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Adaptive noise tracking for Cognitive Radios under more realistic operation conditions
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.
2014 (English)In: IEEE Instrumentation and Measurement Technology Conference, 2014, p. 1339-1344Conference paper, Published paper (Refereed)
Abstract [en]

Normal operation conditions of cognitive radio applications require signal processing techniques that can be executed in real time. One of the first steps is to sense the occupied or free frequency channels. Two major drawbacks in the current techniques are that they assume (i) the noise as white and (ii) the measured spectrum as time-invariant. In real world, the noise is (i) colored so it disturbs the signal unevenly and (ii) its spectrum changes over time. Hence, tracking the time-varying noise spectrum can become crucial to remove the noise contributions and enhance the estimate of the received signal. In this paper, we study an auto-regressive model to develop an adaptive noise tracking technique using a Kalman filter such that an extension of Boll's noise subtraction technique, designed for audio noise cancellation, becomes feasible when adjusted to cognitive radio scenarios. Simulation results show the performance of this technique. 

Place, publisher, year, edition, pages
2014. p. 1339-1344
Series
IEEE Instrumentation and Measurement Technology Conference, ISSN 1091-5281
Keywords [en]
auto-reg ressive model, cognitive radio, denoising, noise tracking, power spectrum, spectral subtraction, Kalman filters, Planning, Signal processing, Spurious signal noise, Sustainable development, Auto regressive models, De-noising, Noise cancellation, Noise contributions, Operation conditions, Signal processing technique, Spectral subtractions, Radio systems
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hig:diva-18459DOI: 10.1109/I2MTC.2014.6860964Scopus ID: 2-s2.0-84905686705ISBN: 978-146736385-3 (print)OAI: oai:DiVA.org:hig-18459DiVA, id: diva2:770214
Conference
2014 IEEE International Instrumentation and Measurement Technology Conference: Instrumentation and Measurement for Sustainable Development, I2MTC 2014, 12-15 May 2014, Montevideo
Available from: 2014-12-10 Created: 2014-12-10 Last updated: 2018-03-13Bibliographically approved

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Van Moer, Wendy

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CiteExportLink to record
Permanent link

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