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Distributed Diffusion LMS based Energy Detection
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Tallinn Univ. of Technol., Tallinn, Estonia.
Tallinn Univ. of Technol., Tallinn, Estonia.
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-3599-5584
2014 (English)In: Proceedings of 6th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), 2014, 2014, p. 176-183Conference paper, Published paper (Refereed)
Abstract [en]

Cognitive radio (CR) is seen as a promising technology to make radio spectrum usage more effective by providing an opportunistic access for secondary users to the licensed spectrum areas. CR systems need to detect the presence of a primary user (PU) signal by continuously sensing the spectrum area of interest. Radiowave propagation effects like fading and shadowing often complicate sensing of spectrum holes because the PU signal can be weak in a particular area. Cooperative spectrum sensing is seen as a prospective solution to enhance the detection of PU signals. This paper studies distributed spectrum sensing in a cognitive radio context. We investigate distributed energy detection schemes without using any fusion center. We propose the usage of distributed, diffusion least mean square (LMS) type of power estimation algorithms. In this paper an Adapt and Combine (ATC) diffusion based power estimation scheme is proposed and the performance is compared with the Combine and Adapt (CTA) and ring-around schemes in a common framework. The PU signal is assumed to be slowly fading. We analyse the resulting energy detection performance and verify the theoretical findings through simulations.

Place, publisher, year, edition, pages
2014. p. 176-183
Keyword [en]
Cognitive radio, distributed estimation, diffusion LMS, diffusion networks, distributed detection, energy detection
National Category
Signal Processing
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-163722DOI: 10.1109/ICUMT.2014.7002099OAI: oai:DiVA.org:kth-163722DiVA, id: diva2:802190
Conference
6th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), 2014
Note

QC 20150414

Available from: 2015-04-11 Created: 2015-04-11 Last updated: 2015-04-14Bibliographically approved

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Bengtsson, Mats

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  • apa
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