A unified framework for GLRT-based spectrum sensing of signals with covariance matrices with known eigenvalue multiplicities

In this paper, we create a unified framework for spectrum sensing of signals which have covariance matrices with known eigenvalue multiplicities. We derive the generalized likelihood-ratio test (GLRT) for this problem, with arbitrary eigenvalue multiplicities under both hypotheses. We also show a number of applications to spectrum sensing for cognitive radio and show that the GLRT for these applications, of which some are already known, are special cases of the general result.

• Type: Journal
• Year: 2011
• Where: ICASSP
• Authors: Erik Axell, Erik G. Larsson
• Keywords: Arbitrary Eigenvalue Multiplicities, Eigenvalue Multiplicities, Generalized Likelihood-ratio Test, ICASSP 2011, Signal Processing