| Paper ID | SPTM-1.1 |
| Paper Title |
MEASURE-TRANSFORMED COVARIANCE TEST FOR ROBUST SPECTRUM SENSING |
| Authors |
Yair Sorek, Koby Todros, Ben-Gurion University, Israel |
| Session | SPTM-1: Detection Theory and Methods 1 |
| Location | Gather.Town |
| Session Time: | Tuesday, 08 June, 13:00 - 13:45 |
| Presentation Time: | Tuesday, 08 June, 13:00 - 13:45 |
| Presentation |
Poster
|
| Topic |
Signal Processing Theory and Methods: [SSP] Statistical Signal Processing |
| IEEE Xplore Open Preview |
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| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
In this paper, we develop a new robust spectrum sensing method for MIMO cognitive radios in the presence of heavy-tailed noise. The proposed sensing technique, called measure-transformed covariance test (MTCT), operates by applying a transform to the probability measure of the data. The considered probability measure transform is structured by a non-negative function, called MT-function, that weights the data points. We show that proper selection of the MT-function, under the class of zero-centered spherical Gaussian functions, can lead to significant mitigation of heavy-tailed noise effects. Simulation studies illustrate the advantages of the proposed MTCT comparing to state-of-the-art spectrum sensing techniques. |
