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Optimal Voting Rule and Minimization of Total Error Rate in Cooperative Spectrum Sensing for Cognitive Radio Networks

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In cognitive radio technology, spectrum sensing is essential for detecting spectrum holes which may be allotted to secondary users. In this paper, an optimal voting rule is used for cooperative spectrum sensing while minimizing the total error rate (TER). The proposed spectrum sensing method is more energy-efficient and may be implemented in practice. It is relied upon in an improved energy detector whose utilization depends on the presence or absence of the primary user. Expressions for false alarm and missed detection probabilities are derived in the paper as well. Overall performance is analyzed both for AWGN and Rayleigh fading channels, in the presence of additive white Gaussian noise (AWGN). The optimum voting rule is applied to the cooperative spectrum sensing process in order to identify the optimum number of sensing nodes and the detection threshold. Finally, an energy-efficient spectrum sensing algorithm is proposed, requiring a lower number of cognitive users for a given error bound.
Rocznik
Tom
Strony
43--50
Opis fizyczny
Bibliogr. 25 poz., rys., tab.
Twórcy
  • Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani, Hyderabad Campus, Hyderabad-500078
  • Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani, Hyderabad Campus, Hyderabad-500078
autor
  • Department of Electronics and Communication Engineering, GLA University, Mathura Mathura-281 406 (U.P.)
Bibliografia
  • [1] S. Haykin, „Cognitive radio: brain-empowered wireless communications", IEEE J. on Selec. Areas in Commun., vol. 23, no. 2, pp. 201-220, 2005 (DOI: 10.1109/JSAC.2004.839380).
  • [2] Y.-C. Liang, Y. Zeng, E. C. Peh, and A. T. Hoang, „Sensing-throughput tradeoff for cognitive radio networks", IEEE Trans. On Wirel. Commun., vol. 7, no. 4, pp. 1326-1337, 2008 (DOI: 10.1109/TWC.2008.060869).
  • [3] K. Poularakis, G. Iosifidis, V. Sourlas, and L. Tassiulas, „Exploiting caching and multicast for 5G wireless networks", IEEE Trans. On Wirel. Commun., vol. 15, no. 4, pp. 2995-3007, 2016 (DOI: 10.1109/TWC.2016.2514418).
  • [4] F. Haider et al., „Spectral and energy efficiency analysis for cognitive radio networks", IEEE Trans. on Wirel. Commun., vol. 14, no. 6, pp. 2969-2980, 2015 (DOI: 10.1109/TWC.2015.2398864).
  • [5] M. Klymash, M. Jo, T. Maksymyuk, and I. Beliaiev, „Spectral efficiency increasing of cognitive radio networks", in Proc. 12th Int. Conf. on the Exper. of Desig. and Appl. of CAD Syst. in Microelectron. CADSM 2013, Polyana Svalyava, Ukraine 2013, pp. 169-171 (ISBN: 9781467364614).
  • [6] J. Mitola and G. Q. Maguire, „Cognitive radio: making software radios more personal", IEEE Pers. Commun., vol. 6, no. 4, pp. 13-18, 1999 (DOI: 10.1109/98.788210).
  • [7] B. Wang and K. R. Liu, „Advances in cognitive radio networks: A survey", IEEE J. of Selec. Topics in Sig. Process., vol. 5, no. 1, pp. 5-23, 2010 (DOI: 10.1109/JSTSP.2010.2093210).
  • [8] T. Yucek and H. Arslan, „A survey of spectrum sensing algorithms for cognitive radio applications", IEEE Commun. Surv. & Tutor., vol. 11, no. 1, pp. 116-130, 2009 (DOI: 10.1109/SURV.2009.090109).
  • [9] M. S. Falih and H. N. Abdullah, „A combined spectrum sensing method based DCT for cognitive radio system", Int. J. of Elec. & Comp. Engin., vol. 10, no. 2, pp. 1935-1942, 2020 (DOI: 10.11591/ijece.v10i2.pp1935-1942).
  • [10] I. F. Akyildiz, W.-Y. Lee, M. C. Vuran, and S. Mohanty, „Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey", Computer Networks, vol. 50, no. 13, pp. 2127-2159, 2006 (DOI: 10.1016/j.comnet.2006.05.001).
