LMPIT-Inspired Tests for Detecting a Cyclostationary Signal in Noise With Spatio-Temporal Structure

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dc.contributor.author Pries, Aaron
dc.contributor.author Schereier, Peter J
dc.contributor.author Ramírez García, David
dc.date.accessioned 2020-11-24T10:04:01Z
dc.date.available 2020-11-24T10:04:01Z
dc.date.issued 2018-09-01
dc.identifier.bibliographicCitation A. Pries, D. Ramírez and P. J. Schreier, "LMPIT-Inspired Tests for Detecting a Cyclostationary Signal in Noise With Spatio–Temporal Structure," in IEEE Transactions on Wireless Communications, vol. 17, no. 9, pp. 6321-6334, Sept. 2018
dc.identifier.issn 1536-1276
dc.identifier.uri http://hdl.handle.net/10016/31467
dc.description.abstract In spectrum sensing for cognitive radio, the presence of a primary user can be detected by making use of the cyclostationarity property of digital communication signals. For the general scenario of a cyclostationary signal in temporally colored and spatially correlated noise, it has previously been shown that an asymptotic generalized likelihood ratio test (GLRT) and locally most powerful invariant test (LMPIT) exist. In this paper, we derive detectors for the presence of a cyclostationary signal in various scenarios with structured noise. In particular, we consider noise that is temporally white and/or spatially uncorrelated. Detectors that make use of this additional information about the noise process have enhanced performance. We have previously derived GLRTs for these specific scenarios; here, we examine the existence of LMPITs. We show that these exist only for detecting the presence of a cyclostationary signal in spatially uncorrelated noise. For white noise, an LMPIT does not exist. Instead, we propose tests that approximate the LMPIT, and they are shown to perform well in simulations. Finally, if the noise structure is not known in advance, we also present hypothesis tests using our framework.
dc.description.sponsorship The work of A. Pries and P. J. Schreierwas supported by the German Research Foundation (DFG) under grant SCHR1384/6-1. The work of D. Ramírez has been partly supported by Ministerio de Economía of Spain under projects: OTOSIS (TEC2013-41718-R) and the COMONSENS Network (TEC2015-69648-REDC), by the Ministerio de Economía of Spain jointly with the European Commission (ERDF) under projects ADVENTURE (TEC2015-69868-C2-1-R) and CAIMAN(TEC2017-86921-C2-2-R), by the Comunidad de Madrid under projectCASI-CAM-CM (S2013/ICE-2845), and by the German Research Foun-dation (DFG) under Project RA 2662/2-1.
dc.language.iso eng
dc.publisher IEEE
dc.rights © 2018 IEEE
dc.subject.other Cyclostationarity
dc.subject.other Detection
dc.subject.other Generalized likelihood ratio test (GLRT)
dc.subject.other Interweave cognitive radio
dc.subject.other Locally most powerful invariant test (LMPIT)
dc.subject.other Spectrum sensing
dc.title LMPIT-Inspired Tests for Detecting a Cyclostationary Signal in Noise With Spatio-Temporal Structure
dc.type article
dc.subject.eciencia Telecomunicaciones
dc.identifier.doi 10.1109/TWC.2018.2859314
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. TEC2013-41718-R
dc.relation.projectID Comunidad de Madrid. S2013/ICE-2845
dc.relation.projectID Gobierno de España. TEC2015-69868-C2-1-R
dc.relation.projectID Gobierno de España. TEC2017-86921-C2-2-R
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 6321
dc.identifier.publicationissue 9
dc.identifier.publicationlastpage 6334
dc.identifier.publicationtitle IEEE Transactions on Wireless Communications
dc.identifier.publicationvolume 17
dc.identifier.uxxi AR/0000022037
dc.contributor.funder Comunidad de Madrid
dc.contributor.funder Ministerio de Economía y Competitividad (España)
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