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Improved energy detector for random signals in Gaussian noise

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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

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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

Official Date:

February 2010

Dates:

Date	Event
February 2010	Published

Volume:

Vol.9

Number:

No.2

Number of Pages:

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.