TY - JOUR T1 - Multiantenna GLR detection of rank-one signals with known power spectral shape under spatially uncorrelated noise JF - IEEE Transactions on Signal Processing Y1 - 2016 A1 - Josep Sala A1 - Gonzalo Vázquez-Vilar A1 - R. López-Valcarce A1 - Saeid Sedighi A1 - Abbas Taherpour KW - cognitive radio KW - compass AB -

We establish the generalized likelihood ratio (GLR) test for a Gaussian signal of known power spectral shape and unknown rank-one spatial signature in additive white Gaussian noise with an unknown diagonal spatial correlation matrix. This is motivated by spectrum sensing problems in dynamic spectrum access (DSA), in which the temporal correlation of the primary signal can be assumed known up to a scaling, and where the noise is due to an uncalibrated receive array. For spatially independent identically distributed (i.i.d.) noise, the corresponding GLR test reduces to a scalar optimization problem, whereas the GLR detector in the general non-i.i.d. case yields a more involved expression, which can be computed via alternating optimization methods. Low signal-to-noise ratio (SNR) approximations to the detectors are given, together with an asymptotic analysis showing the influence on detection performance of the signal power spectrum and SNR distribution across antennas. Under spatial rank-P conditions, we show that the rank-one GLR detectors are consistent with a statistical criterion that maximizes the output energy of a beamformer operating on filtered data. Simulation results support our theoretical findings in that exploiting prior knowledge on the signal power spectrum can result in significant performance improvement.

VL - 64 IS - 23 ER - TY - JOUR T1 - Multiantenna GLR detection of rank-one signals with known power spectrum in white noise with unknown spatial correlation JF - IEEE Trans. on Signal Processing Y1 - 2012 A1 - Josep Sala A1 - Gonzalo Vázquez-Vilar A1 - R. López-Valcarce KW - cognitive radio KW - dynacs AB -
Multiple-antenna detection of a Gaussian signal with spatial rank one in temporally white Gaussian noise with arbitrary and  unknown spatial covariance is considered. This is motivated by spectrum sensing problems in the context of Dynamic Spectrum Access in which several secondary networks coexist but do not cooperate, creating a background of spatially correlated broadband interference. When the temporal correlation of the signal of interest is assumed known up to a scale factor, the corresponding Generalized Likelihood Ratio Test is shown to yield a scalar optimization problem. Closed-form expressions of the test are obtained for the general signal spectrum case in the low signal-to-noise ratio (SNR) regime, as well as for signals with binary-valued power spectrum in arbitrary SNR. The two resulting detectors turn out to be equivalent. An asymptotic approximation to the test distribution for the low-SNR regime is derived, closely matching empirical results from spectrum sensing simulation experiments.
VL - 60 IS - 6 ER - TY - JOUR T1 - Multiantenna Spectrum Sensing Exploiting Spectral a priori Information JF - IEEE Trans. on Wireless Communications Y1 - 2011 A1 - Gonzalo Vázquez-Vilar A1 - R. López-Valcarce A1 - Josep Sala KW - cognitive radio KW - dynacs KW - spectrum sensing VL - 10 IS - 12 ER - TY - CONF T1 - Multiantenna spectrum sensing for Cognitive Radio: overcoming noise uncertainty T2 - International Workshop on Cognitive Information Processing (CIP) Y1 - 2010 A1 - R. López-Valcarce A1 - Gonzalo Vázquez-Vilar A1 - Josep Sala JF - International Workshop on Cognitive Information Processing (CIP) CY - Elba Island, Italy ER -