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In this paper, we propose a robust compressive sampling approach for wideband spectrum sensing in cognitive radios in the presence of non-Gaussian noise. Wideband cognitive radios can be subjected to heterogeneous spectral activities from various sources rendering the resultant noise non- Gaussian. While conventional detectors (e.g. least-squares estimates) are known to be sensitive to the Non-Gaussian...
In this paper, we propose detectors (both parametric and robust) for wideband spectrum sensing in cognitive radios (CR's). The proposed detectors are able to detect spectral activity over a wide frequency range, while assuming little knowledge about the signals of interest. The parametric detector is based on a locally optimal (LO) Neyman-Pearson (NP) test and assumes a known non-Gaussian noise distribution...
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