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Random Sampling for Analog-to-Information Conversion of Wideband Signals

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7 Author(s)
Jason Laska ; Department of Electrical and Computer Engineering, Rice University, Houston, TX ; Sami Kirolos ; Yehia Massoud ; Richard Baraniuk
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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 33times sub-Nyquist average sampling rate with little degradation in signal quality

Published in:

2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software

Date of Conference:

Oct. 2006