Green cognitive communication approaches
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2018-05-07 https://doi.org/10.14419/ijet.v7i2.26.12523 -
Cognitive Radio, Sharing, UWB, OFDM, Power Spectral Density (PSD) -
Abstract
Generally one of the reasons for global warming is Co2 emission. The rapid growth of wireless communication is the reason for more emission. This creates more health issues, especially children. To reduce the issues, now the wireless communication is tilted towards green communication. Green communication cannot be achieved in single step. In this paper some of techniques are followed to achieve sustainable communication. The main objective of this paper is cognitive radio (CR), which makes use of spectrum in efficient way. In our proposed system, we focused on green cognitive cycle, Cognitive radio-Ultra wide band (CR-UWB) and Cognitive radio-Orthogonal Frequency Division Multiplexing (CR-OFDM). With these above methods we achieved better achievements in terms of efficiency, less time delay, resource utilization and low power for 5G wireless green communication.
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References
[1] Mitola J, M. G. “Cognitive radio: Making software radios more personalâ€, IEEE Personal Communications, 1999.
[2] S. Haykin, “Cognitive radio: Brain-empowered wireless communicationsâ€, IEEE J. Sel. Areas Commun., vol. 23, no. 2, pp. 201–220, Feb.2005.
[3] A. Sharma and C. R.Murthy, “A group testing based spectrum hole search using a simple sub-Nyquist sampling scheme,†in Proc. GLOBECOM, pp. 1526–1531, 2012.
[4] Y. C. Liang, K. C. Chen, G. Y. Li, and P. Mahonen, “Cognitive radio networking and communications: An overviewâ€, IEEE Trans. Veh. Technol., vol. 60, no. 7, pp. 3386–3407, Sep. 2011.
[5] T. Yucek and H. Arslan, “A survey of spectrum sensing algorithms for cognitive radio applicationsâ€,IEEE Commun. Surv.Tuts., vol. 11, no. 1, pp. 116–130, First Quart., 2009.
[6] Y. Zeng, Y. C. Liang, A. T. Hoang, and R. Zhang, “A review on spectrum sensing for cognitive radio: Challenges and solutionsâ€, EURASIP J. Adv.Signal Process., vol. 2010, pp. 381 465-1–381 465-15, Jan. 2010.
[7] E. Axell, G. Leus, E. G. Larsson, and H. V. Poor, “Spectrum sensing for cognitive radio: State-of-the-art and recent advancesâ€, IEEE SignalProcess. Mag., vol. 29, no. 3, pp. 101–116, May 2012.
[8] Trigui, E.; Esseghir, M.; Boulahia, L.M., "Spectrum handoff algorithm for mobile cognitive radio users based on agents' negotiation", Wireless and Mobile Computing, Networking and Communications (WiMob), 2013 IEEE 9th International Conference, vol., no., pp.750, 756, 7-9 Oct. 2013.
[9] Lu Li; YanmingShen; Keqiu Li; Kai Lin, "TPSH: “A Novel Spectrum Handoff Approach Based on Time Estimation in Dynamic spectrum networksâ€," Computational Science and Engineering (CSE), 2011 IEEE 14th International Conference, vol., no., pp.345,350, 24-26 Aug. 2011.
[10] Christian, I; Moh, S.; Ilyong Chung; Jinyi Lee, "Spectrum mobility in cognitive radio networksâ€,Communications Magazine, IEEE, vol.50, no.6, pp.114,121, June 2012 doi:10.1109/MCOM.2012.6211495.
[11] M Matthe, LL Mendes, I Gaspar, N Michailow, D Zhang, G Fettweis, “Multi-user time-reversal STC-GFDMA for future wireless networksâ€,EURASIP J. Wirel. Commun. Netw, 2015, 132 (2015).
[12] M Taherzadeh, H Nikopour, ABayesteh, H Baligh, in Proc. IEEE VTC-Fall. CMA codebook design, (2014).
[13] Mohandass Sundararajan and Umamaheswari Govindaswamy, “Multicarrier Spread Spectrum Modulation Schemes andEfficient FFT Algorithms for Cognitive Radio Systems†Electronics 2014, 3, 419-443; doi: 10.3390/electronics3030419 (2014).
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How to Cite
Devi, M., Thalaimalaichamy, M., Usha, G., T. Panneerselvam, K., Suba, M., & Venkateshkumar, M. (2018). Green cognitive communication approaches. International Journal of Engineering & Technology, 7(2.26), 4-6. https://doi.org/10.14419/ijet.v7i2.26.12523Received date: 2018-05-06
Accepted date: 2018-05-06
Published date: 2018-05-07