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Hybrid Spectrum Sensing Algorithm for Cognitive Radio Network

by Syed Fahad Shirazi, Syed Hamad Shirazi, Syed Muslim Shah, Muhammad Khalil Shahid,
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 45 - Number 17
Year of Publication: 2012
Authors: Syed Fahad Shirazi, Syed Hamad Shirazi, Syed Muslim Shah, Muhammad Khalil Shahid,
10.5120/7003-9557

Syed Fahad Shirazi, Syed Hamad Shirazi, Syed Muslim Shah, Muhammad Khalil Shahid, . Hybrid Spectrum Sensing Algorithm for Cognitive Radio Network. International Journal of Computer Applications. 45, 17 ( May 2012), 25-30. DOI=10.5120/7003-9557

@article{ 10.5120/7003-9557,
author = { Syed Fahad Shirazi, Syed Hamad Shirazi, Syed Muslim Shah, Muhammad Khalil Shahid, },
title = { Hybrid Spectrum Sensing Algorithm for Cognitive Radio Network },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 45 },
number = { 17 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 25-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume45/number17/7003-9557/ },
doi = { 10.5120/7003-9557 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:37:52.190624+05:30
%A Syed Fahad Shirazi
%A Syed Hamad Shirazi
%A Syed Muslim Shah
%A Muhammad Khalil Shahid,
%T Hybrid Spectrum Sensing Algorithm for Cognitive Radio Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 17
%P 25-30
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Spectrum sensing plays a very provocative role in cognitive radio network. In order to utilize spectrum more efficiently and to exploit the primary user, spectrum sensing is accomplished. We proposed a new hybrid algorithm for detection of primary user in cognitive radio network. The theoretical analysis and simulation is also presented in this paper. This research work includes an analogy with Energy Based Detection and Cyclostationary Feature Detection. Our proposed algorithm is a flexible algorithm, the Cyclostationary feature algorithm act as feature extractor when primary user is present and function as detector when primary user is absent. The results show that it is optimum spectrum sensing algorithm under different SNR values. It has removed the shortcomings faced by both sensing algorithms i. e. Energy Based Detection and Cyclostationary Feature Detection.

