| 1. |
- Amin, Shoaib, et al.
(författare)
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Characterization of concurrent dual-band Power Amplifiers using a dual two-tone excitation signal
- 2015
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Ingår i: IEEE Transactions on Instrumentation and Measurement. - : IEEE Press. - 0018-9456 .- 1557-9662. ; :99
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Tidskriftsartikel (refereegranskat)abstract
- 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 products but also by cross-modulation 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 an other 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 inter- and cross-modulation products are measured. The asymmetry between the upper and lower third-order inter- and cross-modulation products are measures of the transmitter's memory effects. The measurement results show that the memory effects are more dominant in the third-order intermodulation products than in the cross modulation products. An error analysis and system calibration was performed and measurement results for two different devices are presented.
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| 2. |
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| 3. |
- Barbé, Kurt, et al.
(författare)
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A Simple Nonparametric Preprocessing Technique to Correct for Nonstationary Effects in Measured Data
- 2012
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Ingår i: IEEE Transactions on Instrumentation and Measurement. - 0018-9456 .- 1557-9662. ; 61:8, s. 2085-2094
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Tidskriftsartikel (refereegranskat)abstract
- The general approach for modeling systems assumes that the measured signals are (weakly) stationary, i.e., the power spectrum is time invariant. However, the stationarity assumption is violated when: 1) transient effects due to experimental conditions are dominant; 2) data are missing due to, for instance, sensor failure; or 3) the amplitude of the excitation signals smoothly varies over time due to, for instance, actuator problems. Although different methods exist to deal with each of these nonstationary effects specifically, no unified approach is available. In this paper, a new and general technique is presented to handle nonstationary effects, based on processing overlapping subrecords of the measured data. The proposed method is a simple preprocessing step where the user does not need to specify which nonstationary effect is present, nor the time interval where the nonstationary effect appears. The merits of the proposed approach are demonstrated on an operational wireless system suffering from interrupted link effects.
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| 4. |
- Barbe, Kurt, et al.
(författare)
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Fractional models for modeling complex linear systems under poor frequency resolution measurements
- 2013
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Ingår i: Digital signal processing (Print). - : Elsevier BV. - 1051-2004 .- 1095-4333. ; 23:4, s. 1084-1093
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Tidskriftsartikel (refereegranskat)abstract
- When modeling a linear system in a parametric way, one needs to deal with (i) model structure selection, (ii) model order selection as well as (iii) an accurate fit of the model. The most popular model structure for linear systems has a rational form which reveals crucial physical information and insight due to the accessibility of poles and zeros. In the model order selection step, one needs to specify the number of poles and zeros in the model. Automated model order selectors like Akaikeʼs Information Criterion (AIC) and the Minimum Description Length (MDL) are popular choices. A large model order in combination with poles and zeros lying closer to each other in frequency than the frequency resolution indicates that the modeled system exhibits some fractional behavior. Classical integer order techniques cannot handle this fractional behavior due to the fact that the poles and zeros are lying to close to each other to be resolvable and not enough data is available for the classical integer order identification procedure. In this paper, we study the use of fractional order poles and zeros and introduce a fully automated algorithm which (i) estimates a large integer order model, (ii) detects the fractional behavior, and (iii) identifies a fractional order system.
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| 5. |
- Barbé, Kurt, et al.
(författare)
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Fractional-Order Time Series Models for Extracting the Haemodynamic Response From Functional Magnetic Resonance Imaging Data
- 2012
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Ingår i: IEEE Transactions on Biomedical Engineering. - 0018-9294 .- 1558-2531. ; 59:8, s. 2264-2272
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Tidskriftsartikel (refereegranskat)abstract
- The postprocessing of functional magnetic resonance imaging (fMRI) data to study the brain functions deals mainly with two objectives: signal detection and extraction of the haemodynamic response. Signal detection consists of exploring and detecting those areas of the brain that are triggered due to an external stimulus. Extraction of the haemodynamic response deals with describing and measuring the physiological process of activated regions in the brain due to stimulus. The haemodynamic response represents the change in oxygen levels since the brain functions require more glucose and oxygen upon stimulus that implies a change in blood flow. In the literature, different approaches to estimate and model the haemodynamic response have been proposed. These approaches can be discriminated in model structures that either provide a proper representation of the obtained measurements but provide no or a limited amount of physiological information, or provide physiological insight but lacks a proper fit to the data. In this paper, a novel model structure is studied for describing the haemodynamics in fMRI measurements: fractional models. We show that these models are flexible enough to describe the gathered data with the additional merit of providing physiological information.
