volume | PIER Journals

Abstract

Fast and efficient spectrum sensing is vital for multi-radio multi-channel cognitive radio (CR) networks where unlicensed secondary users (SUs) have to sense and opportunistically transmit on multiple spectrum bands without causing any harmful interference to the licensed primary users (PUs) of those spectrum bands. Accordingly, this paper presents a smart, practical and efficient wideband spectrum sensing scheme based on an optimal sensing stop policy that aims to optimize SU throughput while adhering to the PU interference constraints. Unlike existing work, this scheme is smart because in determining the best time for the multi-transmitter SU to stop sensing and start data transmission based on the channels that have been sensed idle, this scheme explicitly takes into consideration the number of transmitters on the SU; so-called N-transmitters constrained SU. Further, we formulate and solve the optimal sensing stopping problem. The numerical and simulation results presented verify the efficiency of the proposed sensing scheme.

1. Cordeiro, C., K. Challapali, D. Birru, and S. Shankar N, "IEEE 802.22: The first worldwide wireless standard based on cognitive radios," Proc. of the DySPAN Conf., 328-337, Baltimore, MD, Nov. 2005.

2. Yucek, T. and H. Arslan, "A survey of spectrum sensing algorithms for cognitive radio applications," IEEE Commun. Surveys and Tutorials, Vol. 11, No. 1, 116-130, Mar. 2009.
doi:10.1109/SURV.2009.090109 Google Scholar

3. Quan, Z., S. Cui, A. H. Sayed, and H. V. Poor, "Optimal multiband joint detection for spectrum sensing in cognitive radio networks," IEEE Trans. on Signal Processing, Vol. 57, No. 3, 1128-140, Mar. 2009.
doi:10.1109/TSP.2008.2008540 Google Scholar

4. Fan, R. and H. Jiang, "Optimal multi-channel cooperative sensing in cognitive radio networks," IEEE Trans. on Wireless Communications, Vol. 9, No. 3, 1128-1138, Mar. 2010.
doi:10.1109/TWC.2010.03.090467 Google Scholar

5. Kim, S. J. and G. B. Giannaskis, "Sequential and cooperative sensing for multi-channel cognitive radios," IEEE Transactions on Signal Processing, Vol. 58, No. 8, 4239-4253, Aug. 2010.
doi:10.1109/TSP.2010.2049106 Google Scholar

6. Chen, Z., N. Guo, and R. C. Qiu, "Demonstration of real-time spectrum sensing for cognitive radio," IEEE Communications Letters, Vol. 14, No. 10, 915-917, Oct. 2010.
doi:10.1109/LCOMM.2010.082610.100725 Google Scholar

7. Digham, F. F., M. S. Alouini, and M. K. Simon, "On the energy detection of unknown signals over fading channels," IEEE Transactions on Communications, Vol. 55, No. 1, 21-24, Jan. 2007.
doi:10.1109/TCOMM.2006.887483 Google Scholar

8. Zhao, Y., S. Li, N. Zhao, and Z. Wu, "A novel energy detection algorithm for spectrum sensing in cognitive radio," Information Technology Journal, Vol. 9, No. 8, 1659-1664, 2010.
doi:10.3923/itj.2010.1659.1664 Google Scholar

9. Zeng, Y. and Y. C. Liang, "Spectrum-sensing algorithms for cognitive radio based on statistical covariances," IEEE Transactions on Vehicular Technology, Vol. 58, No. 4, 1804-1815, May 2009.
doi:10.1109/TVT.2008.2005267 Google Scholar

10. Nikias, C. L. and J. M. Mendel, "Signal processing with higher-order spectra," IEEE Signal Processing Mag., Vol. 10, No. 3, 10-37, 1993.
doi:10.1109/79.221324 Google Scholar

11. Maranda, B. H. and J. A. Fawcett, "The performance analysis of a fourth-moment detector," Proc. International Conference on Acoustic, Speech, and Signal Processing (ICASSP-90), NM, USA, Apr. 1990. Google Scholar

12. Ferguson, T. S., Optimal stopping and applications, Oct. 2008, available at http://www.math.ucla.edu/ tom/Stopping/Contents.html.

Dr. Brownson Obaridoa Obele

Dr. Mohsin Iftikhar