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 proceedingConference contribution

230 Scopus citations


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 languageEnglish (US)
Title of host publication2006 IEEE Dallas/CAS Workshop onDesign, Applications, Integration and Software, DCAS-06
Number of pages4
StatePublished - Dec 1 2006
Externally publishedYes

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


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