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Item type:Publication, Access status: without files , Behavior of crosstalk in environmentally-impacted automotive PCB interconnects and effect on signal transmission(IEEE, 2026-06); ; ; ; In the automotive industry, interconnect design is impacted by the operational conditions (temperature and humidity) encountered in practice. This paper extends the use of environmentally-dependent dielectric and conductor models, derived in our previous work, to evaluate key metrics for simulated crosstalk-impacted links operating under practical vehicle conditions up to 40 GHz. These metrics include power sum near- and far-end crosstalk (PSNEXT and PSFEXT), and the interconnect crosstalk ratio (ICR). Herein, an analysis of the dependency on temperature and moisture content of crosstalk metrics is presented for two interconnect configurations based on single-ended and differential signaling. Initial observations for PSNEXT and ICR show negligible variation under harsh environmental conditions while PSFEXT shows a considerable reduction as frequency increases.Publicationtype: Conference Paper6 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Data-driven prediction of temperature-dependent dielectric and conductive parameters based on differential stripline characteristics(IEEE, 2025-05); ; ; The design of automotive high-speed interconnects requires the use of broadband material models that consider a wide range of environmental conditions, e.g. temperature and humidity. However, even for nominal conditions these models are nontrivial to generate. This paper extends our previous work on data-driven predictors used for the estimation of dielectric and conductive parameters of high-speed material models. Parametrized frequency-domain simulations of a differential stripline at various temperatures yield a dataset of modal propagation constants, and characteristic impedances up to 25 GHz. These inputs are used to train a 1D Convolutional Neural Network to estimate the temperature-dependent conductive and dielectric model parameters for the cannoball Huray and wideband Debye models, respectively. The trained model shows good accuracy after training/testing. Additional simulations outside the training/test dataset are used for further model validation with good agreement between predictions and expected values.Publicationtype: Conference Paper5 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Design challenges for high-speed digital links for automotive applications(IEEE, 2025-03-26); ; 20 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Uncertainty quantification of the insertion loss of an automotive PCB stripline(IEEE, 2024-05); ; In this combination of measurement and modeling, the relative effect of process variations present in the cross-section dimensions and material properties of two automotive printed circuit boards (PCBs), with 10-inch striplines is studied. Specifically, the insertion loss (IL) uncertainty up to 20 GHz. The PCBs were horizontally cut into fifteen cross-section samples each. Normal distributions were obtained after measurements of their physical dimensions and for the PCB dielectric properties, a uniform distribution was selected. The measured distributions in combination with assumed stochastic variations for the dielectric properties of the striplines were used to simulate a 2D cross-section via an electromagnetic (EM) 2D- Method of Moments (MoM) solver. The sensitivities due to the input variables were obtained through a second order polynomial chaos expansion (PCE) in two different analysis. The first case focused on the measured physical dimensions variability and showed that the conductor roughness had the biggest effect on the IL uncertainty. The second case analyzed the combination between measured data and the assumed stochastic variation of the dielectric properties; and showed a bigger dependence of the IL uncertainty due to the dielectric properties than the physical dimensions.Publicationtype: Conference Paper15 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Modeling electrically long interconnects using physics-informed delayed gaussian processes(IEEE, 2023-12-01); ; ; Dhaene, TomThis work presents a machine learning technique to model wide-band scattering parameters (S-parameters) of interconnects in the frequency domain using a new Gaussian processes (GP) model. Standard GPs with a general-purpose kernel typically assume high smoothness and therefore are not suitable to model S-parameters that are highly dynamic and oscillating due to propagation delays. The new delayed Gaussian process (<inline-formula><tex-math notation="LaTeX">$\tau$</tex-math></inline-formula>GP) model employs a physics-informed kernel consisting of periodic components, whose fundamental frequencies are interpreted as tunable propagation delays. Then, the model hyperparameters are tuned using a combination of maximum marginal likelihood estimation (MMLE) and delay estimation using Gabor transform. The delay estimation allows one to automatically identify the optimal fundamental frequencies for the kernel, thus increasing the numerical stability of the hyperparameters tuning process. The resulting delayed Gaussian process model accurately predicts the S-parameter values at desired frequency points in the training interval. Two application examples demonstrate the increased accuracy of the new technique, compared to standard Gaussian processes, vector fitting (VF), and delayed vector fitting (DVF) rational models.Publicationtype: Journal Article17 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Automated Generation and Correlation of Physics-Based Via Models with Full-Wave Simulation for an SI/PI DatabasePublicationtype: Conference Paper17 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Modeling S-parameters of Interconnects using Periodic Gaussian Process Kernels(2023-05); ; ; In this paper, we present a novel technique to model wide-band scattering parameter (S-parameter) curves of high-speed digital interconnects. The proposed technique utilizes a new kernel function with periodic components for Gaussian process (GP) models. After proper training, the GP models are able to predict the S-parameter values at arbitrary frequency points inside the trained interval. The performance of the proposed technique is reviewed by means of correlation with standard Gaussian Processes with squared exponential kernel and Matern kernel. Results for the proposed technique show an increased prediction accuracy when applied to interconnects.Publicationtype: Conference Paper20 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Combined Assessment of Interconnect and Equalization in Data Links on Multilayer Printed Circuit Boards(2019-02-01); Publicationtype: Bachelor Thesis227 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Direct prediction of linear equalization coefficients using raised cosine pulse shaping in frequency domain(2018-05); ; Publicationtype: Conference Paper98 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Efficient Sensitivity-Aware Assessment of High-Speed Links Using PCE and Implications for COMPublicationtype: Conference Paper37