Review and Challenges of Future Technologies in Spectrum Management over Cognitive Radio Network
Keywords:Cognitive Radio, Wireless, Communication.
AbstractCognitive radio is generally expected to be cutting edge in remote correspondences. Range administrative Boards of trustees in numerous nations have been finding a way to make the way for dynamic range get to utilizing this innovation and furthermore setting out the guidelines for its implementation. Global associations have likewise been taking a stab at normalizing and harmonization this tech-nology for different applications. This paper outlines meaning of Cognitive radio frameworks and portrays the condition of workmanship in the administrative and normalization activi-ties on cognitive radio everywhere throughout the world, which are esteemed to have essential impact on the eventual fate of remote interchanges. Cognitive radio ideas can be applied to an assortment of remote correspondences sce-narios, a couple of which are portrayed in this paper. At long last, in view of led overview through the specialized and administrative examination, a reliable end is given.
W. Lee, "Resource Allocation for Multi-Channel Underlay Cognitive Radio Network Based on Deep Neural Network," in IEEE Communications Letters, Vol. 22, No. 9, pp. 1942-1945, Sept. 2018. . P. Zuo, T. Peng, W. Linghu and W. Wang, "Resource Allocation for Cognitive Satellite Communications Downlink," in IEEE Access, Vol. 6, pp. 75192-75205, 2018.
. D. Das and S. Das, "Intelligent resource allocation scheme for the cognitive radio network in the presence of primary user emulation attack," in IET Communications, Vol. 11, No. 15, pp. 2370-2379, 19 10 2017.
. A. Sultana, L. Zhao and X. Fernando, "Efficient Resource Allocation in Device-to-Device Communication Using Cognitive Radio Technology," in IEEE Transactions on Vehicular Technology, Vol. 66, No. 11, pp. 10024-10034, Nov. 2017.
. L. Zhu and X. Zhao, "Robust power allocation for orthogonal frequency division multiplexing-based overlay/underlay cognitive radio network under spectrum sensing errors and channel uncertainties," in IET Communications, Vol. 10, No. 15, pp. 2010-2017, 13 10 2016.
. A. Ahmad, S. Ahmad, M. H. Rehmani and N. U. Hassan, "A Survey on Radio Resource Allocation in Cognitive Radio Sensor Networks," in IEEE Communications Surveys & Tutorials, Vol. 17, No. 2, pp. 888-917, Secondquarter 2015.
. Y. Long, H. Li, H. Yue, M. Pan and Y. Fang, "SUM: Spectrum Utilization Maximization in Energy-Constrained Cooperative Cognitive Radio Networks," in IEEE Journal on Selected Areas in Communications, Vol. 32, No. 11, pp. 2105-2116, November 2014. . H. Xu and B. Li, "Resource Allocation with Flexible Channel Cooperation in Cognitive Radio Networks," in IEEE Transactions on Mobile Computing, Vol. 12, No. 5, pp. 957-970, May 2013.
. M. Dashti, P. Azmi and K. Navaie, "Radio resource allocation for orthogonal frequency division multiple access-based underlay cognitive radio networks utilising weighted ergodic rates," in IET Communications, Vol. 6, No. 16, pp. 2543-2552, 6 November 2012. . V. Asghari and S. Aissa, "Resource Management in SpectrumSharing Cognitive Radio Broadcast Channels: Adaptive Time and Power Allocation," in IEEE Transactions on Communications, Vol.
, No. 5, pp. 1446-1457, May 2011.
. Tiwari, R., & Nema, M. (2019). Privacy Preserving Authentication Approaches over Mobile Ad-Hoc Networks: Rovin Tiwari, Megha Nema. SMART MOVES JOURNAL IJOSCIENCE, 5(8), 11-14.
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Copyright (c) 2020 Sanjay Kumar Khadagade
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