Skip to main content

Advertisement

Log in

Energy Detection Approach for Spectrum Sensing in Cognitive Radio Systems with the Use of Random Sampling

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In radiomobile contexte, radio frequency spectrum is a ressource that needs to be used with appropriate efficiency. This can be achieved by the mean of spectrum sensing operation. This function consists to analyze the occupancy of the radio frequency spectrum in order to detect which bands are unused. This concept is largely appreciated in cognitive radio where more flexibility is required to adapt to the communication environment. Different techniques are presented in the literature. In this paper, we are interested by the application of the energy detector method for spectrum sensing. This application is performed in cognitive radio systems with the use of random sampling. The performance of this approach is evaluated in term of its receiver operating characteristic curve and compared to the uniform sampling case.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Mitola-III, Jr, J. (2000). Cognitive radio: An integrated agent architecture for software defined radio. Ph.D. dissertation, Royal Institute of Technology, Sweden.

  2. Yucek, T., & Arsalan, H. (2009). A survey of spectrum sensing algorithms for cognitive radio applications. Communications Surveys and Tutorials, 11, 116–130.

    Article  Google Scholar 

  3. Urkowitz, H. (1967). Energy detection of unknown deterministic signals. Proceeding of IEEE, 55(4), 523–531.

    Article  Google Scholar 

  4. Cabric, D., Tkachenko, A., & Brodersen, R. W. (2006). Experimental study of spectrum sensing based on energy detection and network cooperation. In ACM 1st international workshop on technology and policy for accessing spectrum (TAPAS).

  5. Cabric, D., Mishra, S. M., & Brodersen, R. W. (2004). Implementation Issues in Spectrum Sensing for Cognitive Radios. In Asilomar conference on signal, systems and computers.

  6. Wojtiuk, J. J., & Martin, R. J. (2001). Random sampling enables flexible design for multiband carrier signals. IEEE Transactions on Signal Processing, 49(10), 2438–2440.

    Article  Google Scholar 

  7. Bilinskis, I., & Mikelsons, A. (1992). Randomized Signal Processing. Cambridge: Prentice Hall.

    MATH  Google Scholar 

  8. Wojtiuk, J. J. (2000). Randomized sampling for radio design. Ph.D. Thesis, University of South Australia, School of Electrical and Information Engineering, Australia.

  9. Shapiro, H. S., & Silverman, R. A. (1960). Alias-free sampling of random noise. SIAM Jouanal of Applied Mathematics, 8, 225–236.

    Article  MathSciNet  MATH  Google Scholar 

  10. Beutler, F. J. (1966). Error-free recovery of signals from irregularly spaced samples. SIAM Review, 8, 328–335.

    Article  MathSciNet  MATH  Google Scholar 

  11. Digham, F. F., Alouini, M.-S., & Simon, M. K. (2007). On the energy detection of unknown signals over fading channels. IEEE Transactions on Communications, 55(1), 21–24.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hayat Semlali.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Semlali, H., Boumaaz, N., Soulmani, A. et al. Energy Detection Approach for Spectrum Sensing in Cognitive Radio Systems with the Use of Random Sampling. Wireless Pers Commun 79, 1053–1061 (2014). https://doi.org/10.1007/s11277-014-1917-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-014-1917-6

Keywords

Navigation