The Library

Improved energy detector for random signals in Gaussian noise

Tools

Chen, Yunfei. (2010) Improved energy detector for random signals in Gaussian noise. IEEE Transactions on Wireless Communications, Vol.9 (No.2). pp. 558-563. ISSN 1536-1276

PDF
WRAP_Chen_Improved_Energy_detector.pdf - Draft Version - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (471Kb)

Official URL: http://dx.doi.org/10.1109/TWC.2010.02.090622

Abstract

New and improved energy detector for random signals in Gaussian noise is proposed by replacing the squaring operation of the signal amplitude in the conventional energy detector with an arbitrary positive power operation. Numerical results show that the best power operation depends on the probability of false alarm, the probability of detection, the average signal-to-noise ratio or the sample size. By choosing the optimum power operation according to different system settings, new energy detectors with better detection performances can be derived. These results give useful guidance on how to improve the performances of current wireless systems using the energy detector. It also confirms that the conventional energy detector based on the generalized likelihood ratio test using the generalized likelihood function is not optimum in terms of the detection performance.

Item Type:	Journal Article
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Science > Engineering
Library of Congress Subject Headings (LCSH):	Signal processing, Detectors, Random noise theory
Journal or Publication Title:	IEEE Transactions on Wireless Communications
Publisher:	IEEE
ISSN:	1536-1276
Date:	February 2010
Volume:	Vol.9
Number:	No.2
Number of Pages:	6
Page Range:	pp. 558-563
Identification Number:	10.1109/TWC.2010.02.090622
Status:	Peer Reviewed
Access rights to Published version:	Open Access
References:	[1] H. Urkowitz, “Energy detection of unknown deterministic signals,” Proc. IEEE, vol. 55, pp. 523-531, Apr. 1967. [2] D. Cassioli, M. Z. Win, F. Vatalaro, and A. F. Molisch, “Low complexity Rake receivers in ultra-wideband channels,” IEEE Trans. Wireless Commun., vol. 6, pp. 1265-1275, Apr. 2007. [3] M. Z. Win and R. A. Scholtz, “Impulse radio: how it works,” IEEE Commun. Lett., vol. 2, pp. 36-38, Feb. 1998. [4] M. Z. Win and R. A. Scholtz, “Ultrawide bandwidth time-hopping spread-spectrum impulse radio for wireless multiple-access communications,” IEEE Trans. Commun., vol. 48, pp. 679-691, Apr. 2000. [5] T. S. Quek and M. Z. Win, “Analysis of UWB transmitted-reference communication systems in dense multipath channels,” IEEE J. Sel. Areas Commun., vol. 23, pp. 1863-1874, Sep. 2005. [6] E. Arias-de-Reyna, A. A. D’Amico, and U. Mengali, “UWB energy detection receivers with partial channel knowledge,” in Proc. IEEE ICC 2006, vol. 10, pp. 4688-4693, Istanbul, Turkey, 2006. [7] M. Weisenhorn and W. Hirt, “Robust noncoherent receiver exploiting UWB channel properties,” in Proc. IEEE UWBST, Kyoto, Japan, May 2004. [8] C. Carbonelli and U. Mengali, “M-PPM noncoherent receivers for UWB applications,” IEEE Trans. Wireless Commun., vol. 5, pp. 2285-2294, Aug. 2006. [9] D. Cabric, S. M. Mishra, and R. W. Brodersen, “Implementation issues in spectrum sensing for cognitive radios,” in Proc. IEEE Asilomar Conference on Signals, Systems and Computers 2004, pp. 772-776, Pacific Grove, CA, USA, Nov. 2004. [10] M. Ghozzi, M. Dohler, F. Marx, and J. Palico, “Cognitive radios: methods for detection of free bands,” Elsevier Science J., special issue on cognitive radio, vol. 7, pp. 794-805, Sep. 2006. [11] Y. Chen and N. C. Beaulieu, “Performance of collaborative spectrum sensing for cognitive radio in the presence of Gaussian channel estimation errors,” IEEE Trans. Commun., vol. 57, pp. 1944-1947, July 2009. [12] E. Visotsky, S. Kuffner, and R. Peterson, “On collaborative detection of TV transmissions in support of dynamic spectrum sharing,” in Proc. IEEE DySPAN 2005, pp. 338-345, Baltimore, U.S.A., Nov. 2005. [13] V. I. Kostylev, “Energy detection of a signal with random amplitude,” in Proc. ICC 2002, New York, pp. 1606-1610, May 2002. [14] F. F. Digham, M.-S. Alouini, and M. K. Simon, “On the energy detection of unknown signals over fading channels,” IEEE Trans. Commun., vol. 55, pp. 21-24, Jan. 2007. [15] S. M. Kay, Fundamentals of Statistical Signal Processing: Detection Theory. Upper Saddle River, NJ: Prentice-Hall, 1998. [16] I. S. Gradshteyn and I. M. Ryzbik, Table of Integrals, Series, and Products, 6th ed. San Diego, CA: Academic Press, 2000. [17] Y. Chen and N. C. Beaulieu, “SNR estimation methods for UWB systems,” IEEE Trans. Wireless Commun., vol. 6, pp. 3836-3845, Oct. 2007. [18] Y. Chen and N. C. Beaulieu, “Maximum likelihood estimation of SNR using digitally modulated signals,” IEEE Trans.Wireless Commun., vol. 6, pp. 210-219, Jan. 2007. [19] A. Conti, B. Masini, F. Zabini, and O. Andrisano, “On the down-link performance of multi-carrier CDMA systems with partial equalization,” IEEE Trans. Wireless Commun., vol. 6, pp. 230-239, Jan. 2007. [20] M. Chiani, A. Conti, and R. Verdone, “Partial compensation signallevel- based up-link power control toextend terminal battery duration,” IEEE Trans. Veh. Technol., vol. 50, pp. 1125-1131, July 2001. [21] “Channel modeling sub-committee report final,” IEEE P802.15- 02/490r1-SG3a, Feb. 2003.
URI:	http://wrap.warwick.ac.uk/id/eprint/3281