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Topics in Spectrum Sensing for Cognitive Radio
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
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: urn:nbn:se:liu:diva-51748ISBN: 978-91-7393-523-4 (print)OAI: oai:DiVA.org:liu-51748DiVA: diva2:277285
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
List of papers
1. A Bayesian Approach to Spectrum Sensing, Denoising and Anomaly Detection
Open this publication in new window or tab >>A Bayesian Approach to Spectrum Sensing, Denoising and Anomaly Detection
2009 (English)In: Proceedings of the 34th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'09), 2009, 2333-2336 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper deals with the problem of discriminating samples that contain only noise from samples that contain a signal embedded in noise. The focus is on the case when the variance of the noise is unknown. We derive the optimal soft decision detector using a Bayesian approach. The complexity of this optimal detector grows exponentially with the number of observations and as a remedy, we propose a number of approximations to it. The problem under study is a fundamental one and it has applications in signal denoising, anomaly detection, and spectrum sensing for cognitive radio. We illustrate the results in the context of the latter.

Series
Acoustics, Speech and Signal Processing, ISSN 1520-6149 ; 2009
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-25592 (URN)10.1109/ICASSP.2009.4960088 (DOI)978-1-4244-2354-5 (ISBN)978-1-4244-2353-8 (ISBN)
Conference
34th IEEE international conference on acoustics, speech and signal processing,19-24 April, Taipei, Taiwan
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 and Erik G. Larsson, A Bayesian Approach to Spectrum Sensing, Denoising and Anomaly Detection, 2009, Proceedings of the 34th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'09), 2333-2336. http://dx.doi.org/10.1109/ICASSP.2009.4960088Available from: 2009-10-08 Created: 2009-10-08 Last updated: 2016-08-31Bibliographically approved
2. On the Optimal K-term Approximation of a Sparse Parameter Vector MMSE Estimate
Open this publication in new window or tab >>On the Optimal K-term Approximation of a Sparse Parameter Vector MMSE Estimate
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
Keyword
MMSE estimation, Bayesian inference, marginalization
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-25591 (URN)10.1109/SSP.2009.5278594 (DOI)000274988800062 ()978-1-4244-2709-3 (ISBN)
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
3. Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance
Open this publication in new window or tab >>Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance
2011 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 29, no 2, 290-304 p.Article in journal (Refereed) Published
Abstract [en]

We consider spectrum sensing of OFDM signals in an AWGN channel. For  the case of completely known noise and signal powers, we set up  a vector-matrix model for an OFDM signal with a cyclic prefix and  derive the optimal Neyman-Pearson detector from first  principles. The optimal detector exploits the inherent correlation  of the OFDM signal incurred by the repetition of data in the cyclic  prefix, using knowledge of the length of the cyclic prefix and the  length of the OFDM symbol. We compare the optimal detector to the energy  detector numerically. We show that the energy detector is  near-optimal (within 1 dB SNR) when the noise variance is  known. Thus, when the noise power is known, no substantial gain can  be achieved by using any other detector than the energy detector.

For the case of completely unknown noise and signal powers, we  derive a generalized likelihood ratio test (GLRT) based onempirical second-order statistics of  the received data. The proposed GLRT detector exploits the  non-stationary correlation structure of the OFDM signal and does not  require any knowledge of the noise power or the signal power. The  GLRT detector is compared to state-of-the-art OFDM signal detectors,  and shown to improve the detection performance with 5 dB SNR in  relevant cases.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2011
Keyword
spectrum sensing, signal detection, OFDM, cyclic prefix, subspace detection, second-order statistics
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-58515 (URN)10.1109/JSAC.2011.110203 (DOI)000286676500003 ()
Note

©2011 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 and Erik G. Larsson, Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance, 2011, IEEE Journal on Selected Areas in Communications, (29), 2, 290-304. http://dx.doi.org/10.1109/JSAC.2011.110203

The previous status of this article was Manuskript.

