Title :
Compressive sensing with optimal sparsifying basis and applications in spectrum sensing
Author :
Youngjune Gwon ; Kung, H.T. ; Vlah, D.
Author_Institution :
Harvard Univ., Cambridge, MA, USA
Abstract :
We describe a method of integrating Karhunen-Loève Transform (KLT) into compressive sensing, which can as a result improve the compression ratio without affecting the accuracy of decoding. We present two complementary results: 1) by using KLT to find an optimal basis for decoding we can drastically reduce the number of measurements for compressive sensing used in applications such as radio spectrum analysis; 2) by using compressive sensing we can estimate and recover the KLT basis from compressive measurements of an input signal. In particular, we propose CS-KLT, an online estimation algorithm to cope with nonstationarity of wireless channels in reality. We validate our results with empirical data collected from a wideband UHF spectrum and field experiments to detect multiple radio transmitters, using software-defined radios.
Keywords :
compressed sensing; decoding; radio transmitters; software radio; spread spectrum communication; wireless channels; CS-KLT; Karhunen-Loe ve transform; compressive measurements; compressive sensing; decoding; empirical data; multiple radio transmitters; online estimation; optimal sparsifying basis; radio spectrum analysis; software-defined radios; spectrum sensing; wideband UHF spectrum; wireless channels;
Conference_Titel :
Global Communications Conference (GLOBECOM), 2012 IEEE
Conference_Location :
Anaheim, CA
Print_ISBN :
978-1-4673-0920-2
Electronic_ISBN :
1930-529X
DOI :
10.1109/GLOCOM.2012.6503977