Successive‐phase correction calibration method for modulated wideband converter system

Fu, Ning; Jiang, Siyi; Deng, Libao; Qiao, Liyan

doi:10.1049/iet-spr.2018.5325

Cited by 10 publications

(8 citation statements)

References 38 publications

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“…In the practical implementation, the sensing matrix A in (3) is deteriorated by the non-ideality of the real circuits that severely impacts the reconstruction performance. There are numerous calibration techniques for the sensing matrix [10], [27]- [29], [37]- [40]. Among them, we exploit the simultaneous estimation technique of the sensing matrix [40].…”

Section: B Calibration Of the Sensing Matrixmentioning

confidence: 99%

“…Without calibrating the sensing matrix, realization of the reconstruction and the recovery of support becomes infeasible. The works [10], [27]- [29], [37]- [39] exploit the estimation method for actual sensing matrix based on a set of sequential measurements of single-tones with known frequencies. This iterative method This work is licensed under a Creative Commons Attribution 4.0 License.…”

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confidence: 99%

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High-Precision Sub-Nyquist Sampling System Based on Modulated Wideband Converter for Communication Device Testing

Byambadorj

Asami

Yamaguchi

et al. 2022

IEEE Trans. Circuits Syst. I

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This paper proposes a new method of constructing a compensation filter for the modulated wideband converter (MWC) system. The proposed method can be directly used in the MWC circuit without disconnecting any components. Furthermore, the non-ideal transfer characteristics of the real mixer output and the real ADC input are taken into account in the proposed compensation filter. The proposed method can be utilized in the advanced MWC that enables more flexibility in the design parameters of the MWC. This paper also demonstrates the reconstruction of the Bluetooth signal as a practical example for the evaluation of the reconstruction performance. The MWC successfully reconstructs the time-domain waveform of the signal based on the proposed compensation filter. Even in the case that the total effective number of channels in MWC is small as close to the necessary condition of the MWC, the error vector magnitude (EVM) was still under 1%, which is acceptable for Bluetooth device testing applications.

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Section: B Calibration Of the Sensing Matrixmentioning

confidence: 99%

mentioning

confidence: 99%

High-Precision Sub-Nyquist Sampling System Based on Modulated Wideband Converter for Communication Device Testing

Byambadorj

Asami

Yamaguchi

et al. 2022

IEEE Trans. Circuits Syst. I

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“…This technique can be considered as a reference. Some researchers have exploited this work to propose calibration algorithms [29][30][31][32][33] based on the measurements of different single tones. In our opinion, one drawback of this procedure is that this task can be time consuming and annoying when the number of columns of the sensing matrix L is high because the same step must be repeated many times.…”

Section: Introductionmentioning

confidence: 99%

A Modulated Wideband Converter Calibration Technique Based on a Single Measurement of a White Noise Signal with Advanced Resynchronization Preprocessing

et al. 2022

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The Modulated Wideband Converter (MWC) is a blind sub-Nyquist sampling system used especially to monitor wideband spectrum. This system can be realized by existing analog components. From a theoretical point of view, all analog components are assumed ideal. However, this hypothesis is false in practice. Indeed, some imperfections are introduced by analog components such as nonlinearities of mixers, phase/attenuation/selectivity of low-pass filters and desynchronization between modulating waveforms. Consequently, it is necessary to correctly estimate the sensing matrix to ensure correct spectrum reconstruction performance. Conventional calibration methods are based on the measurements of different single tones. However, these approaches need to record several measurements with single-tone inputs. To avoid this problem, this paper presents a new hardware calibration method of MWC by using a single measurement of a white noise signal for radio frequency spectrum monitoring. A preprocessing method is performed to resynchronize input, output and modulating waveforms signals with each other. Our hardware calibration method is applied to our prototype of Compressed Sensing (CS) scheme in order to estimate the corrected sensing matrix. To prove the efficiency of our hardware calibration, reconstruction performances were evaluated with respect to the probability of correct reconstruction and false alarm criteria. These results are compared with those obtained with the theoretical MWC scheme, with our prototype without calibration and with reference calibration.

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“…The procedure is repeated by changing the input frequency until all columns are estimated. Some researchers have exploited this work to calibrate their systems or to propose variants of the calibration algorithms [19][20][21][22][23]. While this procedure is efficient, it can be time consuming because the number of columns to estimate is usually at least a few dozens.…”

Section: Introductionmentioning

confidence: 99%

A Modulated Wideband Converter Model Based On Linear Algebra and its Application to Fast Calibration

Burel¹,

Fiche²,

Gautier³

2022

Preprint

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In the context of cognitive radio, smart city and Internet-of-Things, the need of advanced radio spectrum monitoring becomes crucial. However, surveillance of a wide frequency band without using extremely expensive high sampling rates devices is a challenging task. The recent development of compressed sampling approaches offers a promising solution to these problems. In this context, the Modulated Wideband Converter (MWC), a blind sub-Nyquist sampling system, is probably the most realistic approach and was successfully validated in real-world conditions. The MWC can be realized with existing analog components and there exist calibration methods which are able to integrate the imperfections of the mixers, filters and ADCs, hence allowing its use in real-world. The MWC underlying model is based on signal processing concepts such as filtering, modulation, Fourier series decomposition, oversampling and undersampling, spectrum aliasing, and so on, as well as in-flow data processing. In this paper we develop an MWC model which is entirely based on linear algebra, matrix theory and block processing. We show that this approach has many interests: straightforward translation of mathematical equations into simple and efficient software programming, suppression of some constraints of the initial model, and providing a basis for the development of an extremely fast system calibration method. With a typical MWC acquisition device we obtained a speed up of a factor greater than 20 of the calibration computation time, compared with a previous implementation.

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Successive‐phase correction calibration method for modulated wideband converter system

Cited by 10 publications

References 38 publications

High-Precision Sub-Nyquist Sampling System Based on Modulated Wideband Converter for Communication Device Testing

High-Precision Sub-Nyquist Sampling System Based on Modulated Wideband Converter for Communication Device Testing

A Modulated Wideband Converter Calibration Technique Based on a Single Measurement of a White Noise Signal with Advanced Resynchronization Preprocessing

A Modulated Wideband Converter Model Based On Linear Algebra and its Application to Fast Calibration

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