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인지무선통신 환경에서 슬롯-알로하 기법의 전송 효율 분석

Throughput Analysis of Slotted ALOHA in Cognitive Radios

  • Wang, Hanho (Dept. of Information & Communication Engineering, Sangmyung University) ;
  • Woo, Choongchae (Dept. of Electrical Engineering, Hanseo University)
  • 투고 : 2014.09.04
  • 심사 : 2014.12.18
  • 발행 : 2015.03.01

초록

In cognitive radios, exponentially distributed idle period(EIP) is considered in this paper. In the EIP case, durations of idle periods are be limited and varied by primary traffic arrivals. Accordingly, we first analyze the idle period utilization which can be achieved by the slotted ALOHA in cognitive radio communications. The idle period utilization is a newly defined performance metric to measure the transmission performance of the secondary network as effective time durations utilized for successful secondary transmissions in an idle period. Then, the idle period utilization is maximized through controlling the data transmission time. All technical processes are mathematically analyzed and expressed as closed form solutions.

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참고문헌

  1. Federal Communications Commission, "Spectrum policy task force report, (ET Docket No. 02-135)," Nov. 2002. [Online.] Available: hraunfoss.fcc.gov/edocs_public/attachmatch/DOC-228542A1.pdf.
  2. X. Huang, G. Wang, F. Hu, "Multitask Spectrum Sensing in Cognitive Radio Networks via Spatiotemporal Data Mining," IEEE Trans. Veh. Technol., vol. 62, no.2, pp. 809-823, Feb. 2013. https://doi.org/10.1109/TVT.2012.2223767
  3. A. S. Kannan, E. M. Manuel, "Performance analysis of blind spectrum sensing in cooperative environment," Control Communication and Computing (ICCC), 2013, pp. 277-280, Aug. 2013.
  4. H. Wang, G. Noh, D. Kim, S. Kim, and D. Hong, "Advanced sensing techniques of energy detection in cognitive radios, " Journal of Communications and Networks, vol. 12, no. 1, pp. 19-29, Feb. 2010. https://doi.org/10.1109/JCN.2010.6388431
  5. Q. Chen, W. Wong, M. Motani, Y. C. Liang, "MAC Protocol Design and Performance Analysis for Random Access Cognitive Radio Networks," IEEE Journal on Selected Areas in Communications, vol. 31, no. 11, pp. 2289-2300, Nov. 2013. https://doi.org/10.1109/JSAC.2013.131121
  6. M. E. Bayrakdar, S. Atmaca, A. Karahan, "A slotted ALOHA-Based random access cognitive radio network with capture effect in Rayleigh fading channels,", International Conference on Electronics, Computer and Computation (ICECCO), 2013, pp. 72-75, Oct. 2013.
  7. V. Gungor, D.Sahin, "Cognitive Radio Networks for Smart Grid Applications: A Promising Technology to Overcome Spectrum Inefficiency," IEEE Vehicular Technology Magazine, vol. 7, no. 2, pp. 41-46, Jun. 2012. https://doi.org/10.1109/MVT.2012.2190183
  8. S. Geirhofer, L. Tong and B. M. Sadler, "Cognitive radios for dynamic spectrum access in time domain: modeling and exploiting white space," IEEE Commun. Mag., vol. 45, no. 5, pp. 66-72, May 2007. https://doi.org/10.1109/MCOM.2007.358851
  9. A. Papoulis and S. U. Pillai, Probability, Random Variables and Stochastic Process, McGraw-Hill, 2002.
  10. Robert M. Corless, G. H. Gonnet, D. E. G. Hare, D. J. Jeffrey; D. E. Knuth, "On the Lambert W function," Advances in Computational Mathematics, Vol.5, 1996, Page(s):329-359 https://doi.org/10.1007/BF02124750