Radio Frequency Circuit Design Research Articles

Straightforward bias- and frequency-dependent small-signal model extraction for single-layer graphene FETs

We propose an explicit small-signal graphene field-effect transistor (GFET) parameter extraction procedure based on a charge-based quasi-static model. The dependence of the small-signal parameters on both gate voltage and frequency is precisely validated by high-frequency (up to 18 GHz) on-wafer measurements from a 300 nm device. These parameters are studied simultaneously, in contrast to other works which focus exclusively on few. Efficient procedures have been applied to GFETs for the first time to remove contact and gate resistances from the Y-parameters. The use of these methods yields straightforward equations for extracting the small-signal model parameters, which is extremely useful for radio-frequency circuit design. Furthermore, we show for the first time experimental validation vs. both gate voltage and frequency of the intrinsic GFET non-reciprocal capacitance model. Accurate models are also presented for the gate voltage-dependence of the measured unity-gain and maximum oscillation frequencies as well as of the current and power gains.

Addressing a New Class of Multi-Objective Passive Device Optimization for Radiofrequency Circuit Design

The design of radiofrequency circuits and systems lends itself to multi-objective optimization and the bottom-up composition of Pareto-optimal fronts. Conventional multi-objective optimization algorithms can effectively attain these fronts, which maximize or minimize a set of competing objective functions of interest. However, some of these real-life optimization problems reveal a non-conventional feature: there is one objective function that calls neither for minimization nor maximization. Instead, using the Pareto front demands this objective function to be swept across so that all its feasible values are available. Such a non-conventional feature, as shown here, emerges in the case of inductor optimization. The problem thus turns into a non-conventional one: determining how to find uniformly distributed feasible values of this function over the broadest possible range (typically unknown) while minimizing or maximizing the remaining competing objective functions. An NSGA-II-inspired algorithm is proposed that, based on the dynamic allocation of objective function slots and a modified dominance definition, can successfully return sets of solutions for inductor optimization problems with one sweeping objective. Furthermore, a mathematical benchmark function modeling this kind of problem is presented, which is also used to exhaustively test the proposed algorithm and obtain insight into its parameter settings.

Complex Permittivity and Permeability Extraction of Ferromagnetic Materials For Magnetically Tuned Microwave Circuits

Ferromagnetic materials, such as ferrites, are employed for magnetically tuned radio frequency (RF) circuits. Ferrites exhibit both electric permittivity and magnetic permeability and independent RF characterization of these two properties is crucial for accurate design and modeling of RF circuits. A method that independently extracts each property over Wi-Fi frequencies is presented here, where complex permittivity and permeability of ferrite nano-particles are extracted using resonance frequency sensitivity of a 3D printed metallic cavity to various samples under test and their placement in the cavity. Air-filled 3D printed rectangular cavity using acrylonitrile butadiene styrene (ABS) are shielded using copper sheets; the structure of air-filled cavity is designed to excite TE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">101z</sub> as the dominant resonance mode that resonates at 2.4 GHz. A cylindrical shape material under test (MUT) was added to the cavity at different positions for high electric and magnetic fields, while the resonant frequency change and degradation in quality factor of the resonant cavity are employed for accurate independent extraction of electric permittivity and magnetic permeability of MUT. The sample was prepared with volumetric distribution of 60:40 nanoparticles to glue ratio. In particular, a 3D printed composite sample of ABS with NiFe <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> O <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sub> magnetic nanoparticles is placed in positions of high electric or high magnetic energy densities of the metallic cavity, while any changes in resonant frequency and its frequency selectivity are observed from the cavity insertion loss characteristics. Both perturbation theory (as analytical) and finite element method (as numerical) techniques are employed for extraction of complex permittivity and permeability of NiFe <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> O <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sub> . The perturbation theory provides accurate extraction, which is also numerically confirmed using curve fitting of the full wave simulated scattering parameters to the measured results.

