Document
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Locally optimum detection for spectrum sensing in cognitive radio
type: Document
type: Thing
freetext keyword: Additive White Gaussian noise; BPSK modulation; Cognitive radio; Cognitive radio network; Energy detectors; High noise; Key feature; Linear modulations; Locally optimum; Low Power; Low SNR; Noise power; Probability of false alarm; Second order moment; Simulation result; Spectrum sensing; Sufficient statistics; Binary phase shift keying; Gaussian noise (electronic); Method of moments; Optical communication; Radio; Radio broadcasting; Signal detection; White noise; Wireless networks; Detectors
date time value: conference paper date 8630
doi: 10.1109/CROWNCOM.2009.5189063
has publication venue: Proceedings of the 2009 4th International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CROWNCOM 2009
origen: scopus
type: Article
abstract: Spectrum sensing is a key feature in cognitive radio networks. We propose a locally optimum (LO) detector, which is known to be optimum at low SNR. This is desirable in cognitive radio since the primary user's signal may exhibit a very low power at the cognitive user's transmitter. We focus here on linear modulation in the presence of an unknown phase shift and additive white Gaussian noise. In the case of BPSK modulation, the sufficient statistic of the LO detector is shown to be the sum of the absolute second-order moment (i.e., energy) and second-order moment (pseudo-energy) estimates. For higher size constellation, it is proven that the energy detector is locally optimum. The paper also addresses the issue of noise power uncertainty, to which the energy detector is very sensitive. Although the proposed LO detector is shown to be less sensitive than the energy detector, its performance does deteriorate at high noise power mismatch values. To overcome this problem, we also propose a detector whose probability of false alarm is independent of the noise power. Simulation results show that the proposed detectors in the case of BPSK significantly outperform the energy detector. Further, the complexity of the proposed detectors is only slightly higher than that of the energy detector. © 2009 IEEE.
crisid: 8630
related by: authorship_59707
estado: published
type: Generically Dependent Continuant
abstract: Spectrum sensing is a key feature in cognitive radio networks. We propose a locally optimum (LO) detector, which is known to be optimum at low SNR. This is desirable in cognitive radio since the primary user%27s signal may exhibit a very low power at the cognitive user%27s transmitter. We focus here on linear modulation in the presence of an unknown phase shift and additive white Gaussian noise. In the case of BPSK modulation, the sufficient statistic of the LO detector is shown to be the sum of the absolute second-order moment (i.e., energy) and second-order moment (pseudo-energy) estimates. For higher size constellation, it is proven that the energy detector is locally optimum. The paper also addresses the issue of noise power uncertainty, to which the energy detector is very sensitive. Although the proposed LO detector is shown to be less sensitive than the energy detector, its performance does deteriorate at high noise power mismatch values. To overcome this problem, we also propose a detector whose probability of false alarm is independent of the noise power. Simulation results show that the proposed detectors in the case of BPSK significantly outperform the energy detector. Further, the complexity of the proposed detectors is only slightly higher than that of the energy detector. © 2009 IEEE.
related by: authorship_59708
type: Continuant
type: Conference Paper
most specific type: Document
type: Information Content Entity
related by: authorship_59706
related by: authorship_59709
most specific type: Conference Paper
artnum: 5189063
EI dscopus: 2-s2.0-70449434881
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Proceedings of the 2009 4th International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CROWNCOM 2009
publication venue for: Locally optimum detection for spectrum sensing in cognitive radio
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type: Information Content Entity
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type: Generically Dependent Continuant
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RDF description of Locally optimum detection for spectrum sensing in cognitive radio - http://orbis.uaslp.mx/vivo/individual/scopus8629
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date: 2026-08-27T20:12:22
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Conference Paper
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