Behavioral models of digital IC ports from measured transient waveforms

This paper addresses the behavioral modeling of output ports of digital integrated circuits via the identification of nonlinear parametric models. The aim of the approach is to produce models for signal integrity (SI) simulation directly from the measured transient responses of the devices. The modeling process is thoroughly described and an experimental demonstration of its feasibility is give

Behavioral Modeling of Nonlinear Circuit Elements: Application to Signal Integrity and Electromagnetic Compatibility

Nowadays the availability of computational models of nonlinear dynamic components is becoming a key requirement for the analysis and design of complex systems. The complexity of many components, however, as well as the lack of information on their internal structure often prevent from the development of traditional physical models. This scenario raise the interest for behavioral models, which are models obtained from the observation of the external behavior of components. In this thesis we focus on the development of behavioral models for the assessment of Signal Integrity (SI) and ElecroMagnetic Compatibility (EMC) effects on fast digital circuits. Such an assessment, that is mainly achieved by simulating the evolution of signals sent on interconnects by digital integrated circuits (ICs), requires e±cient and accurate models of IC ports driving and loading the interconnects themselves. The required models must allow the simulation of large realistic problems and must performs at an accuracy level useful to the prediction of sensitive effects, like crosstalk and radiation. Behavioral models meet such requirements and are establishing as the best tools for the description of IC ports. We analyze possible behavioral modeling methods for IC ports and concentrate on behavioral modeling via black-box identification. It amounts to the selection of a suitable parametric model and to the estimation of its parameters from measured transient responses. The selection of a suitable class of parametric models leads to Radial Basis Function (RBF) representations, that offer many advantages in the modeling of systems with strong nonlinear nature and multiple inputs. We developed a simplified RBF model that can be obtained from measured port voltage and current. The estimation of such model is simple and relies on a robust algorithm. In order to test the effectiveness of the proposed approach and its feasibility, we apply it to the modeling of several virtual devices and to an actualdevice of interest. The obtained models perform at a fairly good accuracy and effciency levels and turn out to be weakly sensitive to driven loads and measurement setup. Besides, since the model structure is selected by the estimation process itself, all the relevant physical effects relating input and output signals (e.g., substrate or packaging effects) are automatically taken into accoun

Polynomial Chaos Helps Assessing Parameters Variations of PCB Lines

This paper presents an effective solution for the analysis of long PCB interconnects with the inclusion of uncertainties resulting from different sources of variation, like temperature or fabrication process, on both the structure and loading conditions. The proposed approach is based on the expansion of the well-known frequency-domain telegraph equations in terms of orthogonal polynomials. The method is validated by means of a systematic comparison with the results of Monte Carlo simulations, for an application example involving a coupled-microstrip interconnect on PC

Alternative SPICE Implementation of Circuit Uncertainties Based on Orthogonal Polynomials

The impact on circuit performance of parameters uncertainties due to possible tolerances or partial information on devices can be effectively evaluated by describing the resulting stochastic problem in terms of orthogonal polynomial expansions of electrical parameters and of circuit voltages and currents. This contribution formalizes a rule for the construction of an augmented instance of the original circuit, that provides a systematic solution approach for the unknown coefficients of the expanded electrical variables. The use of SPICE as a solution engine of the augmented circuit is straightforward, thus providing a convenient and efficient alternative to the conventional approach SPICE uses for uncertainty analysis. An application example involving the stochastic simulation of a digital link with variable substrate parameters demonstrates the potential of the proposed approach

Power line communication channel modeling for in-vehicle applications

This paper addresses the problem of generating an accurate power line communication channel model for in-vehicle applications. The proposed modeling methodology is based on a state-of-the-art behavioral representation based on the multipath propagation of signals in a possibly complicated interconnected power structure. The procedure for the computation of model parameters is thoroughly discussed. The effectiveness of the approach has been demonstrated on a set of real measurements carried out on a commercial automobil

Stochastic Evaluation of Parameters Variability on a Terminated Signal Bus

This paper addresses the simulation of the effects on a high-speed data link of external factors due to fabrication tolerances or uncertain loading conditions. The proposed strategy operates in the frequency domain and amounts to generating a suitable set of stochastic models for the different blocks in which the data link can be decomposed. Each model is based on the expansion of the block chain parameter matrix in terms of orthogonal polynomials. This method turns out to be accurate and more efficient than alternative solutions like the Monte Carlo method in determining the system response sensitivity to parameters variability. The advantages of the proposed approach are demonstrated via the stochastic simulation of a PCB application exampl

Performance of Modal Signaling vs. medium dielectric variability

This paper addresses the feasibility of the so-called Modal Signaling (MS) transmission scheme from a stochastic viewpoint. MS has been proposed for crosstalk mitigation over interconnects and is based on the encoding of signals onto fundamental transmission-line modes. However, the design of drivers and receivers strongly depends on the physical characteristics of the channel. In this paper, the impact of random variations of these properties on MS effectiveness is efficiently analyzed by means of Polynomial Chaos (PC) techniqu