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Nonuniform sampling driver design for optimal ADC utilization
 in Proc. ISCAS '03, May 2003
"... Deliberate nonuniform sampling promises increased equivalent sampling rates with reduced overall hardware costs of the DSP system. The equivalent sampling rate is the sampling rate that a uniform sampling device would require in order to achieve the same processing bandwidth. Equivalent bandwidths o ..."
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Cited by 5 (2 self)
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Deliberate nonuniform sampling promises increased equivalent sampling rates with reduced overall hardware costs of the DSP system. The equivalent sampling rate is the sampling rate that a uniform sampling device would require in order to achieve the same processing bandwidth. Equivalent bandwidths of realizable systems may well extend into the GHz range while the mean sampling rate stays in the MHz range. Current prototype systems (IECS) have an equivalent bandwidth of 1.6GHz at a mean sampling rate of 80MHz, achieving 40 times the bandwidth of a classic DSP system that would operate uniformly at 80MHz (cf. [1]). Throughout the literature on nonuniform sampling (e. g. [2] and [3]) different sampling schemes have been investigated. This paper focuses on nonuniform sampling schemes optimized for fast and efficient hardware implementations. To our knowledge this is the first proposal of an efficient nonuniform sampling driver (SD) design in the open literature. 1.
Optimal Sampling Functions In Nonuniform Sampling Driver Designs To Overcome The Nyquist Limit
, 2003
"... In some applications the observed samples are inherently nonuniform. In contrast to that in this paper we take advantage of deliberate nonuniform sampling and perform DSP where the classical approaches leave off. For instance think about mobile communication or digital radio. Deliberate nonuniform s ..."
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Cited by 3 (2 self)
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In some applications the observed samples are inherently nonuniform. In contrast to that in this paper we take advantage of deliberate nonuniform sampling and perform DSP where the classical approaches leave off. For instance think about mobile communication or digital radio. Deliberate nonuniform sampling promises increased equivalent sampling rates with reduced overall hardware costs. The equivalent sampling rate is the sampling rate that a uniform sampling device would require in order to achieve the same processing bandwidth. While the equivalent bandwidth of a realizable system may well extend into the GHz range its mean sampling rate is usually in the MIIz range. Current existing prototype systems achieve 40 times the bandwidth of a classic DSP system that would operate uniformly (cf. [3] and [4]). Throughout the literature on nonuniform sampling (e.g. Ill, [2] and [5]) many sampling schemes have been investigated. In this paper the authors discuss a nonuniform sampling scheme that is especially suited to be implemented in digital devices, thus, fully exploiting stateoftheart ADCs without violating their specifications. An analysis of the statistical properties of the algorithm is given to demonstrate common pitfalls and to prove its correctness.
Aliasfree periodic signal analysis using efficient rate nonuniform sampling sets
 in Proc. of Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP
, 2007
"... In many applications such as signal integrity checking of hardware prototypes or determining dynamic behavior of wideband amplifiers etc. analysis of periodic radio signals with high accuracy is desired. The straight forward approach is to sample the signal to be analyzed with twice its highest har ..."
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In many applications such as signal integrity checking of hardware prototypes or determining dynamic behavior of wideband amplifiers etc. analysis of periodic radio signals with high accuracy is desired. The straight forward approach is to sample the signal to be analyzed with twice its highest harmonic content. But as fundamental frequencies are often far into the MHz range its harmonics may well span into the upper MHz or even GHz range. This leaves two possibilities: First, obey the sampling theorem and sample at that rate. But ADCs able to sample in the GHz range are expensive, power hungry and offer 6 to 8 bits maximum. Sometimes, this is not an option at all. Second, try to live with under sampling accepting alias frequencies in baseband. As long as aliased harmonics do not overlap this presents an acceptable solution. If they overlap, however, nothing can be done once the signal is sampled. But there is one more option presented in this paper, namely the possibility of deliberate nonuniform sampling. If the sampling set is chosen in a convenient way, mostly offered by an additive random sampling (ARS) scheme, this opens up promising possibilities to extend the alias–free processing range into the far MHz or even GHz region. Index Terms — Nonuniform sampling, alias–free signal processing, least squares methods, radio signal processing,
Najib Allay
"... Spectral analysis of randomly sampled signals: suppression of aliasing and sampler jitter. ..."
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Spectral analysis of randomly sampled signals: suppression of aliasing and sampler jitter.