Available from: 2010-08-12 Created: 2010-08-12 Last updated: 2017-01-13Bibliographically approved
4. Spectrum Sensing of Orthogonal Space-Time Block Coded Signals with Multiple Receive Antennas
Open this publication in new window or tab >>Spectrum Sensing of Orthogonal Space-Time Block Coded Signals with Multiple Receive Antennas
2010 (English)In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Institute of Electrical and Electronics Engineers (IEEE), 2010, 3110-3113 p.Conference paper, Published paper (Other academic)
Abstract [en]

We consider detection of signals encoded with orthogonal space-time block codes (OSTBC), using multiple receive antennas. Such signals contain redundancy and they have a specific structure, that can be exploited for detection. We derive the optimal detector, in the Neyman-Pearson sense, when all parameters are known. We also consider unknown noise variance, signal variance and channel coefficients. We propose a number of GLRT based detectors for the different cases, that exploit the redundancy structure of the OSTBC signal. We also propose an eigenvalue-based detector for the case when all parameters are unknown. The proposed detectors are compared to the energy detector. We show that when only the noise variance is known, there is no gain in exploiting the structure of the OSTBC. However, when the noise variance is unknown there can be a significant gain.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2010
Series
Acoustics Speech and Signal Processing (ICASSP), ISSN 1520-6149 (Print), 2379-190X (online), 1520-6149 (CD)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-51745 (URN)10.1109/ICASSP.2010.5496088 (DOI)000287096003014 ()9781424442959 (ISBN)9781424442966 (ISBN)
Conference
IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2010, 14-19 March, Dallas, Texas, U.S.A.
Note

©2010 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 and Erik G. Larsson, Spectrum Sensing of Orthogonal Space-Time Block Coded Signals with Multiple Receive Antennas, 2010, Proceedings of the 35th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'10).

The previous status of this articel was Manuscript.

Available from: 2009-11-17 Created: 2009-11-17 Last updated: 2017-01-13Bibliographically approved
5. Capacity Considerations for Uncoordinated Communication in Geographical Spectrum Holes
Open this publication in new window or tab >>Capacity Considerations for Uncoordinated Communication in Geographical Spectrum Holes
2009 (English)In: Physical Communication, ISSN 1874-4907, Vol. 2, no 1-2, 3-9 p.Article in journal (Refereed) Published
Abstract [en]

Cognitive radio is a new concept of reusing a licensed spectrum in an unlicensed manner. The motivation for cognitive radio is various measurements of spectrum utilization, that generally show unused resources in frequency, time and space. These "spectrum holes" could be exploited by cognitive radios. Some studies suggest that the spectrum is extremely underutilized, and that these spectrum holes could provide ten times the capacity of all existing wireless devices together. The spectrum could be reused either during time periods where the primary system is not active, or in geographical positions where the primary system is not operating. In this paper, we deal primarily with the concept of geographical reuse, in a frequency-planned primary network. We perform an analysis of the potential for communication in a geographical spectrum hole, and in particular the achievable sum-rate for a secondary network, to some order of magnitude. Simulation results show that a substantial sum-rate could be achieved if the secondary users communicate over small distances. For a small number of secondary links, the sum-rate increases linearly with the number of links. However, the spectrum hole gets saturated quite fast, due to interference caused by the secondary users. A spectrum hole may look large, but it disappears as soon as someone starts using it.

Place, publisher, year, edition, pages
Elsevier, 2009
Keyword
achievable rate, capacity, cognitive radio, spectrum hole
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-21547 (URN)10.1016/j.phycom.2009.03.002 (DOI)
Note
Original Publication: Erik Axell, Erik G. Larsson and Danyo Danev, Capacity Considerations for Uncoordinated Communication in Geographical Spectrum Holes, 2009, Physical Communication, (2), 1-2, 3-9. http://dx.doi.org/10.1016/j.phycom.2009.03.002 Copyright: Elsevier Science B.V., Amsterdam http://www.elsevier.com/ Available from: 2009-10-03 Created: 2009-10-02 Last updated: 2016-08-31Bibliographically approved

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
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  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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