Optimal cooperative energy spectrum sensing in cognitive radio network

Haijun WANG, Xin SU, Yi XU, Shidong ZHOU, Jing WANG

PDF(253 KB)
PDF(253 KB)
Front. Electr. Electron. Eng. ›› 2010, Vol. 5 ›› Issue (4) : 449-455. DOI: 10.1007/s11460-010-0113-z
RESEARCH ARTICLE
RESEARCH ARTICLE

Optimal cooperative energy spectrum sensing in cognitive radio network

Author information +
History +

Abstract

Cooperative energy spectrum sensing has been proved effective to detect the spectrum holes in cognitive radio (CR). In this paper, we present the optimal energy sensing algorithm in CR network and prove its optimality through the duality theorem of Neyman-Pearson theorem. Then, the optimal energy sensing algorithm is expanded to a cooperative sensing algorithm based on channel covariance matrix. We compare the proposed algorithms with traditional cooperative sensing algorithms in terms of complexity and required transmission bits. Simulation results validate the optimality of the proposed cooperative sensing algorithm. Furthermore, it is intuitively reasonable for the sensing station to choose the sensing nodes with better channel condition to cooperate, which is verified by our analysis and simulation.

Keywords

cognitive radio (CR) / cooperative sensing / likelihood-ratio test

Cite this article

Download citation ▾
Haijun WANG, Xin SU, Yi XU, Shidong ZHOU, Jing WANG. Optimal cooperative energy spectrum sensing in cognitive radio network. Front Elect Electr Eng Chin, 2010, 5(4): 449‒455 https://doi.org/10.1007/s11460-010-0113-z

References

[1]
Goldsmith A, Jafar S A, Maric I, Srinivasa S. Breaking spectrum gridlock with cognitive radios: an information theoretic perspective. Proceedings of the IEEE, 2009, 97(5): 894–914
CrossRef Google scholar
[2]
Cabric D, Mishra S M, Brodersen R W. Implementation issues in spectrum sensing for cognitive radios. In: Proceedings of the Thirty-Eighth Asilomar Conference on Signals, Systems, and Computers. 2004, 1: 772–776
[3]
Peh E, Liang Y C. Optimization for cooperative sensing in cognitive radio networks. In: Proceedings of IEEE Wireless Communications and Networking Conference. 2007, 27–32
[4]
Zhang W, Mallik R K, Letaief K B. Cooperative spectrum sensing optimization in cognitive radio networks. In: Proceedings of IEEE International Conference on Communications. 2008, 3411–3415
[5]
Yucek T, Arslan H. A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Communications Surveys & Tutorials, 2009, 11(1): 116–130
CrossRef Google scholar
[6]
Quan Z, Cui S, Sayed A H. Optimal linear cooperation for spectrum sensing in cognitive radio networks. IEEE Journal of Selected Topics in Signal Processing, 2008, 2(1): 28–40
CrossRef Google scholar
[7]
Ma J, Li Y. Soft combination and detection for cooperative spectrum sensing in cognitive radio networks. IEEE Transactions on Wireless Communications, 2008, 7(11): 4502–4507
CrossRef Google scholar
[8]
Uchiyama H, Umebayashi K, Kamiya Y, Suzuki Y, Fujii T, Ono F, Sakaguchi K. Study on cooperative sensing in cognitive radio based Ad-Hoc network. In: Proceedings of the 18th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications. 2007, 1–5
[9]
Kay S M. Fundamentals of Statistical Signal Processing (in Chinese, trans. Luo Pengfei, Zhang Wenming, Liu Zhong, et al.). Beijing: Publishing House of Electronics Industry, 2003

Acknowledgements

This work was supported by the National High Technology Research and Development Program of China (Grant No. 2007AA01Z289), the National Natural Science Foundation of China (Grant No. 60832008), and the National Basic Research Program of China (Grant No. 2007CB310608).

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
PDF(253 KB)

Accesses

Citations

Detail

Sections
Recommended

/