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http://dx.doi.org/10.4218/etrij.14.0113.0758

Sensing of OFDM Signals in Cognitive Radio Systems with Time Domain Cross-Correlation  

Xu, Weiyang (College of Communication Engineering, Chongqing University)
Publication Information
ETRI Journal / v.36, no.4, 2014 , pp. 545-553 More about this Journal
Abstract
This paper proposes an algorithm to sense orthogonal frequency-division multiplexing (OFDM) signals in cognitive radio (CR) systems. The basic idea behind this study is when a primary user is occupying a wireless channel, the covariance matrix is non-diagonal because of the time domain cross-correlation of the cyclic prefix (CP). In light of this property, a new decision metric that measures the power of the data found on two minor diagonals in the covariance matrix related to the CP is introduced. The impact of synchronization errors on the signal detection is analyzed. Besides this, a likelihood-ratio test is proposed according to the Neyman-Pearson criterion after deriving probability distribution functions of the decision metric under hypotheses of signal presence and absence. A threshold, subject to the requirement of probability of false alarm, is derived; also the probabilities of detection and false alarm are computed accordingly. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed algorithm.
Keywords
OFDM; cyclic prefix; covariance matrix; signal detection; Neyman-Pearson criterion;
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1 X.B. Hu, Y.M. Huang, and Z.L. Hong, "Residual Synchronization Error Elimination in OFDM Baseband Receivers," ETRI J., vol. 29, no. 5, Oct. 2007, pp. 596-606.   DOI
2 S. Haykin, "Cognitive Radio: Brain-Empowered Wireless Communications," IEEE J. Sel. Areas Commun., vol. 23, no. 2, Feb. 2005, pp. 201-220.   DOI   ScienceOn
3 T. Yucek and H. Arslan, "A Survey Of Spectrum Sensing Algorithms for Cognitive Radio Applications," IEEE Commun. Surveys Tutorials, vol. 11, no. 1, 2009, pp. 116-130.   DOI   ScienceOn
4 S. Bokharaiee, H.H. Nguyen, and E. Shwedyk, "Blind Spectrum Sensing for OFDM-Based Cognitive Radio Systems," IEEE Trans. Veh. Technol., vol. 60, no. 3, Mar. 2011, pp. 858-871.   DOI
5 R. Tandra and A. Sahai, "Fundamental Limits on Detection in Low SNR under Noise Uncertainty," IEEE Int. Conf. Wireless Netw., Commun. Mobile Comput., Maui, HI, USA, vol. 1, June 2005, pp. 464-469.
6 T. Roman, S. Visuri, and V. Koivunen, "Blind Frequency Synchronization in OFDM via Diagonality Criterion," IEEE Trans. Signal Process., vol. 54, no. 8, Aug. 2006, pp. 3125-3135.   DOI   ScienceOn
7 Z. Lei and F. Chin "Sensing OFDM Systems under Frequency- Selective Fading Channels," IEEE Trans. Veh. Technol., vol. 59, no. 4, May 2010, pp. 1960-1968.   DOI
8 H.S. Chen, W. Gao, and D.G. Daut, "Spectrum Sensing for OFDM Systems Employing Pilot Tones," IEEE Trans. Wireless Commun., vol. 8, no. 12, Dec. 2009, pp. 5862-5870.   DOI
9 A. Zahedi-Ghasabeh, A. Tarighat, and B. Daneshrad, "Spectrum Sensing of OFDM Waveforms Using Embedded Pilots Subcarriers," IEEE Int. Conf. Commun., Cape Town, South Africa, May 23-27, 2010, pp. 1-6.
10 J.J. van de Beek, M. Sandell, and P.O. Borjesson, "ML Estimation of Time and Frequency Offset in OFDM Systems," IEEE Trans. Signal Process., vol. 45, no. 7, July 1997, pp. 1800-1805.   DOI   ScienceOn
11 T. Lv, H. Li, and J. Chen, "Joint Estimation of Symbol Timing and Carrier Frequency Offset of OFDM Signals over Fast Time- Varying Multipath Channels," IEEE Trans. Signal Process., vol. 53, no. 12, Dec. 2005, pp. 4526-4535.   DOI
12 S.M. Kay, Fundamentals of Statistical Signal Processing, Detection Theory, Upper Saddle River, NJ: Prentice Hall, 1993.
13 J.A. Lopez-Salcedo, "Simple Closed-Form Approximation to Ricean Sum Distributions," IEEE Signal Process. Lett., vol. 16, no. 3, Mar. 2009, pp. 153-155.   DOI