References
  1. I. F Akyildiz, W. -Y. Lee, M. C. Vuran, S. Mohanty, NeXt generation/ dynamic spectrum access/cognitive radio wireless networks: a survey, computer networks 50 (13) (2006) 2127-2159.
  2. I. F Akyildiz, W. Y Lee , K. R Chowdhury, CRAHNs: cognitive radio ad hoc networks, Ad Hoc Networks 7 (5) 2009 810-823
  3. Federal Communications Commission, " Spectrum Policy Task Force ," Rep. ET Docket no. 02-135, Nov. 2002.
  4. Mitola III J, Maguire Jr G. Cognitive radio: making software radios more personal. Personal Communications,IEEE [see also IEEE Wireless Communications] 1999; 6(4):13–18. DOI: 10. 1109/98. 788210.
  5. Qusay H. Preface. Mahmoud (University of Guelph C (ed. )), COGNITIVE NETWORKS: Towards Self-Aware Networks. Wiley: New York, 2007; 24.
  6. F. F. Digham, N. -S. Alouini, N. K. Simon, On the energy detection of unknown signals over fading channels, IEEE Transactions on Communications 55 (1) (2007) 21–24. .
  7. H. Urkowitz, Energy detection of unknown deterministic signals, Proceedings of the IEEE 55.
  8. Federal Communications Commission, "Notice of Proposed Rulemaking (FCC 04-113): Unlicensed Operation in the TV Broadcast Bands," ET Docket No. 04-186, 25 May 2004
  9. D. Cabric and R. W. Brodersen, "Physical layer design issues unique to cognitive radio systems," in Proc. IEEE Int. Symposium on Personal, Indoor and mobile Radio Commun. , vol. 2, Berlin, Germany, Sept. 2005, pp. 759–763.
  10. U. Gardner, WA, "Exploitation of spectral redundancy in cyclostationary signals," IEEE Signal Processing Mag. , vol. 8, no. 2, pp. 14–36, 1991.
  11. ET Docket No. 03-222 Notice of proposed rulemaking and order, December 2003.
  12. Cognitive radio Research and Implementation Challenges A. Menouni Hayar1, R. Knopp1 and R. Pacalet2 1Mobile Communications Laboratory Institute, Eur´ecom, Sophia Antipolis, France 2SOC Laboratory, ENST Sophia Antipolis
  13. Lars Berlemann, George Dimitrakopoulos, Klaus moessner and Jim Hoffmeyer, ''Cognitive Radio and Management of Spectrum and Radio Resources in Reconfigurable Networks''.
  14. T. Yucek, H. Arslan, A survey of spectrum sensing algorithms for cognitive radio applications, Communications Surveys Tutorials, IEEE 11 (1) (2009) 116–130
  15. J. Lehtom¨aki, M. Juntti, H. Saarnisaari, and S. Koivu, "Threshold setting strategies for a quantized total power radiometer," IEEE Signal Processing Lett. , vol. 12, no. 11, pp. 796–799, Nov. 2005.
  16. Securing cognitive radio networks INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS Int. J. Commun. Syst. 2010; 23:633–652 Published online 10 February 2010 in Wiley InterScience (www. interscience. wiley. com). DOI: 10. 1002/dac. 1102.
  17. I. F Akyildiz, W. Y Lee, Brandon F. Lo, Ravikumar Balakrishanan, Physical Communication 4 (20011) 40-62.
  18. A. Sahai, N. Hoven, and R. Tandra, "Some fundamental limits on cognitive radio," in Proc. Allerton Conf. on Commun. , Control, and Computing, Nonticello, Illinois, Oct. 2004.
  19. N. P. Olivieri, G. Barnett, A. Lackpour, and A. Davis, "A scalable dynamic spectrum allocation system with interference Nitigation for teaNs of spectrally agile software defined radios," in Proc. IEEE Int. Symposium on New Frontiers in Dynamic Spectrum Access Networks, Baltimore, maryland, USA, Nov. 2005, pp. 170–179.
  20. F. Weidling, D. Datla, V. Petty, P. Krishnan, and G. Ninden, "A framework for RF spectrum measurements and analysis," in Proc. IEEE Int. Symposium on New Frontiers in Dynamic Spectrum Access Networks, vol. 1, Baltimore, Maryland, USA, Nov. 2005, pp. 573–576.
  21. R. Tandra and A. Sahai, "Fundamental limits on detection in low SNR under noise uncertainty," in Proc. IEEE Int. Conf. Wireless Networks, Commun. and mobile Computing, vol. 1, Naui, HI, June 2005, pp. 464–469.
  22. A. Takachenko, D. Cabric and R. W Brodersen, " Cyclostationary feature detector experiments using reconfigurable BEE2," in Proc. IEEE Int. Symposium on New Frontiers in Dynamic Spectrum Access Networks, Dublin, Ireland, Apr. 2007, pp. 216-219.
  23. G. Ganesan and Y. Li, "Agility improvement through cooperative diversity in cognitive radio," in Proc. IEEE Global Telecom. Conf. (Globecom), vol. 5, St. Louis, Nissouri, USA, Nov. /Dec. 2005, pp. 2505–2509.
  24. S. Mishra, A. Sahai, R. Brodersen, Cooperative sensing among cognitive radios, in: Proc. of IEEE ICC 2006, vol. 4, 2006, pp. 1658–1663.
  25. A. Ghasemi, E. Sousa, Collaborative spectrum sensing for opportunistic access in fading environments, in: Proc. of IEEE DySPAN 2005, 2005, pp. 131–136.
Index Terms

Computer Science
Information Sciences

Keywords

Power spectral density cyclic correlation function mean square spectrum hybrid spectrum sensing

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