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Spectrum estimation and spectrum hole opportunities prediction for cognitive radios using higher-order statistics
Institute of Informatics, Brandenburg University of Technology, Cottbus, Germany.
Institute of Informatics, Brandenburg University of Technology, Cottbus, Germany.
Halmstad University, School of Information Technology.
Halmstad University, School of Information Technology.
2011 (English)In: 2011 Wireless Advanced (WiAd 2011), Piscataway, NJ: IEEE, 2011, p. 213-217, article id 5983313Conference paper, Published paper (Refereed)
Abstract [en]

Cognitive Radio (CR) is a wireless advanced technology which can utilize an unlicensed as well as a licensed spectrum without a harmful interference to the primary users. An unbiased consistent spectrum estimator is required for the primary user’s detection (sensing) for distinguishing the narrow band signals in a noisy environment. Cognitive radio’s hardware solutions available in a commercial market are frequency band constrained at RF Front-End. In multi-dimensional radio spectrum space any of the dimension: time, frequency, code or space can be used as a transmission opportunity. The spectrum hole time opportunistic prediction is a promising solution to determine the free time slots for transmission within a frequency band. This paper presents classical and parametric statistical spectrum estimators for primary user’s detection. It also presents statistical auto-regressive and moving average predictive modeling for grey-hole spectrum opportunities prediction in a time domain for cognitive radios where frequency, code and space (geographical location) are operational constraints. A prototype system for a cognitive radio is built on top of the software-defined radio in a MATLAB/-Simulink and interfaced with an USRP2 main-board and RFX2400 daughter-board from Ettus Research LLC. © 2011 IEEE.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE, 2011. p. 213-217, article id 5983313
Keywords [en]
Auto-regressive moving average model, Cognitive radio, Periodograms, software defined radio, Spectrum estimation, USRP2, Digital signal processing, Estimation, Forecasting, Frequency bands, Frequency domain analysis, Hardware, Radio systems, Radio transmission, Spectrum analysis, Time domain analysis, Time series, Time series analysis, Radio broadcasting
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:hh:diva-37512DOI: 10.1109/WiAd.2011.5983313Scopus ID: 2-s2.0-80052466686ISBN: 978-1-4577-0109-2 (electronic)ISBN: 978-1-4577-0110-8 (print)ISBN: 978-1-4577-0108-5 (electronic)OAI: oai:DiVA.org:hh-37512DiVA, id: diva2:1288559
Conference
2011 Wireless Advanced, WiAd 2011, London, United Kingdom, 20-22 June, 2011
Available from: 2019-02-13 Created: 2019-02-13 Last updated: 2019-02-13Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf