RESEARCH ARTICLE

A design of multi-cycle detector for cognitive radios

  • Jun WANG ,
  • Guangguo BI
Expand
  • National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China

Received date: 08 Jul 2010

Accepted date: 24 Jun 2011

Published date: 05 Dec 2011

Copyright

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg

Abstract

Cognitive radio (CR) is a promising technology. The most fundamental problem of CR is spectrum sensing. Energy detector is often considered for spectrum sensing in CR, and if the noise power is exactly known, energy detector has admirable performance. However, in practice, noise power is always inexactly known. To solve this problem, Dandawate [Dandawate et al. IEEE Transactions on Signal Processing, 1994, 42(9): 2355–2369] has proposed a nonparametric single-cycle detector based on cyclostationarity, which is robust to noise uncertainty. In this paper, based on Dandawate’s single-cycle detector, a joint multi-cycle detector is further proposed, which is also nonparametric and immune from noise uncertainty. Simulation results have shown the validity and superiority over single-cycle detector of the proposed detector.

Cite this article

Jun WANG , Guangguo BI . A design of multi-cycle detector for cognitive radios[J]. Frontiers of Electrical and Electronic Engineering, 2011 , 6(4) : 501 -506 . DOI: 10.1007/s11460-011-0180-9

Acknowledgements

This work was supported in part by the National Basic Research Program of China (Grant No. 2007CB310603), and in part by the Research Fund of National Mobile Communications Research Laboratory, Southeast University (No. 2010A05).
1
Yucek T, Arslan H. A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Communications Surveys & Tutorials, 2009, 11(1): 116-130

2
Haykin S, Thomson D J, Reed J H. Spectrum sensing for cognitive radio. Proceedings of the IEEE, 2009, 97(5): 849-877

DOI

3
Rawat D B, Yan G. Signal processing techniques for spectrum sensing in cognitive radio systems: Challenges and perspectives. In: Proceedings of the First Asian Himalayas International Conference on Internet. 2009, 1-5

4
Tandra R, Sahai A.SNR walls for signal detection. IEEE Journal of Selected Topics in Signal Processing, 2008, 2(1): 4-17

5
Shellhammer S, Tandra R.Performance of the power detector with noise uncertainty. IEEE Std. 802.22–06/0134r0, 2006

6
Dandawate A V, Giannakis G B. Statistical tests for presence of cyclostationarity. IEEE Transactions on Signal Processing, 1994, 42(9): 2355-2369

DOI

7
Lundén J, Koivunen V, Huttunen A, Poor H V. Spectrum sensing in cognitive radios based on multiple cyclic frequencies. In: Proceedings of the 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications. 2007, 37-43

8
Sadler B M, Dandawate A V. Nonparametric estimation of the cyclic cross spectrum. IEEE Transactions on Information Theory, 1998, 44(1): 351-358

DOI

9
Kay S M. Fundamentals of Statistical Signal Processing: Estimation Theory. New York: Prentice Hall PTR, 1993

10
Anderson T W. An Introduction to Multivariate Statistical Analysis. 3rd ed. New Jersey: John Wiley & Sons, 2003

11
Sutton P D, Nolan K E, Doyle L E. Cyclostationary signatures in practical cognitive radio applications. IEEE Journal on Selected Areas in Communications, 2008, 26(1): 13-24

DOI

12
Harada H, Maeda K, Furuno T, Miura S, Ohya T. Performance evaluation of overhead reduction method for cyclostationarity-inducing transmission. In: Proceedings of the 71st IEEE Vehicular Technology Conference. 2010, 1-5

Outlines

/