Abstract
In this paper, we consider a cluster-based cooperative spectrum sensing approach to improve the sensing performance of cognitive radio (CR) network. In the cluster-based cooperative spectrum sensing, CR users with the similar location are grouped into a cluster. In each cluster, the most favorable user namely cluster header, will be chosen to collect data from all CR users and send the cluster decision to common receiver who makes a final decision on the presence of primary user. In the cluster-based cooperative spectrum sensing, data fusion rule in the cluster takes an important role to reduce the rate of reporting error. Subsequently we propose optimal fusion rule for each cluster header with which we can minimize the sum of probability of false alarm and probability of missed detection in each cluster header.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Federal Communications Commission: Spectrum Policy Task Force. Rep. ET Docket, 02–135 (2002)
Mitola, J., Maguire, G.Q.: Cognitive Radio: Making Software Radios More Personal. IEEE Pers. Commun. 6, 138 (1999)
Haykin, S.: Cognitive Radio: Brain-empowered Wireless Communications. IEEE J. Select. Areas Commun. 23, 201–220 (2005)
Ganesan, G., Y. Li, G.: Cooperative Spectrum Sensing in Cognitive Radio Networks. In: Proc. IEEE Symp. New Frontiers in Dynamic Spectrum Access Networks (DySPAN5), Baltimore, USA (2005)
Ghasemi, A., Sousa, E.S.: Collaborative Spectrum Sensing for Opportunistic Access in Fading Environments. In: Proc. IEEE Symp. New Frontiers in Dynamic Spectrum Access Networks (DySPAN5), Baltimore, USA, vol. 81, pp. 131–136 (2005)
Mishra, S.M., Sahai, A., Brodersen, R.: Cooperative Sensing Among Cognitive Radios. In: Proc. IEEE Int. Conf. Commun., Turkey, vol. 4, pp. 1658–1663 (2006)
Cabric, D., Mishra, S.M., Brodersen, R.W.: Implementation Issues in Spectrum Sensing for Cognitive Radios. In: Proc. of Asilomar Conf. on Signals, Systems and Computers, Pacific Grove, CA, USA, pp. 772–776 (2004)
Sun, C., Zhang, W., Letaief, K.B.: Cluster-based Cooperative Spectrum Sensing for Cognitive Radio Systems. In: Proc. IEEE Int. Conf. Commun., Glasgow, Scotland, UK, pp. 2511–2515 (2007)
Hur, Y., Park, J., Woo, W., Lim, K., Lee, C.H., Kim, H.S., Laskar, J.: A Wideband Analog Multi-resolution Spectrum Sensing (MRSS) Technique for Cognitive Radio (CR) Systems. In: Proc. IEEE Int. Symp. Circuit and System, Greece, pp. 4090–4093 (2006)
Sahai, A., Hoven, N., Tandra, R.: Some Fundamental Limits on Cognitive Radio. In: Proc. Allerton Conf. on Communications, control, and computing, Monticello (2004)
Digham, F.F., Alouini, M.S., Simon, M.K.: In the Energy Detection of Unknown Signals Over Fading Channels. In: Proc. IEEE Int. Conf. Commun., Anchorage, AK, USA, pp. 3575–3579 (2003)
Zhang, W., Mallik, R.K., Letaief, K.B.: Cooperative Spectrum Sensing Optimization in Cognitive Radio Networks. In: Proc. IEEE Int. Conf. on Commun., Beijin, pp. 3411–3415 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Van, HV., Koo, I. (2009). An Optimal Data Fusion Rule in Cluster-Based Cooperative Spectrum Sensing. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence. ICIC 2009. Lecture Notes in Computer Science(), vol 5755. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04020-7_76
Download citation
DOI: https://doi.org/10.1007/978-3-642-04020-7_76
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04019-1
Online ISBN: 978-3-642-04020-7
eBook Packages: Computer ScienceComputer Science (R0)