CFP last date
20 January 2025
Reseach Article

Comparison of Energy Detection Methods in Cognitive Radio Networks

by H.srikanth.kamath, Simon Larsson
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 103 - Number 4
Year of Publication: 2014
Authors: H.srikanth.kamath, Simon Larsson
10.5120/18062-8995

H.srikanth.kamath, Simon Larsson . Comparison of Energy Detection Methods in Cognitive Radio Networks. International Journal of Computer Applications. 103, 4 ( October 2014), 19-23. DOI=10.5120/18062-8995

@article{ 10.5120/18062-8995,
author = { H.srikanth.kamath, Simon Larsson },
title = { Comparison of Energy Detection Methods in Cognitive Radio Networks },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 103 },
number = { 4 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 19-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume103/number4/18062-8995/ },
doi = { 10.5120/18062-8995 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:33:41.036590+05:30
%A H.srikanth.kamath
%A Simon Larsson
%T Comparison of Energy Detection Methods in Cognitive Radio Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 103
%N 4
%P 19-23
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cognitive Radio is an emerging new paradigm in wireless communications. Its goal is to make frequency use more efficient by using temporarily unoccupied frequency bands. Therefore frequency bands have to be measured in order to decide about the occupation of the band. One of the used techniques is energy detection. In this paper different energy detection models were compared. The evaluation was performed using a simulator for an OFDM-modulation based wireless communication network.

References
  1. K. J. R. Liu and B. Wang. "Cognitive Radio Networking and Security". Cambridge : Cambridge University Press, 2011. 978-0-521-76231-1.
  2. L. Khalid and A. Anpalagan. "Emerging cognitive radio technology: Principles, challenges and opportunities". p. 358-366, Toronto : Computers and Electrical Engineering, 2010, Vol. 36.
  3. I. F. Akyildiz, W. -Y. Lee, M. C. Vuran and S. Mohanty. "NeXt gereration/dynamic spectrum access/cognitive radio wireless networks: A survey. " 2006, Computer Networks 50, pp. 2127-2159.
  4. C. Raman, J. Kalyanam, I. Seskar and N. Mandayam. "Distributed Spatio-Temporal Spectrum Sensing: An Experimental Study. " Pacific Grove, CA. IEEE, 2007. 978-1-4244-2110-7.
  5. F. F. Digham, M. -S. Alouini and M. K. Simon. "On the Energy Detection of Unknown Signals over Fading Channels. " IEEE, 2003, Vols. Communications, 2003. ICC '03. IEEE International Conference on (Volume: 5). 0-7803-7802-4.
  6. H. -S. Chen, W. Gao and D. G. Daut. "Spectrum Sensing Using Cyclostationary Properties and Application to IEEE 802. 22 WRAN. " Washington, DC. IEEE, 2007. 978-1-4244-1043-9.
  7. M. P. Wylie-Green. "Dynamic Spectrum Sensing by Multiband OFDM Radio for Interference Mitigation". Baltimore : IEEE, 2005. 1-4244-0013-9.
  8. S. J. Shellhammer. "Spectrum sensing in IEEE 802. 22". San Diego : Qualcomm Inc, 2008.
  9. T. Yücek and H. Arslan. "A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications". IEEE Communications Surveys & Tutorials, 2009, Vol. 11.
  10. IEEE Computer Society. "Part 22: Cognitive Wireless RAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: Policies and Procedures for Operation in the TV Bands". IEEE Standard for Information Technology. New York : IEEE, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Cognitive-radio energy-detection chi-squared OFDM(A) cyclic-prefix simulator