Random sampling for analog-to-information conversion of wideband signals

Jason Laska; Sami Kirolos; Yehia Massoud; Richard Baraniuk; Anna Gilbert; Mark Iwen; Martin Strauss

doi:10.1109/DCAS.2006.321048

Random sampling for analog-to-information conversion of wideband signals

Jason Laska, Sami Kirolos, Yehia Massoud, Richard Baraniuk, Anna Gilbert, Mark Iwen, Martin Strauss

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

233 Scopus citations

Abstract

We develop a framework for analog-to-information conversion that enables sub-Nyquist acquisition and processing of wideband signals that are sparse in a local Fourier representation. The first component of the framework is a random sampling system that can be implemented in practical hardware. The second is an efficient information recovery algorithm to compute the spectrogram of the signal, which we dub the sparsogram. A simulated acquisition of a frequency hopping signal operates at 33x sub-Nyquist average sampling rate with little degradation in signal quality. ©2006 IEEE.

Original language	English (US)
Title of host publication	2006 IEEE Dallas/CAS Workshop onDesign, Applications, Integration and Software, DCAS-06
Pages	119-122
Number of pages	4
DOIs	https://doi.org/10.1109/DCAS.2006.321048
State	Published - Dec 1 2006
Externally published	Yes

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Generated from Scopus record by KAUST IRTS on 2022-09-13

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10.1109/DCAS.2006.321048

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abstract = "We develop a framework for analog-to-information conversion that enables sub-Nyquist acquisition and processing of wideband signals that are sparse in a local Fourier representation. The first component of the framework is a random sampling system that can be implemented in practical hardware. The second is an efficient information recovery algorithm to compute the spectrogram of the signal, which we dub the sparsogram. A simulated acquisition of a frequency hopping signal operates at 33x sub-Nyquist average sampling rate with little degradation in signal quality. {\textcopyright}2006 IEEE.",

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doi = "10.1109/DCAS.2006.321048",

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AU - Laska, Jason

AU - Kirolos, Sami

AU - Massoud, Yehia

AU - Baraniuk, Richard

AU - Gilbert, Anna

AU - Iwen, Mark

AU - Strauss, Martin

N1 - Generated from Scopus record by KAUST IRTS on 2022-09-13

PY - 2006/12/1

Y1 - 2006/12/1

N2 - We develop a framework for analog-to-information conversion that enables sub-Nyquist acquisition and processing of wideband signals that are sparse in a local Fourier representation. The first component of the framework is a random sampling system that can be implemented in practical hardware. The second is an efficient information recovery algorithm to compute the spectrogram of the signal, which we dub the sparsogram. A simulated acquisition of a frequency hopping signal operates at 33x sub-Nyquist average sampling rate with little degradation in signal quality. ©2006 IEEE.

AB - We develop a framework for analog-to-information conversion that enables sub-Nyquist acquisition and processing of wideband signals that are sparse in a local Fourier representation. The first component of the framework is a random sampling system that can be implemented in practical hardware. The second is an efficient information recovery algorithm to compute the spectrogram of the signal, which we dub the sparsogram. A simulated acquisition of a frequency hopping signal operates at 33x sub-Nyquist average sampling rate with little degradation in signal quality. ©2006 IEEE.

UR - http://ieeexplore.ieee.org/document/4115127/

UR - http://www.scopus.com/inward/record.url?scp=46149153160&partnerID=8YFLogxK

U2 - 10.1109/DCAS.2006.321048

DO - 10.1109/DCAS.2006.321048

M3 - Conference contribution

SN - 1424406692

SP - 119

EP - 122

BT - 2006 IEEE Dallas/CAS Workshop onDesign, Applications, Integration and Software, DCAS-06

ER -

Random sampling for analog-to-information conversion of wideband signals

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