Robustness of Compressive Sensing under Multiplicative Perturbations: The Challenge of Fading Channels
"... Abstract—We investigate the robustness of Compressive Sensing (CS) as a direct signal acquisition and reconstruction method at the wireless receiver in fading channels. The wireless channel introduces additive as well as multiplicative random perturbations to the received signal. The original CS the ..."
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Abstract—We investigate the robustness of Compressive Sensing (CS) as a direct signal acquisition and reconstruction method at the wireless receiver in fading channels. The wireless channel introduces additive as well as multiplicative random perturbations to the received signal. The original CS theory considers only additive and bounded perturbations for signal reconstruction with an a priori known basis. However, the impact of multiplicative perturbations, which manifests itself as basis mismatch, on the CS reconstruction performance is largely unknown. In this paper we first formulate such multiplicative perturbations due to wireless fading channel in the CS acquisition and reconstruction problem. We then show that these perturbations can result in significant errors in signal reconstruction if the basis is not properly adjusted. Furthermore, we will propose a method for adjusting the elements of basis to the fading channel coefficients and discuss possible improvements in the signal reconstruction. I.
A Novel Method Improving Nonuniform Sampling Instant Placement
"... Abstract: – In a world of fast evolving standards in wireless communication systems it is desirable to build flexible radio front–ends that have to be reconfigured rather then redesigned if a standard is changing or a new standard is introduced. This is the driving idea behind software defined radi ..."
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Abstract: – In a world of fast evolving standards in wireless communication systems it is desirable to build flexible radio front–ends that have to be reconfigured rather then redesigned if a standard is changing or a new standard is introduced. This is the driving idea behind software defined radio (SDR). SDR systems today usually employ several parallel ADC sampling channels for direct down conversion to be able to process various radio channels at once (see e. g. [1]). Although greatly benefiting from the use of dedicated ASICs and FPGAs these systems are still very complex. An alternative approach to such architectures is offered by using a single (or at most dual) ADC direct down conversion system exploiting nonuniform sampling instead of uniform sampling. This enables alias–free signal processing in a frequency range determined by the systems time quantum. We briefly explain the motivation behind nonuniform sampling in our introduction. The challenge when sampling radio signals nonuniformly lies in the generation of precise, predictable (i. e. pseudo random) sampling instances. These instances have to be produced with picosecond precision like required in uniform undersampling applications mentioned above. Deliberate nonuniform sampling requires a sampling driver (SD) conveniently implemented in FPGAs. The FPGA has to be clocked by a low jitter clock generator (exposing 3 ps RMS cycletocycle jitter or less). Such clock sources are not available for all frequency ranges and are often very expensive. Therefore it is inevitable to use a delay locked loop (DLL) or phase locked loop
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"... Optimal periodic sampling sequences for nearlyaliasfree digital signal processing. ..."
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Optimal periodic sampling sequences for nearlyaliasfree digital signal processing.
Reducing Jitter in Nonuniform Sampling Drivers
"... Abstract: – It is know for quite some time now (cf. [13] and [4]) that practical aliasfree signal processing systems utilizing a wider alias free band than set by the sampling theorem can be built successfully through the use of deliberate nonuniform sampling. Such systems are especially useful w ..."
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Abstract: – It is know for quite some time now (cf. [13] and [4]) that practical aliasfree signal processing systems utilizing a wider alias free band than set by the sampling theorem can be built successfully through the use of deliberate nonuniform sampling. Such systems are especially useful when processing radio signals digitally. However, such sampling systems usually require a high precision clock generator in order to maintain their full spectral dynamic range throughout their operational bandwidth. Clock generators are referred to as high precision if they expose 3 ps RMS cycletocycle jitter or less. Such generators are expensive and not available over all frequency ranges (affordable support typically ranges from 10 to 170 MHz). Therefore, a robust sampling driver (SD) design written in VHDL or another portable hardware description language will usually utilise a delay locked loop (DLL) or phase locked loop (PLL) to obtain higher frequencies for internal logic producing the desired nonuniform sampling eventually presented to an attached ADC. Unfortunately every DLL or PLL will add jitter to the produced sampling instants thus diminishing spectral dynamic range. In this paper we propose a remedy to afore mentioned added jitter. The proposed jitter reducing methodology is robust and will work in a variety of nonuniform sampling driver designs. The obtained results are verified, using a sampling driver implementation featuring a FPGA, by jitter measurements based on an algorithm reported in [5].
Optimal periodic sampling sequences for nearlyaliasfree
"... digital signal processing. ..."
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unknown title
"... Spectral analysis of randomly sampled signals: suppression of aliasing and sampler jitter. ..."
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Spectral analysis of randomly sampled signals: suppression of aliasing and sampler jitter.