Design of fuzzy logic system for cognitive radio networks for efficient spectrum decision and channel assignment

  • Authors

    • Ch Suneetha
    • S Srinivasa Rao
    • K S. Ramesh
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.14166
  • Wireless sensor network, Cognitive radio, Fuzzy logic, Spectrum management.
  • Wireless sensor networks (WSNs) are becoming highly preferable for various day to day applications. Cognitive radio (CR) is a paradigm that can deploy IPV6, which has built-in auto configuration features along with large 128-bit address space for efficient spectrum allocation by considering all possible QOS parameters. An efficient spectrum decision has been developed based on fuzzy for secondary users channel assignment. The parameter such as Signal strength, node velocity and distance between PU and SU for unused available BW IPV6 header has been identified for information such as text, voice or video to be forwarded by the Secondary users with efficient spectrum allocation. The spectrum decision and channel assignment for secondary users has been simulated to obtain satisfactory results

     

     

  • References

    1. [1] Spectrum Policy Task Force Report Technical report 02-135 Federal communications commission Nov. 2002.

      [2] Senhua Huang, Xin Liu†opportunistic spectrum access in cognitive radio networks†IEEE INFOCOM proceedings 2008

      [3] Simon Haykin "Cognitive radio: Brain-empowered wireless communication" IEEE Journal on Selected Areas in Communications vol. 23 no. 5 Feb 2005 pp. 201-220.

      [4] Hong-Sam T. Le ,Hung D. Ly “Opportunistic spectrum access using Fuzzy Logic for cognitive radio networks†IEEE Journal on Communications march 2008

      [5] Ian F. Akyildiz et al "NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey" Computer Networks Journal (Elsevier) vol. 50 pp. 2127-2159 September 2006.

      [6] G. Ko A. A. Franklin S. J. You J. S. Pak M. S. Song C. J. Kim "Channel management in IEEE 802.22 WRAN systems" IEEE Communication. Mag. vol. 48 no. 9 pp. 88-94 Sep. 2010

      [7] W.-Y. Lee I. F. Akyildiz "A spectrum decision framework for cognitive radio networks" IEEE Trans. Mobile Computing vol. 10 no. 2 pp. 161-174 Feb. 2011

      [8] Moshe Timothy Masonta, Mjumo Mzyece “Spectrum Decision in Cognitive Radio Networks: A Surveyâ€IEEE communications surveys and tutorialsvol.15, No.3 Nov.2013

      [9] I.F. Akyildiz, W.Y. Lee, M.C. Vuran, and S. Mohanty, A Survey on Spectrum Management in Cognitive Radio Networks", IEEE Communications Magazine, vol. 46, issue. Four, pp. 40-48, April 2008.

      [10] L. Giupponi and Ana I. P_erez-Neira, Fuzzy-based Spectrum Handoff in Cognitive Radio Networks", third International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom), Singapore, May 2008.

      [11] B. Wang, Z. Ji, and K.J.R. Liu Primary-Prioritized Markov Approach for Dynamic Spectrum Allocation", IEEE Transaction on Wireless Communication (T-WC), vol. 8, no. 4, pp. 1854-1865, April 2009.

      [12] Y.Xing, R. Chandramouli, S.Mangold, and S.S.Nandagopalan, Dynamic spectrum access in open spectrum in wireless networks", IEEE Journal on Selected Areas in Communications (JSAC), vol. 24, no. 3, pp. 626-637, March 2006.

      [13] P.K. Tang, Y.H. Chew, L.C. Ong, and M.K. Halder, Performance of secondary radios in spectrum sharing with prioritized primary access", In IEEE Military Communications Conference (MilCom), Washington, DC, October 2006

      [14] D. Datla R. Rajbanshi A. M. Wyglinski G. J. Minden "An Adaptive Spectrum Sensing Architecture for Dynamic Spectrum Access Networks" IEEE Trans. Wireless Communication vol. 8 no. 8 pp. 4211-4219 2009

      [15] M. Matinmikko M. Mustonen T. Rauma J. Del Ser "Decision-making System for Obtaining Spectrum Availability Information in Opportunistic Networks" Proc. fourth International Conference on Cognitive Radio and Advanced Spectrum Management (CogART 2011) pp. 1-6 October 2011.

      [16] C. Clancy J. Hecker E. Stuntebeck T. O'Shea "Applications of Machine Learning to Cognitive Radio Networks" IEEE Wireless Communications vol. 14 no. 4 pp. 47-52 , nov. 2007.

      [17] M. Matinmikko M. Mustonen†Fuzzy logic Based framework for spectrum availability assessment in cognitive radio systems†IEEE Journal on selected areas in communications Vol.31. No.11, nov.2013.

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  • How to Cite

    Suneetha, C., Srinivasa Rao, S., & S. Ramesh, K. (2018). Design of fuzzy logic system for cognitive radio networks for efficient spectrum decision and channel assignment. International Journal of Engineering & Technology, 7(2.33), 266-272. https://doi.org/10.14419/ijet.v7i2.33.14166