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Wideband Spectrum Sensing Based on Riemannian Distance for Cognitive Radio Networks

Lu, Q; Yang, S; Liu, F; (2017) Wideband Spectrum Sensing Based on Riemannian Distance for Cognitive Radio Networks. Sensors , 17 (4) , Article 661. 10.3390/s17040661. Green open access

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Abstract

Detecting the signals of the primary users in the wideband spectrum is a key issue for cognitive radio networks. In this paper, we consider the multi-antenna based signal detection in a wideband spectrum scenario where the noise statistical characteristics are assumed to be unknown. We reason that the covariance matrices of the spectrum subbands have structural constraints and that they describe a manifold in the signal space. Thus, we propose a novel signal detection algorithm based on Riemannian distance and Riemannian mean which is different from the traditional eigenvalue-based detector (EBD) derived with the generalized likelihood ratio criterion. Using the moment matching method, we obtain the closed expression of the decision threshold. From the considered simulation settings, it is shown that the proposed Riemannian distance detector (RDD) has a better performance than the traditional EBD in wideband spectrum sensing.

Type: Article
Title: Wideband Spectrum Sensing Based on Riemannian Distance for Cognitive Radio Networks
Open access status: An open access version is available from UCL Discovery
DOI: 10.3390/s17040661
Publisher version: https://doi.org/10.3390/s17040661
Language: English
Additional information: This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Keywords: cognitive radio; wideband spectrum sensing; information geometry; Riemannian distance; Riemannian mean; moment matching
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10061404
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