CFP last date
20 January 2025
Reseach Article

Dynamic Threshold Energy Detection Technique for Cognitive Radio

by Neelu, Arun Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 148 - Number 5
Year of Publication: 2016
Authors: Neelu, Arun Kumar
10.5120/ijca2016911127

Neelu, Arun Kumar . Dynamic Threshold Energy Detection Technique for Cognitive Radio. International Journal of Computer Applications. 148, 5 ( Aug 2016), 31-35. DOI=10.5120/ijca2016911127

@article{ 10.5120/ijca2016911127,
author = { Neelu, Arun Kumar },
title = { Dynamic Threshold Energy Detection Technique for Cognitive Radio },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2016 },
volume = { 148 },
number = { 5 },
month = { Aug },
year = { 2016 },
issn = { 0975-8887 },
pages = { 31-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume148/number5/25756-2016911127/ },
doi = { 10.5120/ijca2016911127 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:53:26.875259+05:30
%A Neelu
%A Arun Kumar
%T Dynamic Threshold Energy Detection Technique for Cognitive Radio
%J International Journal of Computer Applications
%@ 0975-8887
%V 148
%N 5
%P 31-35
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Spectrum sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. The dynamic threshold energy detection is proposed in this paper for the spectrum sensing of Cognitive Radio. The proposed dynamic energy scheme depends on the current state of the primary user. Depending on this, dynamic thresholds are evaluated considering the effect of noise uncertainty. The thresholds evaluated are used to increase the value of Pd and decrease the value of

References
  1. S.Haykin, “Cognitive radio: brain empowered wireless communications,” IEEE Journal on Selected Areas in Communications, vol.23, pp. 201-220, Feb. 2005.
  2. Mitola III, Joseph, and Gerald Q. Maguire Jr. "Cognitive radio: making software radios more personal. " IEEE Personal Communications., 1999,6 (4),13-18.
  3. T. Yucek and H, Arslan, “A survey of spectrum sensing algorithms for cognitive radio applications,” IEEE Communications Surveys and Tutorials, vol. 11, pp. 116-130, Jan. 2009.
  4. G. Yu, C. and W. Xi, “A novel energy detection scheme based on dynamic threshold in Cognitive radio systems,” Journal of Computational Information Systems, vol. 8, pp. 2245-2252, Mar. 2012.
  5. X. Hue, X. Xie, T.Song and W. Lei, “An algorithm for energy detection based on noise variance estimation under Noise Uncertainty,” IEEE International Conference on Communication and Technology, pp. 1-5, Nov, 2012
  6. Y. Zeng and Y.-C. Liang, “Maximum-minimum eigenvalue detection for cognitive radio,” in Proc. IEEE International Symposium on Personal, Indoor and Mobile Radio Communication, (PIMRC’07), pp. 1–5, 2007.
  7. F. Digham, M. Alouini, and M. Simon, “On the energy detection of unknown signals over fading channels,” IEEE Transactions on Communications, vol. 55, pp. 21–24, Jan. 2007.
  8. J. Song, Z. Feng, P. Zhang, and Z. Liu, “Spectrum sensing in cognitive radios based on enhanced energy detector,” IET Communications, vol. 6, pp. 805–809, May 2012.
  9. Y. Zeng, Y.-C. Liang, A. Hoang, and C. Peh, “Reliability of spectrum sensing under noise and interference uncertainty,” in Proc. IEEE International Conference on Communications Workshops, (ICC’09), pp. 1–5, 2009.
  10. Akyildiz, I.F., Lee, W.-Y., Vuran, M.C., Mohanty, S.: ‘A survey on spectrum management in cognitive radio networks’, IEEE Commun. Mag., 46, (4), pp. 40–48, 2008.
  11. Yu¨cek, T., Arslan, H.: ‘A survey of spectrum sensing algorithms for cognitive radio applications’, IEEE Commun. Surv. Tutor (First Quarter), 11, (1), pp. 116–130, 2009.
  12. Ariananda, D.D., Lakshmanan, M.K., Nikookar, H.: ‘A survey on spectrum sensing techniques for cognitive radio’. Proc. Second Int. Workshop on Cognitive Radio and Advanced Spectrum Management (CogART 2009), pp. 74–79, May 2009.
  13. Zeng, Y., Liang, Y.-C.: ‘Spectrum-sensing algorithms for cognitive radio based on statistical covariances’, IEEE Trans. Veh. Technol, 58, (4), pp. 1804–1815, 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Spectrum sensing Energy detection Probability of detection (Pd) Probability of false alarm (