Towards Robust Spectrum Sensing in Cognitive Radio Networks

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School of Electrical Engineering | Doctoral thesis (article-based) | Defence date: 2013-11-01
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Date

2013

Department

Tietoliikenne- ja tietoverkkotekniikan laitos
Department of Communications and Networking

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Mcode

Degree programme

Language

en

Pages

79 + app. 75

Series

Aalto University publication series DOCTORAL DISSERTATIONS, 145/2013

Abstract

This thesis focuses on multi-antenna assisted energy based spectrum sensing. The studies leading to this thesis have been motivated by some practical issues with energy based detection. These include the noise uncertainty problem at the secondary receiver, the presence of multiple active primary users in cognitive cellular networks, the existence of unknown noise correlations and detection in the low signal-to-noise ratio regime. In this thesis, the aim is to incorporating these practical concerns into the design of spectrum sensing algorithms. To this end, we propose the use of various detectors that are suitable for different scenarios. We consider detectors derived from decision-theoretical criteriors as well as heuristic detectors. We analyze the performance of the proposed detectors by deriving their false alarm probability, detection probability and receiver operating characteristic. The main contribution of this thesis consists of the derived closed-form performance metrics. These results are obtained by utilizing tools from multivariate analysis, moment based approximations, Mellin transforms, and random matrix theory. Numerical results show that the proposed detectors have indeed resolved the concerns raised by the above practical issues. Some detectors could meet the needs of one of the practical challenges, while others are shown to be robust when several practical issues are taken into account. The use of detectors constructed with decision-theoretical considerations over the heuristically proposed ones is justified as well.

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Supervising professor

Tirkkonen, Olav, Prof., Aalto University, Department of Communications and Networking, Finland

Thesis advisor

Tirkkonen, Olav, Prof., Aalto University, Department of Communications and Networking, Finland

Keywords

cognitive radio, multivariate analysis, robust statistics, spectrum sensing

Other note

Parts

  • [Publication 1]: Lu Wei and Olav Tirkkonen. Cooperative spectrum sensing of OFDM signals using largest eigenvalue distributions. In Proceedings of IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 2295-2299, Sept. 2009.
  • [Publication 2]: Lu Wei and Olav Tirkkonen. Analysis of scaled largest eigenvalue based detection for spectrum sensing. In Proceedings of IEEE International Conference on Communications, pp. 1-5, June 2011.
  • [Publication 3]: Lu Wei, Olav Tirkkonen, Prathapasinghe Dharmawansa, and Matthew McKay. On the exact distribution of the scaled largest eigenvalue. In Proceedings of IEEE International Conference on Communications, pp. 2422-2426, June 2012.
  • [Publication 4]: Lu Wei and Olav Tirkkonen. Spectrum sensing in the presence of multiple primary users. IEEE Transactions on Communications, vol. 60, no. 5, pp. 1268-1277, May 2012.
  • [Publication 5]: Lu Wei, Prathapasinghe Dharmawansa, and Olav Tirkkonen. Multiple primary user spectrum sensing in the low SNR regime. IEEE Transactions on Communications, vol. 61, no. 5, pp. 1720-1731, May 2013.
  • [Publication 6]: Lu Wei and Olav Tirkkonen. Approximate condition number distribution of complex non-central correlated Wishart matrices. In Proceedings of IEEE International Conference on Communications, pp. 1-5, June 2011.
  • [Publication 7]: Lu Wei, Matthew McKay, and Olav Tirkkonen. Exact Demmel condition number distribution of complex Wishart matrices via the Mellin transform. IEEE Communications Letters, vol. 15, no. 2, pp. 175-177, Feb. 2011.
  • [Publication 8]: Lu Wei and Olav Tirkkonen. Multiple primary user spectrum sensing for unknown noise statistics. In Proceedings of IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Sept. 2013.

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https://urn.fi/URN:ISBN:978-952-60-5335-6

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[diss] Sähkötekniikan korkeakoulu / ELEC