Compressed sensing for wideband cognitive radios
Document Type
Conference Proceeding
Publication Date
8-6-2007
Abstract
In the emerging paradigm of open spectrum access, cognitive radios dynamically sense the radio-spectrum environment and must rapidly tune their transmitter parameters to efficiently utilize the available spectrum. The unprecedented radio agility envisioned, calls for fast and accurate spectrum sensing over a wide bandwidth, which challenges traditional spectral estimation methods typically operating at or above Nyquist rates. Capitalizing on the sparseness of the signal spectrum in open-access networks, this paper develops compressed sensing techniques tailored for the coarse sensing task of spectrum hole identification. Sub-Nyquist rate samples are utilized to detect and classify frequency bands via a waveletbased edge detector. Because spectrum location estimation takes priority over fine-scale signal reconstruction, the proposed novel sensing algorithms are robust to noise and can afford reduced sampling rates. © 2007 IEEE.
Publication Title
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Recommended Citation
Tian, Z.,
&
Giannakis, G.
(2007).
Compressed sensing for wideband cognitive radios.
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings,
4.
http://doi.org/10.1109/ICASSP.2007.367330
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/10536
