Detection of Rank-P Signals in Cognitive Radio Networks With Uncalibrated Multiple Antennas
Spectrum sensing is a key component of the Cognitive Radio paradigm. Primary signals are typically detected with uncalibrated receivers at Signal-to-Noise Ratios (SNRs) well below decodability levels. Multiantenna detectors exploit spatial independence of receiver thermal noise to boost detection performance and robustness. The authors study the problem of detecting a Gaussian signal with rank-P unknown spatial covariance matrix in spatially uncorrelated Gaussian noise with unknown covariance using multiple antennas. The Generalized Likelihood Ratio Test (GLRT) is derived for two scenarios.