W. Van Moer

A large-signal network analyzer: Why is it needed?

Good measurements are a major step towards good modeling. However, besides these measurements, modeling a system also requires a good insight in the system behavior. Do harmonics rise above the noise floor? Must they be taken into account during modeling? Is the system essentially dynamic or static? An answer to the above questions lies in the preprocessing of the measured data as obtained by the LSNA. This technique makes nonlinear effects more visible and allows understanding of the energy transport mechanisms behind the device operation

Identification of linear systems in the presence of nonlinear distortions

This paper treats the identification of linear systems in the presence of nonlinear distortions. It extends the theory developed for measurement setups where the input is exactly known and the output is observed with errors (output error framework) to measurement setups where both the input and output are observed with errors (errors-in-variables framework). An appropriate measurement strategy and identification algorithm are presented.

Performance Evaluation of Peak-to-Average Power Ratio Reduction and Digital Pre-Distortion for OFDM Based Systems

In this paper, we evaluate the effect of applying peak-to-average power ratio (PAPR) reduction and digital pre-distortion (DPD) on two types of radio frequency power amplifiers when an orthogonal frequency division multiplexing (OFDM) signal is used. The power amplifiers under test are a standard class-AB amplifier and a Doherty amplifier. The PAPR reduction methods are based on a state-of-the art convex optimization formulation and on the standard clipping and filtering technique. The DPD method consists of modeling the behavior of the power amplifier using a parallel Hammerstein model, and then extracting the inverse parameters based on the indirect learning architecture. To achieve better DPD performance, extracting the DPD parameters based on multiple-step iterations is investigated. The cases where PAPR reduction and DPD are applied separately and combined are studied and investigated. Power amplifier figures of merit are evaluated. Good performance is shown when combining both pre-processing techniques up to a certain operating point where DPD performance deteriorates due to generation of strong peaks in the signal. In addition, a difference in the power amplifier behavior is reported and analyzed.

Identification of a Block-Structured Nonlinear Feedback System, Applied to a Microwave Crystal Detector

This paper studies the identification of a block-structured nonlinear Wiener-Hammerstein system that is captured in the feedforward or the feedback path of a closed-loop system. First, nonparametric initial estimates are generated for the three dynamic blocks, which are modeled by their frequency response function, and the static nonlinear system, which is described using an input-output table. Next, a parametric model is identified. Random or periodic excitations can be used in the experiments. The method is illustrated on the identification of an Agilent HP420C crystal detector.

Spectrally pure excitation signals: only a dream?

Multi-tone excitation signals become increasingly important for test and measurement purposes. However, the signal sources used to create such multitone signals are not perfect and often create unwanted spectral contributions. This paper presents a method to create spectrally pure signals, such as two-tones or multitones, using signal sources based on arbitrary waveform generators (AWG). Only amplitude information is needed, so that a spectrum analyzer can be used to perform all necessary measurements. Unwanted spectral lines are suppressed, independent of their exact origin. This allows to apply a testsignal with the correct spectral content to the device under test, even if the signal source is not perfect or external disturbances are present. Measurements on an RF amplifier show the capabilities of the method.

NVNA versus LSNA: enemies or friends?

The NVNA and the LSNA are powerful instruments which allow to measure the full nonlinear behavior of microwave devices. They are super-oscilloscopes which are able to measure absolute time domain waveforms. Both instruments are based on a different measurement principle: the mixer-based architecture of the NVNA and the sampler based architecture of the LSNA. They both have their advantages and disadvantages. By using these nonlinear measurement instruments, one is able to gain a good insight into the nonlinear behavior of a system. Combining good measurements with good insight, results in good nonlinear modeling.

Linearizing Oscillometric Blood-Pressure Measurements: (Non)Sense?

This paper proposes a simplified method to compute the systolic and diastolic blood pressures from measured oscillometric blood-pressure waveforms. Therefore, the oscillometric waveform is analyzed in the frequency domain, which reveals that the measured blood-pressure signals are heavily disturbed by nonlinear contributions. The proposed approach will linearize the measured oscillometric waveform in order to obtain a more accurate and transparent estimation of the systolic and diastolic pressure based on a robust preprocessing technique. This new approach will be compared with the Korotkoff method and a commercially available noninvasive blood-pressure meter. This allows verification if the linearized approach contains as much information as the Korotkoff method in order to calculate a correct systolic and diastolic blood pressure.

Probability density function for frequency response function measurements using periodic signals

Frequency response function (FRF) measurements are often used to characterize linear dynamic systems. Nowadays uncertainty bounds on FRF measurements still are based on linear approximations, which are valid for sufficiently large input signal-to-noise-ratios (SNR) only. In this paper exact uncertainty bounds are calculated, which are valid for any input SNR. These bounds are obtained via an analytic expression of the probability density function (PDF) of the FRF measurements. The results are valid for open- and closed-loop measurements, and the theory is illustrated on a real measurement example.

Analyzing the Windkessel Model as a Potential Candidate for Correcting Oscillometric Blood-Pressure Measurements

Developing a good model for oscillometric blood-pressure measurements is a hard task. This is mainly due to the fact that the systolic and diastolic pressures cannot be directly measured by noninvasive automatic oscillometric blood-pressure meters (NIBP) but need to be computed based on some kind of algorithm. This is in strong contrast with the classical Korotkoff method, where the diastolic and systolic blood pressures can be directly measured by a sphygmomanometer. Although an NIBP returns results similar to the Korotkoff method for patients with normal blood pressures, a big discrepancy exist between both methods for severe hyper- and hypotension. For these severe cases, a statistical model is needed to compensate or calibrate the oscillometric blood-pressure meters. Although different statistical models have been already studied, no immediate calibration method has been proposed. The reason is that the step from a model, describing the measurements, to a calibration, correcting the blood-pressure meters, is a rather large leap. In this paper, we study a “databased” Fourier series approach to model the oscillometric waveform and use the Windkessel model for the blood flow to correct the oscillometric blood-pressure meters. The method is validated on a measurement campaign consisting of healthy patients and patients suffering from either hyper- or hypotension.

Experimental characterization of the nonlinear behavior of RF amplifiers

Using specifically designed broadband periodic random excitation signals, the best linear approximation of RF amplifiers is measured. The proposed technique: 1) takes into account the measurement uncertainty and the nonlinear distortions and 2) detects, quantifies, and classifies the nonlinear distortions with confidence bounds. The approach is suitable for the experimental characterization of existing amplifiers