한국통신학회논문지 (The Journal of Korean Institute of Communications and Information Sciences)

한국통신학회 (The Korean Institute of Commucations and Information Sciences)
권호 표지
DOI QR코드

DOI QR Code

동적 스펙트럼 접근을 위한 유전자 알고리즘 기반 전송 매개변수 최적화 기법

A Transmission Parameter Optimization Scheme Based on Genetic Algorithm for Dynamic Spectrum Access

  • 채근홍 (성균관대학교 정보통신대학) ;
  • 윤석호 (성균관대학교 정보통신대학)
  • 투고 : 2013.10.07
  • 심사 : 2013.11.05
  • 발행 : 2013.11.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 논문에서는 동적 스펙트럼 접근을 위한 유전자 알고리즘 기반 전송 매개변수 최적화 기법을 제안한다. 구체적으로는 전송 매개변수 최적화를 위해 다목적 적합도 함수를 단일 목적 적합도 함수들의 가중합으로 표현하고, 유전자 알고리즘을 이용하여 주어진 전송 시나리오에 최적화된 전송 매개변수 값을 얻는다. 모의실험을 통하여 제안한 다목적 적합도 함수를 이용하여 주어진 시나리오에 따라 전송 매개변수를 최적화한 결과를 보인다.

In this paper, we propose a transmission parameter optimization scheme based on genetic algorithm for dynamic spectrum access systems. Specifically, we represent a multiple objective fitness function as a weighted sum of single objective fitness functions to optimize transmission parameters, and then, obtain optimized transmission parameters based on genetic algorithm for given transmission scenarios. From numerical results, we confirm that the transmission parameters are well optimized by using the proposed optimization scheme.

키워드

참고문헌

  1. P. Yadav, S. Chatterjee, and P. P. Bhattacharya, "A survey on dynamic spectrum access techniques in cognitive radio," Int. J. Next-Generation Networks, vol. 4, no. 4, pp. 27-46, Dec. 2012. https://doi.org/10.5121/ijngn.2012.4403
  2. T. Yüech and H. Arslan, "A survey of specturm sensing algorithms for cognitive radio applications," IEEE Commun. Surveys and Tutorials, vol. 11, no. 1, pp. 116-127, Mar. 2009. https://doi.org/10.1109/SURV.2009.090109
  3. D. Xu, L. Ying, and W. S. Qun, "Design and implementation of a cognitive engine functional architecture," Chinese Sci. Bulletin, vol. 57, no. 28-29, pp. 3698-3704, Oct. 2009.
  4. B. Park, J. Han, Y. Choi, M. Cho, and H. Park, "Radio network optimization in the homogeneous traffic distribution using genetic algorithm," J. Korean Inst. Commun. Sci. (KICS), vol. 27, no. 2B, pp. 137-144, Feb. 2002.
  5. C. J. Rieser, "Biologically inspired cognitive radio engine model utilizing distributed genetic algorithms for secure and robust wireless communications and networking," Ph.D. dissertation, Virginia Polytechnic Inst. State Univ., Blacksburg, U.S.A., Aug. 2004.
  6. T. Rondeau, B. Le, C. J. Rieser, and C. W. Bostian, "Cognitive radio with genetic algorithms: Intelligent control of software defined radios," in Proc. Software Defined Radio Forum Tech. Conf., pp. C3-C8, Phoenix, U.S.A., Nov. 2004.
  7. D. Maldonado, B. Le, A. Hugine, T. W. Rondeau, and C. W. Bostian, "Cognitive radio applications to dynamic spectrum allocation," in Proc. IEEE Int. Symp. New Frontiers Dynamic Spectrum Access Networks, pp. 597-600, Baltimore, U.S.A., Nov. 2005.
  8. T. R. Newman, B. A. Barker, A. M. Wyglinski, A. Agah, and J. B. Evans, "Cognitive engine implementation for wireless multicarrier transceivers," Wireless Commun. Mobile Comput., vol. 7, no. 9, pp. 1129-1142, May 2007. https://doi.org/10.1002/wcm.486
  9. C. Ahn, R. S. Ramakrishna, and C. Kang, "A new genetic algorithm for shortest path routing problem," J. Korean Inst. Commun. Sci. (KICS), vol. 27, no. 12C, pp. 1215-1227, Dec. 2002.
  10. H. Urkowitz, "Energy detection of unknown deterministic signals," Proc. IEEE, vol. 55, no. 4, pp. 523-531, Apr. 1967. https://doi.org/10.1109/PROC.1967.5573