Abstract
In the single spectrum sensing, it is difficult to overcome obstacles, path loss, deep noise and fading in the network. Cooperative spectrum sensing (CSS) has been proposed as one of solutions to overcome the drawback of the single spectrum sensing. In the CSS, a fusion center collects the sensing information from all secondary users and makes a final decision. Even though CSS can provide better sensing performance than the single spectrum sensing, the problems above mentioned still remain. Thus effective decision method is needed for more adaptive to communication environment. In the paper, we propose a cooperative spectrum sensing utilizing neural network for cognitive radio systems. In the proposed scheme, weight factors of the neural network are trained by using historical sensing information stored on buffer. After that, a final decision is made by using current sensing information as input of neural network. Through the simulation result, we can find the proposed scheme has better performance than other comparison schemes such as AND, OR and half voting rules.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Mitola III., J.: Cognitive Radios: Making Software Radios More Personal. IEEE Personal Communications 6(4), 13–18 (1999)
Mitola III., J.: Cognitive Radio for Flexible Mobile Multimedia Communications. In: IEEE International Workshop on Mobile Multimedia Communications, pp. 3–10 (November 1999)
Ganesan, G., Li, Y.G.: Cooperative Spectrum Sensing in Cognitive Radio Networks. In: IEEE Symposium New Frontiers in Dynamic Spectrum Access Networks (DySPAN 2005), November 8-11, pp. 137–143 (2005)
Mishra, S.M., Sahai, A., Brodersen, R.: Cooperative Sensing Among Cognitive Radios. In: IEEE International Conference, vol. 4, pp. 1658–1663 (2006)
Sun, C., Zhang, W., Letaief, K.B.: Cluster-based Cooperative Spectrum Sensing for Cognitive Radio Systems. In: IEEE International Conference. ICC 2007, June 24-28, pp. 2511–2515 (2007)
Urkowitz, H.: Energy Detection of Unknown Deterministic Signals. Proceedings of the IEEE 55, 523–531 (1967)
Haykin, S.: Neural Networks: A Comprehensive Foundation, 2nd edn., pp. 156–255 (1999)
Hossain, E., Niyato, D., Han, Z.: Dynamic Spectrum Access and Management in Cognitive Radio Networks, pp. 223–273 (2009)
IEEE 802.22: IEEE 802.22 / D0.2 Draft Standard for Wireless Regional Area Networks Part22: Cognitive Wireless RAN Medium Access Control and Physical specifications: Policies and procedures for operation in the TV Bands (2006)
IEEE 802.22: IEEE 802.22 / D0.3.7 Draft Standard for Wireless Regional Area Networks Part22: Cognitive Wireless RAN Medium Access Control and Physical specifications: Policies and procedures for operation in the TV Bands (2007)
Zhang, W., Mallik, R.K., Letaief, K.B.: Cooperative Spectrum Sensing Optimization in Cognitive Radio Networks. In: IEEE International Conference. ICC 2008, May 19-23, pp. 3411–3415 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lee, Y., Koo, I. (2010). A Neural Network-Based Cooperative Spectrum Sensing Scheme for Cognitive Radio Systems. In: Huang, DS., McGinnity, M., Heutte, L., Zhang, XP. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Communications in Computer and Information Science, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14831-6_49
Download citation
DOI: https://doi.org/10.1007/978-3-642-14831-6_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14830-9
Online ISBN: 978-3-642-14831-6
eBook Packages: Computer ScienceComputer Science (R0)