Efficient Cyclostationary Detection Based Spectrum Sensing in Cognitive Radio Networks

Efficient Cyclostationary Detection Based Spectrum Sensing in Cognitive Radio Networks

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2015 by IJETT Journal
Volume-19 Number-4
Year of Publication : 2015
Authors : P. Venkatramana, S. Narayana Reddy
DOI :  10.14445/22315381/IJETT-V19P235

Citation 

P. Venkatramana, S. Narayana Reddy "Efficient Cyclostationary Detection Based Spectrum Sensing in Cognitive Radio Networks", International Journal of Engineering Trends and Technology (IJETT), V19(4), 195-200 Jan 2015. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract

As the customers in wireless communication becoming crowdy and it becomes an important to tackle the spectrum scarcity problem. Most of TV licensed spectrum band, users only utilize their chosen resources partially, thus force the need of cognitive radios (CR) which offers the capable feature of accessing the unused spectrum by dynamic spectrum. In this paper, we are presenting the cyclostationary detection method for estimation and spectral autocorrelation function technique to analyze the spectrum. We used cyclostationary feature detection under modulation scheme to detect the primary users at very low SNR and enhancing cyclostationary feature detection with peak detection algorithm for effective performance. To reduce the noise peaks in the cyclostationary output absolute threshold, standard deviation and filtfilt are the techniques used to get a better efficiency for signal detection.

References

[1] 1Sajjad Ahmed Ghauri, 2Ijaz Mansoor Qureshi, 3Ihtesham Shah and 3Nasir Khan, " Modulation Classification using Cyclostationary Features on Fading Channels, "Research Journal of Applied Sciences, Engineering and Technology 7(24): 5331-5339, 2014.
[2] J.Mitola, ?Cognitive radio: making software radio more personal,? IEEE Personal Communications, vol. 6, no. 4, pp. 13–18, 1999.
[3] Samuel Cheng, 2012, Foundation of Cognitive Radio Systems,
[4] S. Haykin. Cognitive radio: brain-empowered wireless communications. Selected Areas in Communications, IEEE Journal on, 23(2):201{220, 2005.
[5] I. F. Akyildiz, L. Won-Yeol, and K.R. Chowdhury., " Spectrum management in cognitive radio adhoc networks." IEEE Xplore, 3(12):6{12, 2009.
[6] W. A. Gardner, Statistical Spectral Analysis: A Nonprobabilistic Theory, Prentice-Hall, Englewood Cliffs, NJ, USA, 1987.
[7] W. A. Gardner, “Signal interception: a unifying theoretical framework for feature detection,” IEEE Transactions on Communications, vol. 36, no. 8, pp. 897–906, 1988.
[8] FCC, "Spectrum Policy Task Force Report," vol. ET Docket No. 02-155, November 2002.
[9] W. A. Gardner and C. M. Spooner, “Signal interception: performance advantages of cyclic-feature detectors,” IEEE Transactions on Communications, vol. 40, no. 1, pp. 149–159, 1992.
[10] R. S. Roberts, “Computationally efficient algorithms for cyclic spectral analysis,” IEEE Signal Processing Magazine, Apr. 1991.
[11] W. M. Gardner, “Measurement of spectral correlation,” IEEE Trans on Acoust, Speech, and Signal Processing, vol. ASSP-34, no. 5, Oct.1986.
[12] 1 Barathram Ramkumar, Tamal Bose, 2Miloje S. Radenkovic, "Combined Blind Equalization and Automatic Modulation Classification for Cognitive Radios".
[13] Julien Renard, Jonathan Verlant-Chenet, Jean-Michel Dricot, Philippe De Doncker, and Francois Horlin, "Higher-Order Cyclostationarity Detection for Spectrum Sensing".EURASIP Journal onWireless Communications and Networking Volume 2010.
[14] 1niyati Sohni, 2anand Mane, " Spectrum Sensing by Cyclostationary Detector," International Journal of Industrial Electronics and Electrical Engineering, ISSN: 2347-6982 Volume-2, Issue-7, July-2014.
[15] Kyouwoong Kim, I. A. Akbar, K. K. Bae, Jung-sun Urn, C. M. Spooner, 1. H. Reed, "Cyclostationary approaches to signal detection and classification in cognitive radio", 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, pp.212-215, (2007).
[16] W. Gardner, "The spectral correlation theory of cyclostationary time-series", Signal Processing, Vol. 11(1) pp.13-36, (1986).

Keywords
Cyclostationary, Correlation Function, autocorrelation functions, cyclic frequency, Spectral Coherence.