  • [11] X. Kang, Y.-C. Liang, A. Nallanathan, H. K. Garg, and R. Zhang, „Optimal power allocation for fading channels in cognitive radio networks: Ergodic capacity and outage capacity", IEEE Trans. On Wirel. Commun., vol. 8, no. 2, pp. 940-950, 2009 (DOI: 10.1109/TWC.2009.071448).
  • [12] K. B. Letaief and W. Zhang, „Cooperative communications for cognitive radio networks", Proc. of the IEEE, vol. 97, no. 5, pp. 878-893, 2009 (DOI: 10.1109/JPROC.2009.2015716).
  • [13] G. Zhao, G. Y. Li, C. Yang, and J. Ma, „Proactive detection of spectrum holes in cognitive radio", in Proc. of IEEE Int. Conf. on Commun., Dresden, Germany, 2009 (DOI: 10.1109/JPROC.2009.2015716).
  • [14] W. Zhang, R. K. Mallik, and K. B. Letaief, „Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks", IEEE Trans. on Wirel. Commun., vol. 8, no. 12, pp. 5761-5766, 2009 (DOI: 10.1109/TWC.2009.12.081710).
  • [15] S. K. Ghosh and P. Bachan, „Performance evaluation of spectrum sensing techniques in cognitive radio network", IOSR J. of Electron. and Commun. Engin. (IOSR-JECE), vol. 12, no. 4, pp. 17-21, 2017 (DOI: 10.9790/2834-1204051721).
  • [16] I. F. Akyildiz, B. F. Lo, and R. Balakrishnan, „Cooperative spectrum sensing in cognitive radio networks: A survey", Phys. Commun., vol. 4, no. 1, pp. 40-62, 2011 (DOI: 10.1016/j.phycom.2010.12.003).
  • [17] G. Verma and O. Sahu, „A distance based reliable cooperative spectrum sensing algorithm in cognitive radio", Wirel. Pers. Commun., vol. 99, no. 1, pp. 203-212, 2018 (DOI: 10.1007/s11277-017-5052-z).
  • [18] P. Bachan, S. K. Ghosh, and S. K. Saraswat, „Comparative error rate analysis of cooperative spectrum sensing in non-fading and fading environments", in Proc. of Commun., Contr. and Intell. Syst. CCIS 2015, Mathura, India, 2015 pp. 124-127, 2015 (DOI: 10.1109/CCIntelS.2015.7437891).
  • [19] W. Zhang and K. B. Letaief, „Cooperative spectrum sensing with transmit and relay diversity in cognitive radio networks", IEEE Trans. on Wirel. Commun., vol. 7, no. 12, pp. 4761-4766, 2008 (DOI: 10.1109/T-WC.2008.060857).
  • [20] S. K. Ghosh, J. Mehedi, and U. C. Samal, „Sensing performance of energy detector in cognitive radio networks", Int. J. of Inf. Technol., vol. 11, no. 4, pp. 773-778, 2019 (DOI: 10.1007/s41870-018-0236-7).
  • [21] S. Atapattu, C. Tellambura, and H. Jiang, „Energy detection based cooperative spectrum sensing in cognitive radio networks", IEEE Trans. on Wirel. Commun., vol. 10, no. 4, pp. 1232-1241, 2011 (DOI: 10.1109/TWC.2011.012411.100611).
  • [22] G. Mahendru, A. Shukla, and P. Banerjee, „A novel mathematical model for energy detection based spectrum sensing in cognitive radio networks", Wirel. Pers. Commun., vol. 110, no. 3, pp. 1237-1249, 2020 (DOI: 10.1007/s11277-019-06783-3).
  • [23] F. F. Digham, M.-S. Alouini, and M. K. Simon, „On the energy detection of unknown signals over fading channels", IEEE Trans. On Commun., vo. 55, no. 1, pp. 21-24, 2007 (DOI: 10.1109/TCOMM.2006.887483).
  • [24] I. S. Gradshteyn and I. M. Ryzhik, Table of Integrals, Series, and Products, 8th ed. Academic Press, 2014 (ISBN: 9780123849335).
  • [25] A. Nuttall, „Some integrals involving the Q M function (Corresp.)", IEEE Trans. on Inform. Theory, vol. 21, no. 1, pp. 95-96, 1975 (DOI: 10.1109/TIT.1975.1055327).
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-db0aa9ed-99e8-4917-84f8-2cb9eb039fb3
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