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Multiantenna GLR detection of rank-one signals with known power spectral shape under spatially uncorrelated noise
dc.contributor.author | Sala Álvarez, José |
dc.contributor.author | Vázquez Vilar, Gonzalo |
dc.contributor.author | López Valcarce, Roberto |
dc.contributor.author | Sedighi, Saeid |
dc.contributor.author | Taherpour, Abbas |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2016-10-13T13:08:29Z |
dc.date.available | 2016-10-13T13:08:29Z |
dc.date.issued | 2016-12-01 |
dc.identifier.citation | Sala, J., Vázquez, G., López, R., Sedighi, S., Taherpour, A. Multiantenna GLR detection of rank-one signals with known power spectral shape under spatially uncorrelated noise. "IEEE transactions on signal processing", 1 Desembre 2016, vol. 64, núm. 23, p. 6269-6283. |
dc.identifier.issn | 1053-587X |
dc.identifier.uri | http://hdl.handle.net/2117/90744 |
dc.description.abstract | 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, 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. |
dc.format.extent | 15 p. |
dc.language.iso | eng |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Antenes i agrupacions d'antenes |
dc.subject.lcsh | Antennas (Electronics) |
dc.subject.lcsh | Cognitive radio networks |
dc.subject.other | GLRT |
dc.subject.other | Detection |
dc.subject.other | Spectrum sensing |
dc.subject.other | Cognitive radio |
dc.subject.other | Multiple antenna |
dc.subject.other | Uncalibrated array |
dc.title | Multiantenna GLR detection of rank-one signals with known power spectral shape under spatially uncorrelated noise |
dc.type | Article |
dc.subject.lemac | Antenes (Electrònica) |
dc.subject.lemac | Ràdio cognitiva |
dc.contributor.group | Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions |
dc.identifier.doi | 10.1109/TSP.2016.2601290 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://ieeexplore.ieee.org.recursos.biblioteca.upc.edu/document/7547276/?reload=true |
dc.rights.access | Open Access |
local.identifier.drac | 19102522 |
dc.description.version | Postprint (published version) |
dc.relation.projectid | info:eu-repo/grantAgreement/MINECO//TEC2013-47020-C2-2-R/ES/COMUNICACIONES Y PROCESADO DE SEÑAL EN ESCENARIOS ADVERSOS - 1/ |
dc.relation.projectid | info:eu-repo/grantAgreement/AGAUR/PRI2010-2013/2014SGR60 |
local.citation.author | Sala, J.; Vázquez, G.; López, R.; Sedighi, S.; Taherpour, A. |
local.citation.publicationName | IEEE transactions on signal processing |
local.citation.volume | 64 |
local.citation.number | 23 |
local.citation.startingPage | 6269 |
local.citation.endingPage | 6283 |
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