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Performance Evaluation of Cognitive Radio Network Based on 2-D Markov Chain

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Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The objective of cognitive radio network is to enhance the wireless network spectrum utilization. In such a network, two types of users are enlisted, namely primary user (PU) and secondary user (SU). The PU can access any channel in case of its availability, but SU users have lower priority and can access a channel only when it is unused by PUs. The performance of such a network solely depends on two traffic parameters: probability of false alarm and probability of misdetection. In this paper the performance of such a network is analyzed based on two dimensional Markov chain including those parameters. The main contribution of this paper is to evaluate blocking probability and PU and SU throughput using the state transition chain instead of existing statistical analysis.
Rocznik
Tom
Strony
39--44
Opis fizyczny
Bibliogr. 21 poz., rys.
Twórcy
autor
  • Department of Computer Science and Engineering, Jahangirnagar University, Savar, Dhaka, Bangladesh
autor
  • Department of Computer Science and Engineering, Jahangirnagar University, Savar, Dhaka, Bangladesh
autor
  • Department of Computer Science and Engineering, Jahangirnagar University, Savar, Dhaka, Bangladesh
autor
  • Department of Computer Science and Engineering, Jahangirnagar University, Savar, Dhaka, Bangladesh
Bibliografia
  • [1] S. Cheng, Foundation of Cognitive Radio Systems. Rijeka, Croatia: InTech, 2012.
  • [2] Y. Xiao and F. Hu, Cognitive Radio Networks. CRC Press, Taylor & Francis Group, 2009.
  • [3] J. Ma, G. Y. Li, and B. H. Juang, “Signal processing in cognitive radio”, in Proc. of the IEEE, vol. 97, no. 5, pp. 805–823, 2009.
  • [4] S. Wang, Y. Wang, J. P. Coon, and A. Doufexi, “Energy-efficient spectrum sensing and access for cognitive radio networks”, IEEE Trans. Veh. Technol., vol. 61, no. 2, pp. 906–912, 2012.
  • [5] K. Thakur and N. K. Dewangan, “Cognitive radios and their role in efficient allocation of the spectrum”, Mediter. J. Social Sci., vol. 3, no. 15, pp. 152–164, 2012.
  • [6] D. Cabric, S. Mishra, and R. W. Brodersen, “Implementation issues in spectrum sensing for cognitive radios”, in Proc. 38th Asilomar Conf. Sig., Syst. and Comp. ASILOMAR 2004, Pacific Grove, CA, USA, 2004, pp. 772–776.
  • [7] A. Ghasemi and E. S. Sousa, “Spectrum sensing in cognitive radio networks: the cooperation-processing trade-off”, Wirel. Commun. and Mobile Comp., Special Issue on Cognitive Radio, Software-Defined Radio, and Adaptive Wireless Systems, vol. 7, no. 9, pp. 1049–1060, 2007.
  • [8] R. Xie, F. R. Yu, and H. Ji, “Dynamic resource allocation for hetero- geneous services in cognitive radio networks with imperfect channel sensing”, IEEE Trans. Veh. Technol., vol. 61, no. 2, pp. 770–780, 2012.
  • [9] W. Han, J. Li, Q. Liu, and L. Zhao, “Spatial false alarms in cognitive radio”, IEEE Commun. Lett., vol. 15, no. 5, pp. 518–520, 2011.
  • [10] R. T. Khan, T. N. Shabnam, Md. Imdadul Islam, and M. R. Amin, “Enhancement of performance of cognitive radio network with incorporation of MRC scheme at secondary receiver”, IACSIT Int. J. Engine. Technol., vol. 4, no. 4, pp. 495–499, 2012.
  • [11] Y. Y. Mihov and B. P. Tsankov, “Cognitive system with VoIP secondary users over VoIP primary users”, in Proc. 3rd Int. Conf. Adv. Cogn. Technol. Appl. COGNITIVE 2011, Rome, Italy, 2011, pp. 30–35.
  • [12] Y. Y. Mihov, “Cross-layer QoS provisioning in cognitive radio networks”, IEEE Commun. Lett., vol. 16, no. 5, pp. 678–681, 2012.
  • [13] Md. Imdadul Islam, J. K. Das, and S. Hossain, “Modeling of mixed traffic for mobile cellular network”, J. Telecommun. Inform. Technol., no. 1, pp. 83–89, 2007.
  • [14] Md. S. Hossain and M. Imdadul Islam, “A proposed 2-D queuing model of PCT-I traffic”, in Proc. 6th Int. Conf. Comp. Informa. Technol. ICCIT 2003, Dhaka, Bangladesh, 2003, pp. 114–118.
  • [15] Y. Fang, “Thinning scheme for call admission control in wireless networks”, IEEE Transa. Comp., vol. 52, no. 5, pp. 685–687, 2003.
  • [16] G. D. Morley and W. D. Grover, “Strategies to Maximize Carried Traffic in Dual-Mode Cellular Systems”, IEEE Trans. Veh. Technol., vol. 49, no. 2, pp. 357–366, 2000.
  • [17] B. Li, L. Li, B. Li, K. M. Sivalingam, and X.-R. Cao, “Call admission control for voice/data integrated cellular networks: performance analysis and comparative study”, IEEE J. Selec. Areas Commun., vol. 22, no. 4, pp. 706–718, 2004.
  • [18] B. Jabbari and W. F. Fuhrmann, “Teletraffic modeling and analysis of flexible hierarchical cellular network with speed sensitive handoff strategy”, IEEE J. Selec. Areas Commun., vol. 15, no. 8, pp. 1539–48, 1997.
  • [19] F. Pavlidou, “Two-dimensional traffic models for cellular systems”, IEEE Trans. Commun., vol. 42, no. 2/3/4, pp. 1505–1511, 1994.
  • [20] Md. Imdadul Islam and J. K. Das, “A mathematical model of traffic performance of mobile cellular network”, J. Elec. Comp. Sci., vol. 8, pp. 1–9, 2007.
  • [21] M. B. Bhuiyan et al., “Performance evaluation of cognitive radio network under limited user traffic”, Jahangirnagar Univer. J. Elec. Comp. Sci., vol. 15, pp. 23–28, 2014.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-64181e8f-ba61-45cd-81ce-550732069b45
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