IJTEEE
International Journal of Technology Enhancements and Emerging Engineering Research (ISSN 2347-4289)
PREVIOUS PUBLICATIONS



IJTEEE >> Volume 2 - Issue 8, August 2014 Edition



International Journal of Technology Enhancements and Emerging Engineering Research  
International Journal of Technology Enhancements and Emerging Engineering Research

Website: http://www.ijteee.org

ISSN 2347-4289



Study Of Spectrum Sensing Techniques For OFDM Based Cognitive Radio

[Full Text]

 

AUTHOR(S)

Monika Tripathi

 

KEYWORDS

Keywords: Cognative Radio, OFDM, Spectrum Sensing, Energy Detection, Matched Filter, Cyclostationary Feature Detection.

 

ABSTRACT

Abstract: Nowadays OFDM (Orthogonal Frequency Division Multiplexing) techniques are adopted by many existing or progressing wireless communication standards.OFDM’s sensing and spectrum shaping capabilities together with its flexibility and adaptivity make it the best transmission technology for CR system. Spectrum sensing helps to detect the spectrum holes (unutilized bands of the spectrum) providing high spectral resolution capability.Thus, a robust spectrum sensing algorithm for OFDM modulated signals is highly decide to implement CR when the primary signal uses OFDM modulation. Motivated by this demand,a Time-Domain Symbol Cross-correlation based spectrum sensing algorithm (TDSC method) is presented in this paper.The algorithm makes use of the property that the mean of the TDSC of two OFDM symbols is not zero if they have embedded the same frequency-domain pilot tones. We propse a new decision statistic for the signal detection based on the special feature –Cyclic Prefix embedded in OFDM signal. Further, in this paper we used to control the Transmit Power for cognitive radio.Different spectrum sensing techniques for OFDM based cognitive radio are discussed in this paper.

 

REFERENCES

[1]. J.Mitola, “Cognitive radio:making software radio more personal,” IEEE Personal Communications, vol. 6, no. 4, pp. 13–18, 1999.

[2]. Federal Communications Commission, "Notice of Proposed Rulemaking: Unlicensed operation in the TV broadcast", ET Docket no. 04-186 (FCC 04- 113) May 2004.

[3]. FCC, “Notice of proposed rulemaking and order,” ET, Docket 03-222, December 2003.

[4]. H.Urkowitz, “Energy detection of unknown deterministic signals." Proc.IEEE, vol.55, pp.523-531, apr.1967.

[5]. A.Sahai, N. Hoven, R. Tandra, “Some Fundamental Limits on Cognitive Radio,” Proc. of Allerton Conference, Monticello, 2004

[6]. W.A.Gardner, “Signal Interception: A Unifying Theoretical Framework for Feature Detection,” IEEE Trans. on Communications, vol. 36,1988.

[7]. A.Fehske, J.D. Gaeddert, J.H. Reed, “A new approach to signal classification using spectral correlation and neural networks,” Proc. IEEE DySPAN 2005, pp. 144–150, 2005.

[8]. S. M. Kay, “Fundamentals of statistical signal processing: Detection theory,” Printice Hall PTR, vol. 2, 1998

[9]. HuseyinArslan, "Cognitive Radio, Software Defined Radio andAdaptive Wireless Systems" 1" Edition, Springer Press 2007, and ISBN:978-1-4020-5541-6.

[10]. M. Schwartz, Mobile Wireless Communications. Cambridge University Press, 2005.

[11]. Omer Ali,, “Analysis of OFDM parameters using Cyclostationary Spectrum Sensing in Cognitive Radio,” 2011 IEEE.

[12]. R. Suresh Babu,“Review of Energy Detection for Spectrum sensing in various channels and its performance for cognitive radio applications,”American Journal of Engineering and Applied Sciences, 2012, 5 (2), 151-156.