Xampling: analog to digital at sub-Nyquist rates

Mishali, Moshe; Eldar, Yonina C.; Dounaevsky, Oleg; Shoshan, Eli

doi:10.1049/iet-cds.2010.0147

Cited by 376 publications

(322 citation statements)

References 22 publications

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“…The simulations demonstrate robustness to noise and signal mismodeling, potential hardware simplifications in order to reduce the number of devices, fast adaption to time-varying spectral support, and the performance with quantized samples. A circuit-level realization of the MWC is reported in [12]. This paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals

Mishali

Eldar

2010

IEEE J. Sel. Top. Signal Process.

1,044

919

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Abstract-Conventional sub-Nyquist sampling methods for analog signals exploit prior information about the spectral support. In this paper, we consider the challenging problem of blind sub-Nyquist sampling of multiband signals, whose unknown frequency support occupies only a small portion of a wide spectrum. Our primary design goals are efficient hardware implementation and low computational load on the supporting digital processing. We propose a system, named the modulated wideband converter, which first multiplies the analog signal by a bank of periodic waveforms. The product is then low-pass filtered and sampled uniformly at a low rate, which is orders of magnitude smaller than Nyquist. Perfect recovery from the proposed samples is achieved under certain necessary and sufficient conditions. We also develop a digital architecture, which allows either reconstruction of the analog input, or processing of any band of interest at a low rate, that is, without interpolating to the high Nyquist rate. Numerical simulations demonstrate many engineering aspects: robustness to noise and mismodeling, potential hardware simplifications, real-time performance for signals with time-varying support and stability to quantization effects. We compare our system with two previous approaches: periodic nonuniform sampling, which is bandwidth limited by existing hardware devices, and the random demodulator, which is restricted to discrete multitone signals and has a high computational load. In the broader context of Nyquist sampling, our scheme has the potential to break through the bandwidth barrier of state-of-the-art analog conversion technologies such as interleaved converters.

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Section: Introductionmentioning

confidence: 99%

From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals

Mishali

Eldar

2010

IEEE J. Sel. Top. Signal Process.

1,044

919

View full text Add to dashboard Cite

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“…Tunable amplification gains along the path ensure a signal to noiseand-distortion ratio of 15 dB at the outputs yi(t), which was verified experimentally over a dynamic range of 50 dB input power [1]. In contrast to standard RF mixing with a single sinusoid, X-ADC requires periodic mixing, that is simultaneous multiplication with the multiple sinusoids (1) comprising pi(t).…”

Section: B Circuit Workmentioning

confidence: 83%

“…The fact that only slight hardware modifications are required, on the level of assembling or disassembling components in the existing layout of [1], supports the generality of X-ADC. Once the samples are obtained by the generic system, application-dependent algorithms use different processing methods in order to extract the relevant information.…”

Section: Introductionmentioning

confidence: 95%

“…In contrast to standard RF mixing with a single sinusoid, X-ADC requires periodic mixing, that is simultaneous multiplication with the multiple sinusoids (1) comprising pi(t). To support the nonordinary mixing additional circuitries were inserted: wideband equalization, passive mixing and adjustable power control with frequency reshaping option [1]. An elliptic filter with up to 14 stages allows a flexible choice for Hi(f ) in a wide range of pass and stop band combinations.…”

Section: B Circuit Workmentioning

confidence: 99%

“…The X prefix hints at the reduced sampling rate. We also describe a recent board-level prototype of the MWC [1], which serves as a reference X-ADC circuit.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Generic sensing hardware and real-time reconstruction for structured analog signals

Mishali

Hilgendorf

Shoshan

et al. 2011

2011 IEEE International Symposium of Circuits and Systems (ISCAS)

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Abstract-Generic acquisition hardware promotes a unified treatment of various signal classes. In modern applications involving wide input bandwidths, uniform sampling, the common practice for generic digitization, leads to prohibitively large sampling and processing rates due to the wide Nyquist bandwidth of the input. In this paper, we present the X-ADC system which narrows down the input bandwidth by analog preprocessing prior to sampling at rates substantially lower than Nyquist. As we show, the X-ADC strategy is generic in the sense that multitude radio and medical imaging applications with structured signals can utilize the same architecture for lowrate acquisition. A recently published sub-Nyquist hardware, which was designed according to the proposed X-ADC scheme, provides a concrete reference for the present study. We complement the generic acquisition by reporting on a real-time embedded implementation of a sub-Nyquist reconstruction algorithm. The embedded design enables, for example, fast spectrum sensing which is essential to real-time cognitive radio applications.

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Mathematics of Analog‐to‐Digital Conversion

Güntürk

2012

Comm Pure Appl Math

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As the performance of digital circuits and the capacity of digital communication channels have advanced steadily over the past decades, digital signals have replaced analog signals in nearly every technological application domain, offering robustness, ever increasing quality, and speed. At the same time, many signals that we perceive audiovisually (sound and video), or measure via instrumentation (e.g., geophysical signals and medical images), are analog in their nature. Consequently, not only are the analog‐to‐digital (A/D) and digital‐to‐analog (D/A) conversion processes as crucial as ever, but also the performance of these processes must improve to meet the increasing demands at the digital processing end. Both A/D and D/A conversion is necessarily carried out via analog devices bound by physical limitations such as imprecisions and noise, which present continual technological as well as theoretical challenges to achieving this objective. This article aims to introduce some of the modern mathematical ideas, developments, and challenges in this context from the author's perspective. © 2012 Wiley Periodicals, Inc.

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Xampling: analog to digital at sub-Nyquist rates

Cited by 376 publications

References 22 publications

From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals

From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals

Generic sensing hardware and real-time reconstruction for structured analog signals

Mathematics of Analog‐to‐Digital Conversion

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