of the circuit response variability, rendering it suitable for design purposes. The outstanding predictive capability of the proposed model, its superiority over traditional techniques, and its readiness for design applications are demonstrated through the analysis of three microstrip circuits of diverse characteristics.

Simulation and Automated Modeling of Microwave Circuits: State-of-the-Art and Emerging Trends

Microwave modeling and simulation are essential to designing microwave circuits and systems. Although fundamental concepts and approaches for modeling and simulation are mature, the drive to higher frequencies, tighter design margins, and more functionality/complexity of circuits continue to defy the capabilities of existing modeling and simulation methods. Newer algorithms are being developed to address the speed, accuracy and robustness of design algorithms. Coupled with the advent of more powerful computers and algorithms, microwave design automations are solving much more complex problems in much shorter time than previously imaginable. This paper describes the advances and state-of-the-art in automated modeling and simulation. Automated data-driven modeling approaches covering data sampling/generation, model structure adaptation, and model training/validation are described. Simulation of nonlinear microwave circuits is described covering formulations of simulation equations and advanced solution algorithms addressing problem size, convergence speed and solution accuracy. The descriptions highlight fundamental concepts, advanced methodologies, and future trends of development.

A Robust Quasi-Newton Training with Adaptive Momentum for Microwave Circuit Models in Neural Networks

A Robust Quasi-Newton Training with Adaptive Momentum for Microwave Circuit Models in Neural Networks

Progress in neural network based techniques for signal integrity analysis–a survey

With the increase in data rates, signal integrity analysis has become more time and memory intensive. Simulation tools such as 3D electromagnetic field solvers can be accurate but slow, whereas faster models such as design equations and equivalent circuit models lack accuracy. Artificial neural networks (ANNs) have recently gained popularity in the RF and microwave circuit modeling community as a new modeling tool. This has in turn spurred progress towards applications of neural networks in signal integrity. A neural network can learn from a set of data generated during the design process. It can then be used as a fast and accurate modeling tool to replace conventional approaches. This paper reviews the recent advancement of neural networks in the area of signal integrity modeling. Key advancements are considered, particularly those that assist the ability of the neural network to cope with an increasing number of inputs and handle large amounts of data.

Polynomial-Based Surrogate Modeling of RF and Microwave Circuits in Frequency Domain Exploiting the Multinomial Theorem

A general formulation to develop electromagnetic-based polynomial surrogate models in the frequency domain utilizing the multinomial theorem is presented in this paper. Our approach is especially suitable when the number of learning samples is very limited and no physics-based coarse model is available. We compare our methodology against four other surrogate modeling techniques: response surface modeling, support vector machines, generalized regression neural networks, and Kriging. Results confirm that our modeling approach has the best performance among these techniques when using a very small amount of learning base points on relatively small modeling regions. We illustrate our technique by developing a surrogate model for a substrate integrated waveguide interconnect with transitions to microstrip lines, a dual-band T-slot planar inverted-F handset antenna, and a high-speed package interconnect. Examples are simulated on a commercially available 3-D FEM simulator.

Microwave harmonic generation and nonlinearity in microplasmas

Nonlinearities in microplasmas excited by microwaves are described both experimentally and through a 2D fluid model. A split-ring resonator generates a microplasma in a 150 μm discharge gap at 1 GHz. Nonlinearity generates both radiated and conducted harmonics which are measured from 0.2–760 Torr (Ar) for power levels between 0.5 and 3 W. Asymmetric electrode configurations produce the highest 3rd harmonic power (>10 mW) at an optimal pressure of the order of 0.3 Torr. The microplasma is also demonstrated as a mixer. The experimental results are explained with the aid of a fluid model of the microplasma. The model shows that the smaller electrode in an asymmetric device is forced to attain a large microwave potential that strongly modulates the sheath thickness and the local electron energy. The voltage-dependent sheath width gives rises to a nonlinear sheath capacitance as well as short pulses of hot electron flux to the electrode. The modeled 3rd harmonic current is converted to an extractable harmonic power by a microwave circuit model. Using this technique the modeled and measured harmonic production of the microplasma are found to compare favorably.

The Wonderful World of Nonlinearity : A Distinguished Microwave Lecture on the Modeling and Characterization of RF and Microwave Circuits

This article summarizes my IEEE Distinguished Microwave Lecture "The Wonderful World of Nonlinearity: Modeling and Characterization of RF and Microwave Circuits." Conceived for nonexperts, the lecture aims to catch the attention of an audience of either graduate students or practicing engineers, whose undergraduate preparation in nonlinear analysis typically is insufficient to help them deal with even the simplest nonlinear wireless RF subsystems. Rather than any current hot topics in microwave technology, the focus is on the varied roles nonlinearity plays in many microwave circuits.