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| 6. |
- Björsell, Niclas, 1964-, et al.
(författare)
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Adding errors to reduce the PAPR and BER of OFDM-based transmissions
- 2013
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Ingår i: 2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC 2013). - New York : IEEE. - 9781467346214 ; , s. 743-746
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Konferensbidrag (refereegranskat)abstract
- When transmitting signals, one of the most important issues is to keep the transmission errors as low as possible. Or in other words, to obtain a reliable transmission link, the bit-error-rate (BER) should be kept within certain limits. However, the probability of transmission errors strongly depends on the signal-to-noise ratio (SNR) of the transmitted signals. Hence, the power amplifier plays a key role in the sender part: the more power, the higher the SNR, the lower the probability of transmission errors. Unfortunately, this is a too simple vision.One should take care to keep the peak-to-average power ratio (PAPR) of the transmitted signal low in order not to push the power amplifier into its nonlinear operation region. Classical techniques use clipping or backing-off the input signal to reduce the PAPR of the transmitted signal. However, these techniques have a negative influence on the SNR and hence on the BER.In this paper, we present a technique to reduce the PAPR of the transmitted signals and hence to reduce the BER, by introducing errors into Orthogonal Frequency Division Multiplexing (OFDM) signals in a controlled way. Channel coding will be used to compensate for the introduced errors.
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| 7. |
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| 8. |
- de la O Serna, Jose Antonio, et al.
(författare)
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Using alternating Kalman filtering to analyze oscillometric blood pressure waveforms
- 2013
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Ingår i: IEEE Transactions on Instrumentation and Measurement. - 0018-9456 .- 1557-9662. ; 62:10, s. 2621-2628
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 9. |
- Esfeh, Babak Kazemi, et al.
(författare)
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Low-cost wideband double-layer microstrip coupled-line directional coupler with high directivity
- 2014
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Ingår i: Microwave and optical technology letters (Print). - : Wiley. - 0895-2477 .- 1098-2760. ; 56:7, s. 1570-1575
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Tidskriftsartikel (refereegranskat)abstract
- In this article, a low-cost double-layer microstrip structure with a gap space between the two substrate layers is used to develop a microstrip coupled-line directional coupler with high directivity. The proposed design shows a high directivity (more than 20 dB) over a wide frequency bandwidth (more than 2 GHz). The double-layer directional coupler, designed on FR4 substrate material at 2.4 GHz provides more than 30 dB isolation. The simulation and measurement results are in good agreement. By applying a simple and low-cost fabrication process and design, the directivity of the directional coupler is enhanced by more than 10 dB compared with a microstrip structure.
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| 10. |
- Gonzales-Fuentes, L., et al.
(författare)
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Adaptive noise tracking for Cognitive Radios under more realistic operation conditions
- 2014
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Ingår i: IEEE Instrumentation and Measurement Technology Conference. - 9781467363853 ; , s. 1339-1344
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Konferensbidrag (refereegranskat)abstract
- Normal operation conditions of cognitive radio applications require signal processing techniques that can be executed in real time. One of the first steps is to sense the occupied or free frequency channels. Two major drawbacks in the current techniques are that they assume (i) the noise as white and (ii) the measured spectrum as time-invariant. In real world, the noise is (i) colored so it disturbs the signal unevenly and (ii) its spectrum changes over time. Hence, tracking the time-varying noise spectrum can become crucial to remove the noise contributions and enhance the estimate of the received signal. In this paper, we study an auto-regressive model to develop an adaptive noise tracking technique using a Kalman filter such that an extension of Boll's noise subtraction technique, designed for audio noise cancellation, becomes feasible when adjusted to cognitive radio scenarios. Simulation results show the performance of this technique.
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