Research ArticleOpen AccessGoogle Scholar indexed
Markov Model Based Jamming and Anti-Jamming Performance Analysis for Cognitive Radio Networks
Department of Electrical and Computer Engineering, State University of New York at Binghamton, Binghamton, USA
Department of Electrical and Computer Engineering, State University of New York at Binghamton, Binghamton, USA
Department of Electrical and Computer Engineering, State University of New York at Binghamton, Binghamton, USA
- 1 Department of Electrical and Computer Engineering, State University of New York at Binghamton, Binghamton, USA
- 2 Department of Electrical and Computer Engineering, State University of New York at Binghamton, Binghamton, USA
- 3 Department of Electrical and Computer Engineering, State University of New York at Binghamton, Binghamton, USA
Communications and Network·Volume 06 (2014)·Pages 76–85·Published 8 May 2014·DOI10.4236/cn.2014.62010
Copy link · social · email
Abstract
In this paper, we conduct a cross-layer analysis of both the jamming capability of the cognitiveradio-based jammers and the anti-jamming capability of the cognitive radio networks (CRN). We use a Markov chain to model the CRN operations in spectrum sensing, channel access and channel switching under jamming. With various jamming models, the jamming probabilities and the throughputs of the CRN are obtained in closed-form expressions. Furthermore, the models and expressions are simplified to determine the minimum and the maximum CRN throughput expressions under jamming, and to optimize important anti-jamming parameters. The results are helpful for the optimal anti-jamming CRN design. The model and the analysis results are verified by simulations.
KeywordsCognitive RadioDynamic Spectrum AccessJammingMarkov ModelThroughput
- Akyildiz, I.F., Lee, W.-Y., Vuran, M.C. and Mohanty, S. (2006) NeXt Generation/Dynamic Spectrum Access/Cognitive Radio Wireless Networks: A Survey. Computer Networks, 50, 2127-2159. http://dx.doi.org/10.1016/j.comnet.2006.05.001
- McHenry, M., Livsics, E., Nguyen, T. and Majumdar, N. (2007) XG Dynamic Spectrum Access Field Test Results. IEEE Xplore: Communications Magazine, 45, 51-57. http://dx.doi.org/10.1109/MCOM.2007.374432
- Cordeiro, C., Challapali, K., Birru, D. and Shankar, S. (2006) IEEE 802.22: An Introduction to the First Wireless Standard Based on Cognitive Radios. Journal of Communication, 1, 38-47.
- Clancy, T.C. and Goergen, N. (2008) Security in Cognitive Radio Networks: Threats and Mitigation. International Conference on Cognitive Radio Oriented Wireless Networks and Communications, Singapore.
- Chen, R., Park, J.-M. and Reed, J.H. (2008) Defense Against Primary User Emulation Attacks in Cognitive Radio Networks. IEEE Journal on Selected Areas in Communications, Special Issue on Cognitive Radio Theory and Applications, 26, 25-37. http://dx.doi.org/10.1109/JSAC.2008.080104
- Wang, Q., Ren, K. and Ning, P. (2011) Anti-Jamming Communication in Cognitive Radio Networks with Unknown Channel Statistics. 2011 19th IEEE International Conference on Network Protocols (ICNP), 393-402.
- Pietro, R.D. and Oligeri, G. (2013) Jamming Mitigation in Cognitive Radio Networks. IEEE Network, 27, 10-15. http://dx.doi.org/10.1109/MNET.2013.6523802
- Li, H. and Han, Z. (2009) Dogfight in Spectrum: Jamming and Anti-Jamming Inmultichannel Cognitive Radio Systems. Proc. of IEEE GLOBECOM, 1-6.
- Wang, B., Wu, Y., Liu, K.J.R. and Clancy, T.C. (2011) An Anti-Jamming Stochastic Game for Cognitive Radio Networks. IEEE Journal on Selected Areas in Communications, 29, 877-889. http://dx.doi.org/10.1109/JSAC.2011.110418
- Chen, C., Song, M., Xin, C. and Backens, J. (2013) A Game-Theoretical Anti-Jamming Scheme for Cognitive Radio Networks. IEEE Network, 27, 22-27. http://dx.doi.org/10.1109/MNET.2013.6523804
- Tumuluru, V.K., Wang, P., Niyato, D. and Song, W. (2012) Performance Analysis of Cognitive Radio Spectrum Access with Prioritized Traffic. IEEE Transactions on Vehicular Technology, 61, 1895-1906. http://dx.doi.org/10.1109/TVT.2012.2186471
- Li, X. and Cadeau, W (2011) Anti-Jamming Performance of Cognitive Radio Networks. Proceedings of the 45th Annual Conf. on Information Sciences and Systems (CISS), Johns Hopkins Univ., Baltimore.