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 | Click here to view in IEEE Xplore | ||
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. |