ARCHITECTURES AND ISSUES FOR GIGASAMPLE/SECOND ADCs

Poulton, K.; Neff, Raymond K.; Setterberg, B.; Wuppermann, Bernd; Kopley, T.E.

doi:10.1007/1-4020-5186-7_2

Cited by 3 publications

(5 citation statements)

References 11 publications

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“…Even though CMOS scaling has made digital circuits highly power efficient, large amount of digital data is generated, which requires significant power consumption in digital post-processing. Digital power is estimated to be the same as the total power consumed in backend electronic ADCs (as a similar trend is observed in [13]). Using these numbers with 1-mW input optical power at each photo-detector, the total optical and electrical powers can be calculated.…”

Section: Power Calculations For a Time-stretch Adcsupporting

confidence: 54%

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A sound barrier for silicon?

Muller

2005

Nature Mater

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Section: Power Calculations For a Time-stretch Adcsupporting

confidence: 54%

“…However, from the trend seen in Fig. 1 and in [13], and from the discussion in the following subsection, it becomes clear that in reality, the energy per conversion step scales roughly as f s , i.e., power dissipation is proportional to f 2 s in high-speed ADCs.…”

Section: Fundamental Limits To Power Dissipation In Adcsmentioning

confidence: 92%

A sound barrier for silicon?

Muller

2005

Nature Mater

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“…* The k-th sub-converter has intrinsic gain and sampling time error of (G k, zlt k), which is unknown. (2) Note that zk[n]'s and yk[n]'s are both observable and carry the same information since Gk's are known to the algorithm.…”

Section: System Configurationmentioning

confidence: 99%

“…One of the sensible choices of equalization reference is the following average autocorrelations, (2). For convenience, we ignore common time delay and assume the following in further discussions.…”

Section: A Selection Ofequalization Referencementioning

confidence: 99%

“…It has been well known that, however, the spectral performance of a TIADC is limited by aliasing spectra due to mismatches in subconverter gain, sampling time, etc [1], [11]. Currently known mismatch correction techniques can be categorized into training (foreground) [2], [11] and blind (background) methods [3]- [10], [12]- [13]. In this paper, we are interested in blind methods which are generally capable of uninterrupted operation and of tracking time-varying errors.…”

Section: Introductionmentioning

confidence: 99%

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A Low Computation Adaptive Blind Mismatch Correction for Time-Interleaved ADCs

Seo

Rodwell

Madhow

2006

2006 49th IEEE International Midwest Symposium on Circuits and Systems

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We introduce a computationally very efficient technique for adaptive blind correction of M-channel time-interleaved analog-todigital converters (TIADC). Under wide-sense stationary (WSS) and bandlimited input assumption, gain and timing errors are estimated in the digital domain by detecting shift-dependence of TIADC output autocorrelation. Input signal integrity is preserved since there is no analog input pre-processing. Gain mismatch is digitally corrected, but sampling time mismatches are compensated in the analog domain by adjusting individual clock timing offsets. This mixed-domain technique takes advantage of each domain to dramatically reduce computational requirement on the digital side. As a by-product, convergence is guaranteed under mild conditions with arbitrary number of channels.Experimental demonstration is performed by a proof-of-concept, M=4 400-MSPS real-time setup. After 300 iterations, mismatch spurs are suppressed by more than 40-dB, down to -80dB below the signal at -171MHz. This is the first proposal and demonstration of lowcomputation blind technique with guaranteed convergence.

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Photonic time‐stretch digitizer and its extension to real‐time spectroscopy and imaging

Fard

Gupta

Jalali

2013

Laser & Photonics Reviews

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Real-time wideband digitizers are the key building block in many systems including oscilloscopes, signal intelligence, electronic warfare, and medical diagnostics systems. Continually extending the bandwidth of digitizers has hence become a central challenge in electronics. Fortunately, it has been shown that photonic pre-processing of wideband signals can boost the performance of electronic digitizers. In this article, the underlying principle of the time-stretch analog-to-digital converter (TSADC) that addresses the demands on resolution, bandwidth, and spectral efficiency is reviewed. In the TSADC, amplified dispersive Fourier transform is used to slow down the analog signal in time and hence to compress its bandwidth. Simultaneous signal amplification during the time-stretch process compensates for parasitic losses leading to high signal-to-noise ratio. This powerful concept transforms the analog signal's time scale such that it matches the slower time scale of the digitizer. A summary of time-stretch technology's extension to highthroughput single-shot spectroscopy, a technique that led to the discovery of optical rouge waves, is also presented. Moreover, its application in high-throughput imaging, which has recently led to identification of rogue cancer cells in blood with record sensitivity, is discussed.

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ARCHITECTURES AND ISSUES FOR GIGASAMPLE/SECOND ADCs

Cited by 3 publications

References 11 publications

A sound barrier for silicon?

A sound barrier for silicon?

A Low Computation Adaptive Blind Mismatch Correction for Time-Interleaved ADCs

Photonic time‐stretch digitizer and its extension to real‐time spectroscopy and imaging

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