Optimization techniques for analog and RF circuit designs: an overview

Optimizations have gained much consideration from the researchers working in the domains of analog and radio frequency (RF), recently. Dealing with highly nonlinear behavior of active components and aiming to meet design specifications are common issues in all nonlinear circuit designs. As a consequence and accordingly, many studies have been conducted on diverse optimization methods and algorithms for tackling the design problems and meeting optimal solutions with high accuracy. The main purpose of this article is to provide a comprehensive and systematic literature review for the optimization approaches applied by the researchers for designing various analog and microwave circuits. We focus on considering the existing optimization methods from the newly published optimization methods in the last decade. Thus, this study can guide and enlighten complementary metal-oxide-semiconductor analog and RF microwave circuit designers to consider optimization methods commonly used in both areas and to expand conventional performance figures used in their area.

Broadband RF Characterization and Extraction of Material Properties in 3-D Printed Composite Substrates for Magnetically Tuned Circuits

3-D additive printing technology has been employed recently for the manufacturing of a wide variety of tunable radio frequency (RF) components. In particular, this article is focused on the extraction of magnetically tuned 3-D printed materials suitable for RF circuits. The design and modeling of tunable RF circuits require an accurate electromagnetic (EM) characterization of the 3-D printed dielectric [polylactide (PLA)] as a primary substrate, magnetic particles (CoFeO) as the tunable component in the composite substrate, and copper traces at RF frequencies. The extraction of complex permittivity, permeability, and conductivity parameters is reported over broadband (50–7000 MHz) and narrowband Wi-Fi bands (2.4 and 5.4 GHz) using the best fitting of EM simulated to measured scattering ( $S$ ) parameters. Broadband characterization is performed using best-fit modeling of three different physical lengths of microstrip transmission lines that are fabricated on unknown 3-D printed PLA substrates. Error analysis of this approach was evaluated on commercially available RT/Duroid substrate as a baseline. An accurate narrowband extraction procedure around the resonance frequency of 3-D printed annular ring resonators (ARRs) at 2.4 and 5.4 GHz is performed by the best fitting of simulated material RF properties to measured results. Further modeling improvements are presented through completely 3-D printed circuits that include the bottom and top copper traces with extracted conductivity of one tenth of bulk copper. Moreover, a 50-MHz tuning of ARR operating at Wi-Fi bands is observed and complex permeabilities are extracted at zero and 2-kG external magnetic field for the 3-D printed composite substrate.

RF Matching Networks Using S-Parameters

The paper presents a design and study of impedance matching for radio frequency (RF) circuit application of common-source amplifier topology. Matching networks for input and output sides of the amplifier were determined from the S-parameters given for the transistor at frequency of 2.6 GHz and ensuring unconditional stability requirement. Impedance matching is necessary in RF circuit design to provide maximum possible power transfer between the source and the load. Two designs were modeled, simulated and analyzed employing L-network input and output matching networks. The design with inductor-capacitor combination in the L-matching networks exhibited a stable and smoother behavior for higher frequencies compared to an all-inductor design. Complex tradeoffs among technology specifications and design parameters are inevitable, therefore should be carefully handled in designing the impedance matching networks, to optimize the performance of the common-source amplifier. Ultimately, the common-source amplifier achieved a gain of 6.569 dB at 2.6 GHz. For future research, physical implementations of the impedance matching networks could be studied in order to improve and optimize the simulated models.

Ready-to-Fabricate RF Circuit Synthesis Using a Layout- and Variability-Aware Optimization-Based Methodology

In this paper, physical implementations and measurement results are presented for several Voltage Controlled Oscillators that were designed using a fully-automated, layout- and variability-aware optimization-based methodology. The methodology uses a highly accurate model, based on machine-learning techniques, to characterize inductors, and a multi-objective optimization algorithm to achieve a Pareto-optimal front containing optimal circuit designs offering different performance trade-offs. The final outcome of the proposed methodology is a set of design solutions (with their GDSII description available and ready-to-fabricate) that need no further designer intervention. Two key elements of the proposed methodology are the use of an optimization algorithm linked to an off-the-shelf simulator and an inductor model that yield EM-like accuracy but with much shorter evaluation times. Furthermore, the methodology guarantees the same high level of robustness against layout parasitics and variability that an expert designer would achieve with the verification tools at his/her disposal. The methodology is technology-independent and can be used for the design of radio frequency circuits. The results are validated with experimental measurements on a physical prototype.

