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RD-AIC based DS-CDMA navigation receiver model.
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... RD-AIC based navigation receiver considered in this paper removes the demodulation stage (a in Figure 2), as the received signal is already spread in spectrum, but affected by noise. Then, DS-CDMA demodulation based on auto- correlation detection is performed, according to the receiver model shown in Figure 3. ...
Citations
... Lower sampling frequency Sparsity requirement on input signal Lower data rate More computational load for back-end Reduced occupancy of acquisition memory Architectural complexity [7-9] Reduced power consumption [6,7] Difficult uncertainty evaluation High compression in recent architectures [8,9] More sensitivity to non-idealities [10] Broadband input in recent architectures [8,9] Intricate front-end characterization [3,6] Although AICs are not an industrial reality yet, they are a promising perspective of research within different fields. The prototypes developed in the last few years prove the AIC potential from building structural monitoring [11] to remote healthcare systems [12][13][14], from electrical impedance spectroscopy [15] to spectrum sensing [6][7][8][9][16][17][18][19][20][21][22][23][24][25]. Indeed, as proposed in [11], the AIC is exploited to acquire acoustic emission signals. ...
... The operation mode of the prototype [14], experimentally demonstrated for ECG signals, highlights that, despite the compression phase, the signal information content, such as QRS complex, is preserved. Anyway, since AIC technology allows to reduce high sampling frequencies as well as large amounts of samples, the most investigated application is spectrum sensing, where AICs can be employed as code division multiple access receivers [16] or wideband receivers [6][7][8][9][17][18][19][20][21][22][23][24][25]. Some wideband receivers perform the function of radar detection [22][23][24] or cognitive radio [7,9]. ...
Data acquisition systems have shown the need of wideband spectrum monitoring for many years. This paper describes and discusses a recently proposed architecture aimed at acquiring efficiently wideband signals, named the Analog-to-Information Converter (AIC). AIC framework and working principle implementing the sub-Nyquist sampling are analyzed in general terms. Attention is specifically focused on the idea of exploiting the condition of the signals that, despite their large bandwidth, have a small information content in the frequency domain. However, as clarified in the paper, employing AICs in measurement instrumentation necessarily entails their characterization, through the analysis of their building blocks and the corresponding non-idealities, in order to improve the signal reconstruction.
... Among the different AIC architectures proposed in literature, one of the most common is based on the Random Demodulation (RD) principle [10]- [18]. In particular, the RD AIC has been employed in [10] for biosignal acquisition. ...
... Such signal is a Pseudo Random Binary Sequence (PRBS), namely a sequence of random symbols in the set {−1, +1}. Various PRBS families can be adopted [18] and both actual shape and jitter of each symbol affect the PRBS waveform generation [16], [17]. Anyway, the key aspect of RD AIC is that each symbol is generated at a fast symbol rate f p , at least equal to the Nyquist rate f N yq of the input signal, i.e. f p ≥ f N yq . ...
... In other words, the output is composed of a down-sampled number of measurements than required by the Nyquist-Shannon theorem: the purpose of an AIC is to realize in only one step sampling and compression of the original signal. This technology has been applied to many research fields especially for monitoring purposes, such as cognitive radios [2] and code division multiple access receivers [3]. ...
Aim of this paper is to compare in Analog-to-Information Converters the working principles of the two devices typically used to perform the operation of multiplication: mixers and analog multipliers. The comparison has been experimentally realized on two AIC prototypes based on the Random Demodulation principle: the former employing a mixer, the latter employing an analog multiplier.
The paper presents a sensitivity analysis of the non-idealities introduced by the Pseudo Random Binary Sequence (PRBS) on two modulation-based architectures of Analog-to-Information Converters (AICs), namely the Random Demodulator and the Modulated Wideband Converter. In particular, the effects of both PRBS pulse shape and jitter are contemplated. The emerging findings from this analysis can guide the design process of AICs, so that the jitter effect can be brought below acceptable levels for a given target application. The analysis is carried out firstly by characterizing the PRBS pulse shape, and then by including the calibration data in the behavioral models of the two architectures. The reconstructed signal is thus evaluated for different values of random and deterministic jitter, in terms of Spurious Free Dynamic Range and Signal to Noise And Distortion Ratio. The results highlight a different behavior of the two architectures due to the different reconstruction models they adopt. Mainly, the identification phase of the measurement matrix proves to be able to compensate the jitter effect when jitter is correlated with the PRBS sequence.
The dissertation deals with the characterization of sub-sampling devices, the Analog-to-Information Converters (AICs), recently proposed in research as an alternative to the traditional Analog-to-Digital Converters. By exploiting the Compressive Sampling paradigm, AICs stably recover the input signal, previously acquired with less samples than needed by the Nyquist-Shannon theorem, reducing simultaneously sampling frequency and acquisition memory. The dissertation research was carried out in order to design and develop an AIC prototype to be employed in a measurement instrument: a vector signal analyzer, that acquires and reconstructs sparse wideband signals. The aim of such an instrument is to guarantee proper monitoring, circumventing the trade-off between resolution and sampling frequency, typical of conventional data acquisition systems. With a view to this use, the characterization of AICs is of crucial importance, since their performance conditions the measurement instrument based on them, and, although several efforts have been made in research to propose several architectures, only in a few cases their performance is assessed.
