An efficient nonlinear circuit simulation technique

This paper proposes a new and efficient approach for the analysis and simulation of circuits subject to input signals with widely separated rates of variation. Such signals arise in communication circuits when an RF carrier is modulated by a low-frequency information signal. The proposed technique initially involves converting the ordinary differential equation system, that describes the nonlinear circuit, to a partial differential equation system. The resultant system is then semidiscretised using a multiresolution collocation scheme, involving cubic spline wavelet decomposition. A reduced equation system is subsequently formed, using a nonlinear model reduction strategy. This enables an efficient solution process using trapezoidal numerical integration. Results highlight the efficacy of the proposed approach

A novel iterative solution of the three dimensional electric field integral equation

A novel forward backward iterative scheme for solving the three-dimensional (3-D) electric field integral equation is presented. This communication details how a naive extension of a 2-D forward backward algorithm to 3-D problems results in convergence difficulties due to spurious edge effects. The method proposed in this communication postulates the use of local "buffer regions" to suppress these unwanted effects and ensure stability. Results are presented illustrating the convergence of the algorithm when applied to scattering by a 15λ square metallic plate with an aperture and a metallic right-angled wedge

An efficient nonlinear circuit simulation technique

This paper proposes a novel method for the analysis and simulation of integrated circuits (ICs) with the potential to greatly shorten the IC design cycle. The circuits are assumed to be subjected to input signals that have widely separated rates of variation, e.g., in communication systems, an RF carrier modulated by a low-frequency information signal. The proposed technique involves two stages. Initially, a particular order result for the circuit response is obtained using a multiresolution collocation scheme involving cubic spline wavelet decomposition. A more accurate solution is then obtained by adding another layer to the wavelet series approximation. However, the novel technique presented here enables the reuse of results acquired in the first stage to obtain the second-stage result. Therefore, vast gains in efficiency are obtained. Furthermore, a nonlinear model-order reduction technique can readily be used in both stages making the calculations even more efficient. Results will highlight the efficacy of the proposed approac

A causal model for linear RF systems developed from frequency-domain measured data

With the ever-growing complexity of interconnect networks, models developed from measured data or data from 3-D electromagnetic simulators are increasingly becoming essential. It is to this end that the current contribution is directed. In particular, it focuses on the development of a model via a Fourier series expansion (FSE) approach. Its primary advantage is that the response in the time domain can be explicitly obtained in a simple form for an arbitrary input using only a set of FSE coefficients. Also, it guarantees causality without requiring a numerical implementation of a Hilbert transform. The end result is a causal and stable time-domain representation of a system that may subsequently be used in a time-domain simulator such as SPICE

Arnoldi model order reduction for electromagnetic wave scattering computation

This paper presents a model order reduction (MOR) algorithm for the volume integral equation formulation of electromagnetic wave scattering. We apply the Arnoldi algorithm to circumvent the computational complexity associated with the numerical solution of such formulations. An approximate extension of the Arnoldi algorithm to the problem of wave scattering from an inhomogeneous body is introduced and implemented. Numerical examples are presented to demonstrate the accuracy of our approximate extension

An efficient wavelet-based nonlinear circuit simulation technique with model order reduction

This paper proposes further improvement to a novel method for the analysis and simulation of ICs recently proposed by the authors. The circuits are assumed to be subjected to input signals that have widely separated rates of variation, e.g. in communication systems an RF carrier modulated by a low-frequency information signal. The previously proposed technique enables the reuse of the results obtained using a lower-order accuracy model to calculate a response of higher-order accuracy model. In this paper, the efficiency of this method is further improved by using a nonlinear model order reduction technique. Results highlight the efficiency of the proposed approach

Efficient wideband electromagnetic scattering computation for frequency dependent lossy dielectrics using WCAWE

This paper presents a model order reduction algorithm for the volume electric field integral equation (EFIE) formulation, that achieves fast and accurate frequency sweep calculations of electromagnetic wave scattering. An inhomogeneous, two-dimensional, lossy dielectric object whose material is characterized by a complex permittivity which varies with frequency is considered. The variation in the dielectric properties of the ceramic BaxLa4Ti 2+xO 12+3x in the <1 GHz frequency range is investigated for various values of x in a frequency sweep analysis. We apply the well-conditioned asymptotic waveform evaluation (WCAWE) method to circumvent the computational complexity associated with the numerical solution of such formulations. A multipoint automatic WCAWE method is also demonstrated which can produce an accurate solution over a much broader bandwidth. Several numerical examples are given on order to illustrate the accuracy and robustness of the proposed methods

A route identification algorithm for assisted living applications fusing WLAN, GPS and image matching data

This paper addresses the automatic identification of often traversedroutes for assisted living applications using WLAN technology in addition to other modalities. This problem is complicated by a number of factors, including the changing and noisy nature of the WLAN channel, the need to track users seamlessly in both indoor and outdoor environments, the need for robustness to slight deviations in the precise path taken, and speed, along a route. In this work commonly traversed routes are identified by clustering based on sensed data, two of which take the form of wireless signals: GPS and WLAN. The latter is particularly important as it can be used both indoors and outdoors. In addition an efficient image matching algorithm is implemented to process data from images automatically taken along the route. In this work a finite number of routes were identified within the DCU campus. Each route was traversed many times over a period of 6 weeks and data sequences collected automatically on each occasion. Each such traversal of a route is referred to as a trip in what follows. Section (2) outlines the use of Multidimensional Time Warping in order to automatically cluster trips corresponding to specific routes based on wireless and image data sensed on each trip. Section (3) outlines the manner in which data was sensed and presents clustering results for each modality individually as well as results based on a fusion of the data

User tracking using a wearable camera

Abstract—This paper addresses automatic indoor user tracking based on fusion of WLAN and image sensing. Our motivation is the increasing prevalence of wearable cameras, some of which can also capture WLAN data. We propose a novel tracking method that can be employed when using image-based, WLAN-based and fusion-based approach only. The effectiveness of combining the strengths of these two complementary modalities is demonstrated for a very challenging data

Indoor localisation based on fusing WLAN and image data

In this paper we address the automatic identification of indoor locations using a combination of WLAN and image sensing. We demonstrate the effectiveness of combining the strengths of these two complementary modalities for very chal- lenging data. We describe a fusion approach that allows localising to a specific office within a building to a high degree of precision or to a location within that office with reasonable precision. As it can be orientated towards the needs and capabilities of a user based on context the method becomes useful for ambient assisted living applications