Genetic spectrum assignment model with constraints in cognitive radio networks

Автор: Fang Ye, Rui Yang, Yibing Li

Журнал: International Journal of Computer Network and Information Security(IJCNIS) @ijcnis

Статья в выпуске: 4 vol.3, 2011 года.

Бесплатный доступ

The interference constraints of genetic spectrum assignment model in cognitive radio networks are analyzed in this paper. An improved genetic spectrum assignment model is proposed. The population of genetic algorithm is divided into two sets, the feasible spectrum assignment strategies and the randomly updated spectrum assignment strategies. The penalty function is added to the utility function to achieve the spectrum assignment strategy that satisfies the interference constraints and has better fitness. The proposed method is applicable in both the genetic spectrum assignment model and the quantum genetic spectrum assignment mode. It can ensure the randomness of partial chromosomes in the population to some extent, and reduce the computational complexity caused by the constraints-free procedure after the update of population. Simulation results show that the proposed method can achieve better performance than the conventional genetic spectrum assignment model and quantum genetic spectrum assignment model

Еще

Cognitive radio, spectrum assignment, genetic algorithm, interference constraints, penalty function

Короткий адрес: https://sciup.org/15011030

IDR: 15011030

Список литературы Genetic spectrum assignment model with constraints in cognitive radio networks

  • S. Haykin, “Cognitive radio: Brain-empowered wireless communications,” IEEE Journal on Selected Areas in Communications, vol. 23 no.2, pp.201-220, February 2005.
  • B. A. Fette, Cognitive radio technology. Newnes, USA, 2006.
  • W. Wang, X. Liu, “List-coloring based channel allocation for open-spectrum wireless networks,” Vehicular Technology Conference, pp. 690-694, September 2005.
  • C. Peng, H. Zheng, B. Zhao, “Utilization and fairness in spectrum assignment for opportunistic spectrum access,” Mobile Networks and Applications, vol.11, no. 4, pp. 555-576, August 2006.
  • Y. Li, R. Yang, Z. Gao, “List-coloring based spectrum access in cognitive radio networks,” Systems Engineering and Electronics, vol.32, no.6, pp. 1109-1112, June 2010
  • C. J. Rieser, T. W. Rondeau, C. W. Bostian, Gallagher, T. M. Gallagher, “Cognitive radio testbed: Further details and testing of a distributed genetic algorithm based cognitive engine for programmable radios,” IEEE Military Communications Conference, vol.3, pp. 1437-1443, October 2004.
  • T. W. Rondeau, B. Le, D. Maldonado, D. Scaperoth, , C. W. Bostian, “Cognitive radios with genetic algorithms: intelligent control of software defined radios,” SDR Forum Technical Conference,May 2004.
  • T. R. Newman, R. Rajbanshi, A. M. Wyglinski, J. B. Evans; G. J. Minden, “Population adaptation for genetic algorithm-based cognitive radios,” International Conference on Cognitive Radio Oriented Wireless Networks and Communications, June 2008.
  • Z. Zhao, S. Zheng, J. Shang, X. Kong, “A study of cognitive radio decision engine based on quantum genetic algorithm,” ACTA PHYSICA SINICA, vol.56, no.11, pp. 6760-6766, November 2007.
  • Z. Zhao, Z. Peng, S. Zheng, X. Xu, C. Lou, X. Yang, “Cognitive radio spectrum assignment based on quantum genetic algorithm,” Acta Physica Sinica, vol.58, no.2, 1358-1363, February 2009.
  • Z. Zhao, Z. Peng, S. Zheng, J. Shang, “Cognitive radio spectrum allocation using evolutionary algorithms,” IEEE Transactions on Wireless Communications, vol.8, no.9 pp. 4421-4425,September 2009.
  • C. Jiao, K. Wang, “Cognitive radio decision engine based on immune genetic algorithm,” System Engineering and Electronics, vol.32, no.5, pp.1084-1087, M ay 2010.
  • J. Zhou, X. Zu, “A parallel immune genetic algorithm in adaptive resource allocation for cognitive radio network,” ACTA PHYSICA SINICA, vol.59, no.10, pp. 7508-7515, October 2010.
  • S. Chen, A. M. Wyglinski, “Cognitive radio-enabled distributed cross-layer optimization via genetic algorithms,” 4th International Conference on Cognitive Radio Oriented Wireless Networks and Communications, 2009.
  • S. Chen, A. M. Wyglinski, “Efficient spectrum utilization via cross-layer optimization in distributed cognitive radio networks,” Computer Communications, vol.32, no.18, pp.1931-1943, October 2009.
  • S. Chen, T. R. Newman, J. B Evans, A. M. Wyglinski, “Genetic algorithm-based optimization for cognitive radio networks,” 33rd IEEE Sarnoff Symposium, 2010.
  • P. Chen, Q. Zhang, Y. Wang, J. Meng, “Multi-objective resources allocation for OFDM-based cognitive radio systems,” Information Technology Journal, vol.9, no.2, pp. 494-499, 2010.
Еще
Статья научная