A Goal-Oriented Error Estimator for Reduced Basis Method Modeling of Microwave Devices

This letter proposes a novel a-posteriori error estimator suitable for the reduced order modeling of microwave circuits. Unlike the existing error estimators based on impedance function residuals, the new one exploits the residual error associated with the computation of the scattering matrix. The estimator can be effectively used in the Reduced Basis Method (RBM) to automatically generate reduced-order models. The results of numerical experiments show that the new error estimator predicts the errors in the computed S-parameters more accurately than the other existing approaches, and that it can be used to automate the generation of wideband reduced models.

Modeling and Simulation of Microwave Circuits

A new and efficient method is presented for the analysis of arbitrarily shaped discontinuities. The technique obtains closed form expressions for the equivalent circuits which are used to model these discontinuities. Then it would be easy to handle and to characterize complicated structures like T and Y junctions, truncated junctions, arbitrarily shaped junctions, cascading junctions and more generally planar multiport junctions. Another advantage of this method is that the edge line concept for arbitrary shape junctions operates with real parameters circuits. The validity of the method was further confirmed by comparing our results for various discontinuities (bend, filters) with those from HFSS as well as from other published sources.

Simulation optimization to microwave components using neural network

This paper proposes a new technique to train neural network (NN); with the result, we can solve some real-world application problems such as microwave components modeling and optimization. Its major advance is achieved in avoiding the testing error falling into local minimum. After the generalization, the ability of three-layer and four-layer NN is also checked; our investigations show that four-layer NN trained by the proposed training method can map the electromagnetic simulation of microwave components better than its counterpart. Besides, the modeling of microwave circuits and slotted patch antennas is examined to demonstrate the validity of this technique. Copyright © 2012 John Wiley & Sons, Ltd.

Surrogate modeling of microwave structures using kriging, co‐kriging, and space mapping

SUMMARYSpace mapping (SM) is one of the most popular techniques for creating computationally cheap and reasonably accurate surrogates of electromagnetic‐simulated microwave structures (so‐called fine models) using underlying coarse models, typically equivalent circuits. One of the drawbacks of SM is that although good modeling accuracy can be obtained using a limited number of training points, SM is not capable of efficiently utilizing larger amount of fine model information, even if it is available. In this paper, we consider various ways of enhancing SM surrogates by exploiting additional training data as well as two function approximation methodologies, kriging and co‐kriging. To our knowledge, it is the first application of co‐kriging for microwave circuit modeling. With three examples of microstrip filters, we present a comprehensive numerical study in which we compare the accuracy of the basic SM models as well as SM enhanced by kriging and co‐kriging. Direct kriging interpolation of fine model data is used as a reference. Copyright © 2012 John Wiley & Sons, Ltd.

25Gb/s 1V-driving CMOS ring modulator with integrated thermal tuning

We report a high-speed ring modulator that fits many of the ideal qualities for optical interconnect in future exascale supercomputers. The device was fabricated in a 130 nm SOI CMOS process, with 7.5 μm ring radius. Its high-speed section, employing PN junction that works at carrier-depletion mode, enables 25 Gb/s modulation and an extinction ratio >5 dB with only 1V peak-to-peak driving. Its thermal tuning section allows the device to work in broad wavelength range, with a tuning efficiency of 0.19 nm/mW. Based on microwave characterization and circuit modeling, the modulation energy is estimated ~7 fJ/bit. The whole device fits in a compact 400 μm2 footprint.

Accurate modeling and optimization of microwave circuits and devices using adaptive neuro-fuzzy inference system

In this paper, an accurate neuro-fuzzy-based model is proposed for efficient computer-aided design (CAD) modeling and optimization of microwave circuits and devices. The adaptive neuro-fuzzy inference system (ANFIS) approach is used to determine the scattering parameters of a microstrip filter and is applied to the optimization design of this microstrip filter. The ANFIS has the advantages of expert knowledge of fuzzy inference system and learning capability of artificial neural networks. The neuro-fuzzy model has been trained and tested with different sets of input/output data. Finally, different results, which confirm the validity of the proposed model, are reported.

Study of a Capacitive Clamped Beam RF MEMS Power Sensor Based on MEMS Technology

This paper proposes a sophisticated type of capacitive clamped beam RF MEMS power sensor, which is fabricated on GaAs substrate with MMIC technology. This new capacitive clamped beam RF MEMS power sensor can act quickly to the RF signals and consumes little power on central CPW line. A version of draft microwave circuit model is presented, in order to build a set of initial structure parameters of the clamped beam RF MEMS power sensor simulation model. The frequency scope of this designed clamped beam RF MEMS power sensor is from 8GHz to 12GHz. Through adjusting the set of initial structure parameters of simulation model, a set of successful and proper S parameter of HFSS simulation can be obtained, and the S parameter is: S11 is less than -35dB and S21 is less than 0.15dB. Based on the performance parameter mentioned, the optimization on the power sensor simulation structure has been presented.

