liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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
On the Optimal K-term Approximation of a Sparse Parameter Vector MMSE Estimate
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-7599-4367
Linköping University, Department of Electrical Engineering, Information Coding. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-1082-8325
2009 (English)In: Proceedings of the 2009 IEEE Workshop on Statistical Signal Processing (SSP'09), IEEE , 2009, 245-248 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper considers approximations of marginalization sums thatarise in Bayesian inference problems. Optimal approximations ofsuch marginalization sums, using a fixed number of terms, are analyzedfor a simple model. The model under study is motivated byrecent studies of linear regression problems with sparse parametervectors, and of the problem of discriminating signal-plus-noise samplesfrom noise-only samples. It is shown that for the model understudy, if only one term is retained in the marginalization sum, thenthis term should be the one with the largest a posteriori probability.By contrast, if more than one (but not all) terms are to be retained,then these should generally not be the ones corresponding tothe components with largest a posteriori probabilities.

Place, publisher, year, edition, pages
IEEE , 2009. 245-248 p.
Keyword [en]
MMSE estimation, Bayesian inference, marginalization
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-25591DOI: 10.1109/SSP.2009.5278594ISI: 000274988800062ISBN: 978-1-4244-2709-3 (print)OAI: oai:DiVA.org:liu-25591DiVA: diva2:246025
Note
©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Erik Axell, Erik G. Larsson and Jan-Åke Larsson, On the Optimal K-term Approximation of a Sparse Parameter Vector MMSE Estimate, 2009, Proceedings of the 2009 IEEE Workshop on Statistical Signal Processing (SSP'09), 245-248. http://dx.doi.org/10.1109/SSP.2009.5278594 Available from: 2009-10-08 Created: 2009-10-08 Last updated: 2016-08-31Bibliographically approved
In thesis
1. Topics in Spectrum Sensing for Cognitive Radio
Open this publication in new window or tab >>Topics in Spectrum Sensing for Cognitive Radio
2009 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Cognitive radio is a new concept of reusing licensed spectrum in an unlicensed manner. Cognitive radio is motivated by recent measurements of spectrum utilization, showing unused resources in frequency, time and space. The spectrum must be sensed to detect primary user signals, in order to allow cognitive radios in a primary system. In this thesis we study some topics in spectrum sensing for cognitive radio.

The fundamental problem of spectrum sensing is to discriminate samples that contain only noise from samples that contain a very weak signal embedded in noise. We derive detectors that exploit known structures of the signal, for the cases of an OFDM modulated signal and an orthogonal space-time block coded signal. We derive optimal detectors, in the Neyman-Pearson sense, for a few different cases when all parameters are known. Moreover we study detection when the parameters, such as noise variance, are unknown. We propose solutions the problem of unknown parameters.

We also study system aspects of cognitive radio. More specifically, we investigate spectrum reuse of geographical spectrum holes in a frequency planned primary network. System performance is measured in terms of the achievable rate for the cognitive radio system. Simulation results show that a substantial sum-rate could be achieved if the cognitive radios communicate over small distances. However, the spectrum hole gets saturated quite fast, due to interference caused by the cognitive radios.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2009. 21 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1417
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-51748 (URN)978-91-7393-523-4 (ISBN)
Presentation
2009-12-21, Glashuset, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2009-11-20 Created: 2009-11-17 Last updated: 2017-01-13Bibliographically approved

Open Access in DiVA

fulltext(204 kB)738 downloads
File information
File name FULLTEXT01.pdfFile size 204 kBChecksum SHA-512
693aaed339d54726423e76fcb9e32dffe55abb3c50a3f4c12af7982de434e2849d57116c253f2ee3c15078ef155cd55ccb442427d4cd724dd2f5ba2aea99e367
Type fulltextMimetype application/pdf

Other links

Publisher's full textLink to Licentiate Thesis

Authority records BETA

Axell, ErikLarsson, Erik G.Larsson, Jan-Åke

Search in DiVA

By author/editor
Axell, ErikLarsson, Erik G.Larsson, Jan-Åke
By organisation
Communication SystemsThe Institute of TechnologyInformation Coding
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 738 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 1547 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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