Multiple antenna spectrum sensing using statistical a-priori information in cognitive radios

Multiple antenna spectrum sensing using statistical a-priori information in cognitive radios

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Signal Processing — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

In this study, the authors consider the problem of multiple antenna spectrum sensing by exploiting the prior information about unknown parameters. Under assumption that additional statistical side information is available about unknown parameters, a novel framework and some detectors are proposed, which are optimal for finite number of received samples. locally most powerful, average likelihood ratio and the novel generalised likelihood ratio detectors are calculated for the different practical conditions in wireless channels. In addition, the analytical performance evaluation for proposed detectors is provided whenever possible. The simulation and analytical results show that the a-priori information can be used for better spectrum sensing using finite number of samples.


    1. 1)
      • 1. Taherpour, A., Nasiri-Kenari, M., Gazor, S.: ‘Multiple antenna spectrum sensing in cognitive radios’, IEEE Trans. Wirel. Commun., 2010, 9, (2), pp. 814823.
    2. 2)
      • 2. Tandra, R., Sahai, A.: ‘SNR walls for signal detection’, IEEE J. Sel. Top. Signal Process., 2008, 2, (1), pp. 417.
    3. 3)
      • 3. Sutton, P., Nolan, K., Doyle, L.: ‘Cyclostationary signatures in practical cognitive radio applications’, IEEE J. Sel. Areas Commun., 2008, 26, (1), pp. 1324.
    4. 4)
      • 4. Tang, H.: ‘Some physical layer issues of wide-band cognitive radio systems’. First IEEE Int. Symp. on New Frontiers in Dynamic Spectrum Access Networks, 2005 (DySPAN 2005), 2005, pp. 151159.
    5. 5)
      • 5. Yucek, T., Arslan, H.: ‘A survey of spectrum sensing algorithms for cognitive radio applications’, IEEE Commun. Surv. Tutor., 2009, 11, (1), pp. 116130.
    6. 6)
      • 6. Lim, T., Zhang, R., Liang, Y., Zeng, Y.: ‘GLRT-based spectrum sensing for cognitive radio’. IEEE Global Telecommunications Conf., 2008 (IEEE GLOBECOM 2008), 2008, pp. 15.
    7. 7)
      • 7. Wang, P., Fang, J., Han, N., Li, H.: ‘Multiantenna-assisted spectrum sensing for cognitive radio’, IEEE Trans. Veh. Technol., 2010, 59, (4), pp. 17911800.
    8. 8)
      • 8. Poor, H.: ‘An introduction to signal detection and estimation’, 1994.
    9. 9)
      • 9. Moustakides, G.: ‘Finite sample size optimality of GLR tests’. arXiv:0903.3795, 2009.
    10. 10)
      • 10. ATSC: ‘Recommended Practice Guideline Document entitled: ATSC recommended practice : receiver performance guidelines’, 74.
    11. 11)
      • 11. Nevat, I., Peters, G., Collings, I., Yuan, J.: ‘Cooperative spectrum sensing with partial csi’. arXiv:1104.2355, 2011.
    12. 12)
      • 12. Strang, G.: ‘Introduction to linear algebra’ (Wellesley Cambridge Press, 2003).
    13. 13)
      • 13. Tadaion, A., Derakhtian, M., Gazor, S., Nayebi, M., Aref, M.: ‘Signal activity detection of phase-shift keying signals’, IEEE Trans. Commun., 2006, 54, (8), pp. 14391445.
    14. 14)
      • 14. Taherpour, A., Gazor, S., Nasiri-Kenari, M.: ‘Wideband spectrum sensing in unknown white gaussian noise’, IET Commun., 2008, 2, (6), pp. 763771.
    15. 15)
      • 15. Font-Segura, J., Wang, X.: ‘GLRT-based spectrum sensing for cognitive radio with prior information’, IEEE Trans. Commun., 2010, 58, (7), pp. 21372146.
    16. 16)
      • 16. Ghogho, M., Cardenas-Juarez, M., Swami, A., Whitworth, T.: ‘Locally optimum detection for spectrum sensing in cognitive radio’. Fourth Int. Conf. on Cognitive Radio Oriented Wireless Networks and Communications, 2009 (CROWNCOM'09), 2009, pp. 16.
    17. 17)
      • 17. Box, G., Tiao, G.: ‘Bayesian inference in statistical analysis’ (Wiley Online Library, 1973).
    18. 18)
      • 18. Hjørungnes, A., Gesbert, D.: ‘Introduction to complex-valued matrix differentiation’, IEEE Trans. Signal Process., 2007, 55, pp. 27402746.
    19. 19)
      • 19. Feiveson, A.H., Delaney, C.: ‘The distribution and properties of a weighted sum of chi squares’. NASA Technical Note, 1968.

Related content

This is a required field
Please enter a valid email address