DocumentCode :
1674276
Title :
Recovery of sparse signals from amplitude-limited sample sets
Author :
Polak, Adam C. ; Duarte, Marco F. ; Jackson, Robert W. ; Goeckel, Dennis L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Massachusetts, Amherst, MA, USA
fYear :
2013
Firstpage :
4663
Lastpage :
4667
Abstract :
Motivated by the compelling application of interference mitigation at wideband receivers in wireless communication and sensing systems, we consider the recovery of a frequency-sparse signal from samples of small magnitude. The standard ℓ1-norm minimization results in an inadequate signal-dependent recovery performance, and hence we introduce three techniques to improve the quality of recovery. The performance of each of these three techniques is characterized through numerical simulations, from which we conclude that each of the proposed techniques show the promise of substantially improving recovery performance.
Keywords :
compressed sensing; interference suppression; minimisation; radio receivers; signal sampling; amplitude-limited sample sets; frequency sparse signal; interference mitigation; numerical simulation; signal-dependent recovery performance; sparse signal recovery; standard ℓ1-norm minimization; wideband receiver; wireless communication; Compressed sensing; Interference; Matrix converters; Minimization; Receivers; Sensors; Wideband; cognitive radio; compressive sensing; interference rejection; nonlinear distortion; nonuniform sampling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2013.6638544
Filename :
6638544
Link To Document :
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