Assessment of thermal instabilities and oscillations in multifinger heterojunction bipolar transistors through a harmonic-balance-based CAD-oriented dynamic stability analysis technique

We present a novel analysis of thermal instabilities and oscillations in multifinger heterojunction bipolar transistors (HBTs), based on a harmonic-balance computer-aided-design (CAD)-oriented approach to the dynamic stability assessment. The stability analysis is carried out in time-periodic dynamic conditions by calculating the Floquet multipliers of the limit cycle representing the HBT working point. Such a computation is performed directly in the frequency domain, on the basis of the Jacobian of the harmonic-balance problem yielding the limit cycle. The corresponding stability assessment is rigorous, and the efficient calculation method makes it readily implementable in CAD tools, thus allowing for circuit and device optimization. Results on three- and four-finger layouts are presented, including closed-form oscillation criteria for two-finger device

Physics-based large-signal sensitivity analysis of microwave circuits using technological parametric sensitivity from multidimensional semiconductor device models

The authors present an efficient approach to evaluate the large-signal (LS) parametric sensitivity of active semiconductor devices under quasi-periodic operation through accurate, multidimensional physics-based models. The proposed technique exploits efficient intermediate mathematical models to perform the link between physics-based analysis and circuit-oriented simulations, and only requires the evaluation of dc and ac small-signal (dc charge) sensitivities under general quasi-static conditions. To illustrate the technique, the authors discuss examples of sensitivity evaluation, statistical analysis, and doping profile optimization of an implanted MESFET to minimize intermodulation which makes use of LS parametric sensitivities under two-tone excitatio

Dynamic, self consistent electro-thermal simulation of power microwave devices including the effect of surface metallizations

We present an efficient simulation technique to account for the thermal spreading effects of surface metallizations in the self-consistent dynamic electro-thermal analysis of power microwave devices. Electro-thermal self-consistency is achieved by solving the coupled nonlinear system made of a temperature dependent device electrical model, and of an approximate description of the device thermal behavior through a thermal impedance matrix. The numerical solution is pursued in the frequency domain by the Harmonic Balance technique. The approach is applied to the thermal stability analysis of power AlGaAs/GaAs HBTs and the results show that metallizations have a significant impact on the occurrence of the device thermal collapse

Efficient spectral domain technique for the frequency locking analysis of nonlinear oscillators

After discussing an implementation of the harmonic balance technique that enables the efficient determination of the limit cycles for a nonlinear autonomous dynamical system, we consider the frequency locking of a set of oscillators that is studied by means of a proper extension of the aforementioned approach. Harmonic balance is also used for the numerical computation of the Floquet exponents and eigenvectors of the frequency locked limit cycle, thus enabling the assessment of its stability properties. The proposed technique is applied to the study of the frequency locking properties of a set of coupled Chua’s oscillators as a function of several parameters

Linking X Parameters to Physical Simulations for Design-Oriented Large-Signal Device Variability Modeling

We propose various techniques extending X parameters to include the effect of active microwave device variability by exploiting TCAD simulations. We discuss two possible implementations into Agilent ADS. Both approaches are validated against full microwave amplifier TCAD simulations

Cyclostationary noise modeling of radio frequency devices

We present a review of the current status of research in the modeling and simulation of cyclostationary (nonlinear) noise properties of semiconductor active devices operated in forced large-signal conditions, a typical operating regime for high-frequency applications. We discuss both the case of physics-based device simulations, where numerical burden is the most important issue, and the derivation of compact cyclostationary noise models. In the latter case, both phenomenological amplitude modulation approaches and the derivation of consistent analytical device descriptions are discussed. We show examples of both physics-based simulations of the noise properties of a realistic high-electron mobility transistor resistive mixer and show for the first time the application of a novel, fully analytical cyclostationary noise bipolar transistor model

Memcomputing NP-complete problems in polynomial time using polynomial resources and collective states

Memcomputing is a novel non-Turing paradigm of computation that uses interacting memory cells (memprocessors for short) to store and process information on the same physical platform. It was recently proven mathematically that memcomputing machines have the same computational power of nondeterministic Turing machines. Therefore, they can solve NP-complete problems in polynomial time and, using the appropriate architecture, with resources that only grow polynomially with the input size. The reason for this computational power stems from properties inspired by the brain and shared by any universal memcomputing machine, in particular intrinsic parallelism and information overhead, namely, the capability of compressing information in the collective state of the memprocessor network. We show an experimental demonstration of an actual memcomputing architecture that solves the NP-complete version of the subset sum problem in only one step and is composed of a number of memprocessors that scales linearly with the size of the problem. We have fabricated this architecture using standard microelectronic technology so that it can be easily realized in any laboratory setting. Although the particular machine presented here is eventually limited by noise—and will thus require error-correcting codes to scale to an arbitrary number of memprocessors—it represents the first proof of concept of a machine capable of working with the collective state of interacting memory cells, unlike the present-day single-state machines built using the von Neumann architecture

PA design and statistical analysis through X-par driven load-pull and EM simulations

Modeling the active device is a key step for the successful statistical analysis of power amplifiers: the nonlinear model must not only depend on the most relevant device fabrication parameters, but should also work accurately in source/load-pull analysis, since variations of the passive embedding network effectively act as a load-pull at the active device ports. We demonstrate that the X-parameter model extracted from physics-based nonlinear TCAD simulations is extremely accurate for load-pull analysis. The X-parameter model is coupled to electromagnetic simulations to assist the variability-aware design of a GaAs MMIC X-band power amplifier (PA): concurrent variations of the active device doping and of the capacitor dielectric layer thickness are considered as the main contributions to PA variability. Two possible output matching networks, with distributed or semi-lumped design, are compared: already for moderate doping variations the PA output power spread is dominated by the active device variability, while passive network variations are always the relevant contribution to PA efficiency