| Title: | Compressive Sensing with Optimal Sparsifying Basis and Applications in Spectrum Sensing |
| Author: |
Vlah, Dario; Kung, H.T. T.; Gwon, Youngjune Lee
Note: Order does not necessarily reflect citation order of authors. |
| Citation: | Gwon, Youngjune, H.T. Kung, and Dario Vlah. 2012. Compressive sensing with optimal sparsifying basis and applications in spectrum sensing. Paper presented at IEEE 2012 Global Telecommunications Conference (GLOBECOM 2012), Annaheim, CA, December 3-7, 2012. |
| Full Text & Related Files: |
2012-globecom-gwon-kung-vlah-1.pdf (1.607Mb; PDF)
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| 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 eld experiments to detect multiple radio transmitters, using software-defined radios. |
| Other Sources: | http://www.eecs.harvard.edu/~htk/publication/2012-globecom-gwon-kung-vlah.pdf |
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| Citable link to this page: | http://nrs.harvard.edu/urn-3:HUL.InstRepos:10000991 |
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