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

226 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.

Original languageEnglish (US)
Title of host publication2006 IEEE Dallas ICAS Workshop on Design, Applications, Integration and Software, DCAS-06
Pages119-122
Number of pages4
DOIs
StatePublished - 2006
Event2006 IEEE Dallas ICAS Workshop on Design, Applications, Integration and Software, DCAS-06 - Richardson, TX, United States
Duration: Oct 29 2006Oct 30 2006

Publication series

Name2006 IEEE Dallas/CAS Workshop onDesign, Applications, Integration and Software, DCAS-06

Other

Other2006 IEEE Dallas ICAS Workshop on Design, Applications, Integration and Software, DCAS-06
Country/TerritoryUnited States
CityRichardson, TX
Period10/29/0610/30/06

ASJC Scopus subject areas

  • Computer Science Applications
  • Software

Fingerprint

Dive into the research topics of 'Random sampling for analog-to-information conversion of wideband signals'. Together they form a unique fingerprint.

Cite this