Wendy Van Moer

Automatic Detection, Estimation, and Validation of Harmonic Components in Measured Power Spectra: All-in-One Approach

The detection of periodic components buried in noise is a general problem in various engineering fields. The amplitudes in the frequency domain of a disturbed signal follow Rice distribution, which is fully described by two parameters. Most methods are restricted to automatically detecting the harmonic components. In this paper, we extend the methodology to detect significant harmonics in measured spectra such that, aside from detection, the magnitude of the harmonic component is also estimated, together with the probability that the harmonic component was incorrectly detected.

Estimating the parameters of a Rice distribution: A Bayesian approach

The problem of detecting a periodic signal buried in zero-mean Gaussian noise is present in various fields of engineering. It is well-known that the amplitude of the disturbed signal follows a Rice distribution which is characterized by two parameters. In this paper, an alternative Bayesian approach is proposed to tackle this two-parameter estimation problem. By incorporating prior knowledge into a mathematical framework, the drawbacks of the existing methods (i.e., the maximum likelihood approach and the method of moments) can be overcome. The performance of the proposed Bayesian estimatoris shown through simulations.

Using Alternating Kalman Filtering to Analyze Oscillometric Blood Pressure Waveforms

Measuring the blood pressure as accurately as possible can save a lot of human lives. Hence, it is very important to find an optimal method to determine the systolic and diastolic pressures out of the measured oscillometric blood pressure waveform (OBPW). Recently, studies have shown that by working in the frequency domain, outperforming results could be obtained for the separation of breathing from cardiac activity. In this paper, we present a new implementation of the Kalman filtering algorithm to estimate the envelope of the cardiac activity. Even though the alternating Kalman filter algorithm has subharmonic infiltrations, it offers an envelope that, when applied together with the Windkessel model for calibration, substantially reduces the error of the calibrated systolic and diastolic pressures. This important result validates the non-linear model for the OBPW, as well as the Windkessel model for calibration.

Blind Spectrum Sensing for Cognitive Radios Using Discriminant Analysis: A Novel Approach

In this paper, we present a new spectrum sensing technique for cognitive radios based on discriminant analysis called spectrum discriminator. The presented technique uses the knowledge of the noise uncertainty and a probabilistic validation to overcome the limitations of the discriminant analysis. A comparative study between the proposed technique and the maximum-minimum eigenvalue detection has been performed based on two performance metrics: the probability of false alarm and the probability of detection. The spectrum discriminator has been further developed to a peel-off technique where all primary users can be detected. The performance of the spectrum discriminator and the peel-off technique has been tested on simulations and experimentally verified. The comparative study is based on simulations as well as measurements.

Calibration of a Wideband IF Nonlinear Vectorial Network Analyser

Unlike the Vectorial Network Analyser, the Nonlinear Vectorial Network Analyser imposes a wideband intermediate frequency (IF) detection (a few kHz instead of Hz). In this paper, the influence of the resulting signal-to-noise degradation on the calibration accuracy is analysed. The statistical properties of a standard calibration are compared to a stochastically founded method based on real experimental data.

Characterization of Concurrent Dual-Band Power Amplifiers Using a Dual Two-Tone Excitation Signal

A method to characterize the memory effects in a nonlinear concurrent dual-band transmitter is presented. It is an extension of the conventional two-tone test for power amplifiers to concurrent dual-band transmitters. The output signal of a concurrent dual-band transmitter is affected not only by intermodulation (IM) products but also by cross-modulation (CM) products. In one frequency band, the transmitter is excited by a two-tone signal which frequency separation is swept. In the second band, the transmitter is concurrently excited by another two-tone signal with slightly wider frequency separation. The frequency difference of the two signals is fixed during the frequency sweep. The two-tone test is made at different power levels. The upper and lower third-order IM and CM products are measured. The asymmetry between the upper and lower third-order IM and CM products are measures of the transmitters memory effects. The measurement results show that the memory effects are more dominant in the third-order IM products than in the CM products. An error analysis and system calibration was performed and measurement results for two different devices are presented.

Application of the Artificial Neural Network for blood pressure evaluation with smartphones

The smartphone is proposed to evaluate the Blood Pressure (BP) anywhere and anytime. The tasks performed by smartphone are (i) extraction of the PhotoPlethysmoGram (PPG) signal from a frame sequence acquired by the integrated camera, and (ii) processing it by Artificial Neural Network for the evaluation of the BP. The PPG signal is evaluated by analyzing the volumetric blood variation of the fingertip on the frame sequence. Successively, parameters characterizing the pulses of the PPG signal are sent to the Fit Forward Neural Network for the simultaneously evaluation of the systolic and the diastolic BP. The validation of the results is performed by comparing them with the ones obtained by the Ambulatory Blood Pressure monitor ABP Spacelabs 90207. Preliminary experimental results show useful information to address the future research devoted to reduce the maximum error.

Spectrum sensing through spectrum discriminator and maximum minimum eigenvalue detector: A comparative study

In this paper we present a new spectrum sensing technique for cognitive radios based on discriminant analysis called spectrum discriminator and compare it with the maximum minimum eigenvalue detector. The common feature between those two techniques is that neither prior knowledge about the system noise level nor the primary user signal, that might occupy the band under sensing, is required. Instead the system noise level will be derived from the received signal. The main difference between both techniques is that the spectrum discriminator is a non-parametric technique while the maximum minimum eigenvalue detector is a parametric technique. The comparative study between both has been done based on two performance metrics: the probability of false alarm and the probability of detection. For the spectrum discriminator an accuracy factor called noise uncertainty is defined as the level over which the noise energy may vary. Simulations are performed for different values of noise uncertainty for the spectrum discriminator and different values for the number of received samples and smoothing factor for the maximum minimum eigenvalue detector.

Wideband radio frequency measurements: From instrumentation to sampling theory

Whether listening to broadcast radio or testing developed wireless devices, for civilian or military applications, based on terrestrial or spatial links, a radio frequency (RF) receiver with good measurement capabilities that preserves the received signal information is required. Todays RF measurement receivers with wideband capabilities are split into two groups based on the measurement strategy they adopt. Both groups produce a time domain waveform with both amplitude and phase information that is constructed either from a transformation of its frequency contents or directly from its time-domain samples.

Measuring the Characteristics of Modulated Non-Linear Devices

A flexible and reconfigurable measurement setup for non-linear devices is proposed. It combines the advantages of a reconfigurable instrument and interchangeability of the instrumentation modules. To show the framework capability, the non-linear characterisation of an amplifier in the 900 MHz band under cw and modulated excitation is presented. The spectral regrowth is hereby fully characterised in amplitude and phase.