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Kronecker-Based Fusion Rule for Cooperative Spectrum Sensing with Multi-Antenna Receivers
Electrical Engineering, University of Engineering and Technology of Peshawar, Pakistan.
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
Telecommunications and Systems Engineering, Universitat Autònoma de Barcelona, Spain.
Universitat Autònoma de Barcelona, Spain. (Telecommunications and Systems Engineering)
2014 (English)In: Electronics, ISSN 2079-9292, Vol. 3, no 4, 675-688 p.Article in journal (Refereed) Published
Abstract [en]

This paper considers a novel fusion rule for spectrum sensing scheme for a cognitive radio network with multi-antenna receivers. The proposed scheme exploits the fact that when any primary signal is present, measurements are spatially correlated due to presence of inter-antenna and inter-receiver spatial correlation. In order to exploit this spatial structure, the generalized likelihood ratio test (GLRT) operates with the determinant of the sample covariance matrix. Therefore, it depends on the sample size N and the dimensionality of the received data (i.e., the number of receivers K and antennas L). However, when the dimensionality fK; Lg is on the order, or larger than the sample size N, the GLRT degenerates due to the ill-conditioning of the sample covariance matrix. In order to circumvent this issue, we propose two techniques that exploit the inner spatial structure of the received observations by using single pair and multi-pairs Kronecker products. The performance of the proposed detectors is evaluated by means of numerical simulations, showing important advantages with respect to the traditional (i.e., unstructured) GLRT approach.

Place, publisher, year, edition, pages
2014. Vol. 3, no 4, 675-688 p.
National Category
Signal Processing
URN: urn:nbn:se:kth:diva-165269DOI: 10.3390/electronics3040675ScopusID: 2-s2.0-84958149061OAI: diva2:807798

QC 20150504

Available from: 2015-04-24 Created: 2015-04-24 Last updated: 2015-05-04Bibliographically approved

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Jansson, Magnus
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Signal ProcessingACCESS Linnaeus Centre
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