The state of the art of microwave CAD: EM-based optimization and modeling

We briefly review the current state of the art of microwave CAD technologies. We look into the history of design optimization and CAD-oriented modeling of microwave circuits as well as electromagnetics-based optimization techniques. We emphasize certain direct approaches that utilize efficient sensitivity evaluations as well as surrogate-based optimization approaches that greatly enhance electromagnetics-based optimization performance. On the one hand, we review recent adjoint methodologies, on the other we focus on space mapping implementations, including the original, aggressive, implicit, output, tuning, and related developments. We illustrate our presentation with suitable examples and applications. © 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010.

High frequency characterization of a Schottky contact to a GaN nanowire bundle

A two-port GaN nanowire (NW) device with one Schottky contact and one Ohmic contact was characterized up to 10 GHz using on-wafer microwave measurements. In addition to the measurement of the broadband response, two additional applications of microwave measurements are introduced: (1) the capability to distinguish a Schottky-type contact from an Ohmic contact based on the reflected broadband signals (S11 and S22) and (2) the measurement of a capacitance voltage (CV) curve for a Schottky contact to a bundle of a few NWs. The junction capacitance of the Schottky contact is determined at various bias voltages by fitting the broadband response with a microwave circuit model. The carrier concentration is estimated from the resulting CV curve to be 5.3×1018/cm3 and the Schottky barrier height is estimated to be 0.89 eV.

Microwave circuit model of the three-port transistor laser

Based on an earlier charge control analysis, we have constructed a microwave circuit model of a three-port quantum-well (QW) transistor laser (TL) by extending Kirchhoff’s law to include electron-photon interaction, to yield an electrical-optical form of Kirchhoff’s law. The TL circuit model includes both intrinsic device elements and extrinsic parasitic elements, and fits accurately measured microwave S-parameters upto 20 GHz and matches also measured eye-diagram data up to 13 Gb/s (equipment-limited). The TL model yields both electrical and optical device parameters as well as physical quantities such as QW charge density, nQW∼1016 cm−3, which is useful in the analysis of the device physics of TL operation. The low density indicates that the base QW charge level is not as important as the current driving the QW and supplying electron-hole recombination, and implies that the quasi-Fermi level is discontinuous in the TL base. The model is used to simulate a directly modulated TL up to 40 Gb/s, for example, a TL employed in an optical communication link.

Tuning in to RF MEMS

RF MEMS technology was initially developed as a replacement for GaAs HEMT switches and p-i-n diodes for low-loss switching networks and X-band to mm-wave phase shifters. However, we have found that its very low loss properties (high device Q), its simple microwave circuit model and zero power consumption, its high power (voltage/current) handling capabilities, and its very low distortion properties, all make it the ideal tuning device for reconfigurable filters, antennas and impedance matching networks. In fact, reconfigurable networks are currently being funded at the same level-if not higher-than RF MEMS phase shifters, and in our opinion, are much more challenging for high-Q designs.

Space mapping

In this article we review state-of-the-art concepts of space mapping and place them con- textually into the history of design optimization and modeling of microwave circuits. We formulate a generic space-mapping optimization algorithm, explain it step-by-step using a simple microstrip filter example, and then demonstrate its robustness through the fast design of an interdigital filter. Selected topics of space mapping are discussed, including implicit space mapping, gradient-based space mapping, the optimal choice of surrogate model, and tuning space mapping. We consider the application of space mapping to the modeling of microwave structures. We also discuss a software package for automated space-mapping optimization that involves both electromagnetic (EM) and circuit simulators.

Systematic design and realization of the optical feedforward transmitter based on microwave circuit modeling

AbstractWe have systematically designed and realized the optical feedforward transmitter using microwave circuit model of distributed‐feedback laser diode (DFB LD) based on rate equations. Through the system‐level simulation for the optical feedforward method, the nonlinearity of DFB‐LD is analyzed, and the optimized characteristics of the RF components in the system are confirmed by using a microwave simulator. The experimental and simulated results show the reduced distortion products and enhanced spurious‐free dynamic ranges are in good agreement at 2.4 GHz. These results are analyzed as the evaluation parameters for the miniaturization and optimization of the feedforward compensation method in radio‐over‐fiber systems. © 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 192–195, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.24007