A Comparison of Automated RF Circuit Design Methodologies: Online Versus Offline Passive Component Design

In this paper, surrogate modeling techniques are applied for passive component modeling. These techniques are exploited to develop and compare two alternative strategies for automated radio-frequency circuit design. The first one is a traditional approach where passive components are designed during the optimization stage. The second one, inspired on bottom-up circuit design methodologies, builds passive component Pareto-optimal fronts (POFs) prior to any circuit optimization. Afterward, these POFs are used as an optimized library from where the passive components are selected. This paper exploits the advantages of evolutionary computation algorithms in order to efficiently explore the circuit design space, and the accuracy and efficiency of surrogate models to model passive components.

Design of Impedance Matching Networks for RF Applications

This technical paper presents a design and study of impedance matching for RF (radio frequency) circuit application of common-source amplifier topology. Input and output matching networks of the amplifier were designed and computed ensuring unconditional stability. Inductors and capacitors are key passive components that are crucial for impedance matching, and are specifically designed such that they would satisfy the gain requirements at a specific frequency of operation. Impedance matching is necessary in RF circuit design to provide maximum possible power transfer between the source or the generator and the load. Complex tradeoffs among technology specifications and design parameters exist and should be carefully handled when designing the impedance matching networks, to optimize the performance of the amplifier.Â

Device and Compact Circuit-Level Modeling of Graphene Field-Effect Transistors for RF and Microwave Applications

Graphene field-effect transistors (GFETs) are promising candidates for future nano-electronic circuitry with excellent radio frequency (RF) and microwave performance due to the ultra-high carrier mobility, large saturation velocity, and good electrical conductivity of the graphene channel. In this paper, a compact circuit-level model of GFETs is proposed for RF and microwave high-frequency applications. An improved double-gate monolayer short channel GFET with an agate length of 150 nm was first designed and fabricated by self-aligned gate processing, enabled by optimized organic, contamination-free graphene transfer, for realizing high working frequency up to 40 GHz. A compact, precise circuit-level model, including the linear and nonlinear operation of GFETs, is then proposed with model parameters extracted based on the test data from the fabricated GFETs. The proposed model is capable of precisely simulating the ambipolar status of GFETs working up to microwave frequency. The calculated errors of the S-parameters, the reflection coefficient, the gain, (all in decibel), and the I–V data (in decimal) are less than 3.5%, 4.1%, 3.1%, and 2.4%, respectively. By defining as the symbolically defined device module, the GFET model with gate dimensional scalability can be easily embedded in the common commercial simulators for RF and microwave circuit and system level designs.

A two-step surrogate modeling strategy for single-objective and multi-objective optimization of radiofrequency circuits

The knowledge-intensive radiofrequency circuit design and the scarce design automation support play against the increasingly stringent time-to-market demands. Optimization algorithms are starting to play a crucial role; however, their effectiveness is dramatically limited by the accuracy of the evaluation functions of objectives and constraints. Accurate performance evaluation of radiofrequency passive elements, e.g., inductors, is provided by electromagnetic simulators, but their computational cost makes their use within iterative optimization loops unaffordable. Surrogate modeling strategies, e.g., Kriging, support vector machines, artificial neural networks, etc., arise as a promising modeling alternative. However, their limited accuracy in this kind of applications has prevented a widespread use. In this paper, inductor performance properties are exploited to develop a two-step surrogate modeling strategy in order to evaluate the behavior of inductors with high efficiency and accuracy. An automated design flow for radiofrequency circuits using this surrogate modeling of passive components is presented. The methodology couples a circuit simulator with evolutionary computation algorithms such as particle swarm optimization, genetic algorithm or non-dominated sorting genetic algorithm (NSGA-II). This methodology ensures optimal performances within short computation times by avoiding electromagnetic simulations of inductors during the entire optimization process and using a surrogate model that has less than 1% error in inductance and quality factor when compared against electromagnetic simulations. Numerous real-life experiments of single-objective and multi-objective low-noise amplifier design demonstrate the accuracy and efficiency of the proposed strategies.

