Roni Khazaka

Passive parameterized time-domain macromodels for high-speed transmission-line networks

There is a significant need for efficient and accurate macromodels of components during the design of microwave circuits. Increased integration levels in microwave devices and higher signal speeds have produced the need to include effects previously neglected during circuit simulations. Accurate prediction of these effects involve solution of large systems of equations, the direct simulation of which is prohibitively CPU expensive. In this paper, an algorithm is proposed to form passive parametrized macromodels of large linear networks that match the characteristics of the original network in time, as well as other design parameters of the circuit. A novel feature of the algorithm is the ability to incorporate a set of design parameters within the reduced model. The size of the reduced models obtained using the proposed algorithm were less than 5% when compared to the original circuit. A speedup of an order of magnitude was observed for typical high-speed transmission-line networks. The algorithm is general and can be applied to other disciplines such as thermal analysis.

Analysis of transmission line circuits using multi-dimensional model reduction techniques

This paper presents a new technique to reduce the order of transmission line circuits simultaneously with respect to multiple parameters. The reduction is based on multi-dimensional congruence transformation. The proposed algorithm provides efficient means to estimate the response of large distributed circuits simultaneously as a function of frequency and other design parameters.

Circuit reduction technique for finding the steady state solution of nonlinear circuits

Computing the steady state response of large nonlinear circuits is becoming a key simulation requirement due to the rapid market growth of RF silicon ICs. In this paper we describe a nonlinear circuit reduction algorithm for finding the steady state response. The proposed algorithm uses a congruent transformation-based technique to reduce the harmonic balance equations into a much smaller set of equations. The main feature of the reduced circuit is that it shares with the original one a certain number of the derivatives w.r.t. the RF input power. Steady state analysis is then done on the reduced circuit instead of the original circuit.

Simulation of high-speed interconnects in a multilayered medium in the presence of incident field

Simulation of high-speed circuits and interconnects in the presence of incident electromagnetic interference is becoming an important step in the design cycle. An accurate and efficient method for the analysis of incident field coupling to traces in inhomogeneous medium is described. The method is based on the application of the physical optics technique. An interconnect circuit simulation stamp is derived. This stamp provides an easy link to current simulators and to recently developed model reduction techniques. In addition to accounting for the inhomogeneity of the medium, this method provides significant computational efficiency improvement over conventional approaches.

A circuit reduction technique for finding the steady-state solution of nonlinear circuits

Computing the steady-state response of large nonlinear circuits is becoming a key simulation requirement due to the rapid market growth of RF silicon integrated circuits. In this paper, we describe a nonlinear circuit reduction algorithm for finding the steady-state response. The proposed algorithm uses a congruent transformation-based technique to reduce the harmonic-balance equations into a much smaller set of equations. The main feature of the reduced circuit is that it shares with the original one a certain number of the derivatives with respect to the RF input power, steady-state analysis is then carried out on the reduced circuit instead of the original circuit.

A transition from substrate integrated waveguide (SIW) to rectangular waveguide

In this work, a simple and compact transition from substrate integrated waveguide (SIW) to traditional rectangular waveguide is proposed and demonstrated. The substrate of SIW can be easily surface-mounted to the standard flange of the waveguide by creating a flange on the substrate. A longitudinal slot window etched on the broad wall of SIW couples energy between SIW and rectangular waveguide. An example of the transition structure is realized at 35 GHz with substrate of RT/Duroid 5880. HFSS simulated result of the transition shows a return loss less than −15 dB over a frequency range of 800 MHz. A back to back connected transition has been fabricated, and the measured results confirm well with the anticipated ones.

Parametric model order reduction technique for design optimization

Model order reduction has proven to be an effective tool for dealing with the computational complexity that arises during the simulation of large interconnect networks. However, in the case of parametric reduced order models, the effectiveness of traditional reduction methods is dependent on the number of moments and cross moments required to construct the orthonormal basis used in the congruence transformation. This can result in a relatively large reduced system in cases when the number of parameters is large. We propose a new approach for constructing the orthonormal basis that is not directly dependent on the moments. This new technique reduces a circuit with respect to many parameters by using singular value decomposition as a tool to filter out redundant information from the original subspaces. The result is a parametric reduced order model that is smaller, but still conserves the essential behavior of the original circuit as a function of frequency and other circuit parameters.

Efficient sensitivity analysis of transmission-line networks using model reduction techniques

An analysis method, based on congruent transformation and model reduction, is described for evaluation of frequency and time domain sensitivity of networks which include lossy coupled transmission lines. The sensitivity can be calculated with respect to network components and parameters of transmission lines. The proposed algorithm provides a significant decrease in computational expense for sensitivity analysis.

Macromodeling of Distributed Networks From Frequency-Domain Data Using the Loewner Matrix Approach

Recently, Loewner matrix (LM)-based methods were introduced for generating time-domain macromodels based on frequency-domain measured parameters. These methods were shown to be very efficient and accurate for lumped systems with a large number of ports; however, they were not suitable for distributed transmission-line networks. In this paper, an LM-based approach is proposed for modeling distributed networks. The new method was shown to be efficient and accurate for large-scale distributed networks.

Parameterized Model Order Reduction Techniques for FEM Based Full Wave Analysis

As operating frequencies increase full wave methods such as the finite element method (FEM) become necessary for the analysis of high-frequency circuit structures. Such techniques result in very large systems of equations, and model order reduction (MOR) was proven to be very effective in combating such increased complexity. Using traditional MOR, one has to generate a new reduced model each time a design parameter is modified, thus significantly reducing the CPU efficiency. In this paper, a multidimensional Krylov subspace method is proposed to perform reduction directly on the vector wave equation based FEM system and to generate parametric reduced order models that are valid over the desired parameter range without the need to redo the reduction. In order to accomplish this, second-order Arnoldi methods are extended to include design parameters such as material properties, and geometrical parameters in the reduced order model. In addition, multidimensional moment matching technique is used to address the Krylov incompatibility of FEM problems which include arbitrary frequency dependence in the system. This technique results in significant CPU savings and enables applications such as optimization and design space exploration.