Analytical design technique for real‐to‐real single‐ and dual‐frequency impedance matching networks in lossy passive environment

A passive-loss accounted analytic design technique for impedance matching networks is proposed here for efficient radio frequency (RF) circuit design. The impact of component losses on matching performance is briefed initially. To overcome the matching impact due to component losses, a set of modified equations are introduced which finds the accurate inductor and capacitor values accounting component losses. The proposed technique is applied for single-frequency L-match, Pi-match, Tmatch and dual-frequency L-match networks. The improvement in matching performance by using the proposed design technique is validated through simulations and measurements in UMC 0.18 μm complementary metal oxide semiconductor technology. The measurement results closely (90-95%) follow ideal component performance. Hence, the proposed passive-loss accounted design technique will be more useful in accurate low power RF circuit design.

Radio-frequency inductor synthesis using evolutionary computation and Gaussian-process surrogate modeling

In recent years, the application of evolutionary computation techniques to electronic circuit design problems, ranging from digital to analog and radiofrequency circuits, has received increasing attention. The level of maturity runs inversely to the complexity of the design task, less complex in digital circuits, higher in analog ones and still higher in radiofrequency circuits. Radiofrequency inductors are key culprits of such complexity. Their key performance parameters are inductance and quality factors, both a function of the frequency. The inductor optimization requires knowledge of such parameters at a few representative frequencies. Most common approaches for optimization-based radiofrequency circuit design use analytical models for the inductors. Although a lot of effort has been devoted to improve the accuracy of such analytical models, errors in inductance and quality factor in the range of 5%–25% are usual and it may go as high as 200% for some device sizes. When the analytical models are used in optimization-based circuit design approaches, these errors lead to suboptimal results, or, worse, to a disastrous non-fulfilment of specifications. Expert inductor designers rely on iterative evaluations with electromagnetic simulators, which, properly configured, are able to yield a highly accurate performance evaluation. Unfortunately, electromagnetic simulations typically take from some tens of seconds to a few hours, hampering their coupling to evolutionary computation algorithms. Therefore, analytical models and electromagnetic simulation represent extreme cases of the accuracy-efficiency trade-off in performance evaluation of radiofrequency inductors. Surrogate modeling strategies arise as promising candidates to improve such trade-off. However, obtaining the necessary accuracy is not that easy as inductance and quality factor at some representative frequencies must be obtained and both performances change abruptly around the self-resonance frequency, which is particular to each device and may be located above or below the frequencies of interest. Both, offline and online training methods will be considered in this work and a new two-step strategy for inductor modeling is proposed that significantly improves the accuracy of offline methods The new strategy is demonstrated and compared for both, single-objective and multi-objective optimization scenarios. Numerous experimental results show that the proposed two-step approach outperforms simpler application strategies of surrogate modelling techniques, getting comparable performances to approaches based on electromagnetic simulation but with orders of magnitude less computational effort.

An inductor modeling and optimization toolbox for RF circuit design

This paper describes the SIDe-O toolbox and the support it can provide to the radio-frequency designer. SIDe-O is a computer-aided design toolbox developed for the design of integrated inductors based on surrogate modeling techniques and the usage of evolutionary optimization algorithms. The models used feature less than 1% error when compared to electromagnetic simulations while reducing the simulation time by several orders of magnitude. Furthermore, the tool allows the creation of S-parameter files that accurately describe the behavior of inductors for a given range of frequencies, which can later be used in SPICE-like simulations for circuit design in commercial environments. This toolbox provides a solution to the problem of accurately and efficiently optimizing inductors, which alleviates the bottleneck that these devices represent in the radio-frequency circuit design process.

Design methodology for low power RF LNA based on the figure of merit and the inversion coefficient

The complexity of radiofrequency circuit design comes from the large number of parameters to be adjusted. Constant node shrink in CMOS process and variation of technology skills significantly contr...

Tunable Compact Low-Noise Amplifier With Permalloy Thin-Film Enabled Slow-Wave Transmission Lines

This paper provides a first tunable low-noise amplifier (LNA) design with Permalloy (Py) enabled inductors. Tunable inductor is an important passive device in adaptive radio frequency circuit design. In this paper, a new integrated tunable inductor is implemented utilizing novel slow-wave transmission lines that are built with coplanar waveguide having alternative high and low impedance signal sections, and the Py thin films are deposited and patterned on the signal line of narrow section to provide higher and tunable inductance density. The inductance per unit length has been increased from 877 to 949 nH/m with 100 nm Py thin film at 5 GHz. A tunable 5 GHz LNA utilizing SWLTs is developed, where the tunability of power reflection and power gain of LNA are demonstrated with variable inductors.

Graphene Field Effect Transistor’s Circuit Modeling and Radio Frequency Application Study

In this paper, a large signal circuit model of graphene field effect transistor (GFET) is described accurately by Verilog-A language, which is suitable for radio frequency circuit design and can be applied in HSPICE and ADS directly. Then two typical radio frequency (RF) circuits, frequency multiplier and mixer, are based on this GFET circuit model. The proposed circuits’ performance are analyzed respectively in 10GHz, 15GHz and 20GHz, and GFET’s application foreground in radio frequency area is discussed.

Design and evaluation of a 1.1-GHz surface coil resonator for electron paramagnetic resonance-based tooth dosimetry.

This paper describes an optimized design of a surface coil resonator for in vivo electron paramagnetic resonance (EPR)-based tooth dosimetry. Using the optimized resonator, dose estimates with the standard error of the mean of approximately 0.5 Gy were achieved with irradiated human teeth. The product of the quality factor and the filling factor of the resonator was computed as an index of relative signal intensity in EPR tooth dosimetry by the use of 3-D electromagnetic wave simulator and radio frequency circuit design environment (ANSYS HFSS and Designer). To verify the simulated results of the signal intensity in our numerical model of the resonator and a tooth sample, we experimentally measured the radiation-induced signals from an irradiated tooth with an optimally designed resonator. In addition to the optimization of the resonator design, we demonstrated the improvement of the stability of EPR spectra by decontamination of the surface coil resonator using an HCl solution, confirming that contamination of small magnetic particles on the silver wire of the surface coil had degraded the stability of the EPR spectral baseline.

Using modern RF tools to detect chaotic behaviour of electronic circuits and systems

In this paper, a new approach in identifying chaotic behaviour of nonlinear circuits is presented. This approach could be very useful to circuit designers, whether they pursue a chaotic behaviour or not. Simulation tools used for radio-frequency circuit design (Cadence SpectreRF), initially developed to characterise harmonic oscillators, are now utilised to detect chaotic behaviour, as well as routes to chaotic mode of operation. Specifically, Periodic Steady State Convergence Norm is used for the first time for chaos detection in circuits. The advantages of this method (especially in terms of simulation time) are presented, together with an example of detection of chaotic route to chaos in the case of a chaotic-operating Colpitts oscillator.

Operating Voltage Constraints in 45-nm SOI nMOSFETs and Cascode Cores

We investigate the operating voltage constraints and hot carrier reliability (HCR) of 45-nm SOI RF nMOSFETs and cascode cores built from these devices. The devices were implemented with both “floating” body and “contacted” body schemes. It is shown through experimental results that floating-body (FB) devices have greater hot carrier degradation compared with body-contacted (BC) devices. Cascode cores designed with two FB devices (FB-FB), with one BC device and one FB device (BC-FB), and with two BC devices (BC-BC), were also investigated. The tradeoffs in the dc versus radio-frequency (RF) performance versus the HCR of these cascode cores were assessed. The cascode cores have a much longer reliability lifetime compared with a single device operating under similar stress conditions. The BC-BC cascode core is shown to have a much longer reliability lifetime compared with BC-FB and FB-FB cascode core topologies. The physical mechanisms behind the observed hot carrier degradation in these devices and cascode cores are explored using calibrated technology computer-aided design (TCAD) simulations. Taken together, these results suggest some important implications for realizing high-performance and high-reliability RF circuit designs using 45-nm CMOS-on-SOI technology.