Share This Article:

Optimization of QoS Parameters in Cognitive Radio Using Combination of Two Crossover Methods in Genetic Algorithm

Abstract Full-Text HTML XML Download Download as PDF (Size:74KB) PP. 478-483
DOI: 10.4236/ijcns.2013.611050    3,375 Downloads   5,199 Views   Citations


Radio Cognitive (RC) is the new concept introduced to improve spectrum utilization in wireless communication and present important research field to resolve the spectrum scarcity problem. The powerful ability of CR to change and adapt its transmit parameters according to environmental sensed parameters, makes CR as the leading technology to manage spectrum allocation and respond to QoS provisioning. In this paper, we assume that the radio environment has been sensed and that the SU specifies QoS requirements of the wireless application. We use genetic algorithm (GA) and propose crossover method called Combined Single-Heuristic Crossover. The weighted sum multi-objective approach is used to combine performance objectives functions discussed in this paper and BER approximate formula is considered.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

A. Elarfaoui and N. Elalami, "Optimization of QoS Parameters in Cognitive Radio Using Combination of Two Crossover Methods in Genetic Algorithm," International Journal of Communications, Network and System Sciences, Vol. 6 No. 11, 2013, pp. 478-483. doi: 10.4236/ijcns.2013.611050.


[1] D. Cabric, S. M. Mishra and R. Brodersen, “Implementation Issues Inspectrum Sensing for Cognitive Radios,” Proceedings of 38th Asilomar Conferences on Signals, Systems and Computers, Pacific Grove, 7-10 November 2004, pp. 772-776.
[2] Federal Communications Commission, “Spectrum Policy Task Force,” Report of ET Docket 02-135, 2002.
[3] I. F. Akyildiz, W. Y. Lee, M. C. Vuran and S. Mohanty, “NeXt Generationdynamic Spectrum Access Cognitive Radio Wireless Networks: A Survey,” Computer Networks, Vol. 50, No. 13, 2006, pp. 2127-2159
[4] T. R. Newman, R. Rajbanshi, A. M. Wyglinski, J. B. Evans and G. J. Minden, “Population Adaptationfor Genetic Algorithm-Based Cognitive Radios,” IEEE Proceedings of Cognitive Radio Oriented Wireless Networks and Communications, Orlando, 1-3 August 2007, pp. 279-284.
[5] M. J. Kaur, M. Uddin and H. K. Verma, “Optimization of QoS Parameters in Cognitive Radio Using Adaptive Genetic Algorithm,” International Journal of Next-Generation Networks (IJNGN), Vol. 4, No. 2, 2012, 15 Pages.
[6] J. Mitola III., “Software Radios: Survey, Critical Evaluation and Future Directions,” Aerospace and Electronic Systems Magazine (IEEE), Vol. 8, No. 4, 1993, pp. 25-36.
[7] L. Doyle, “Essentials of Cognitive Radio,” Cambridge University Press, New York, 2009.
[8] V. Blaschke, T. Renk and F. K. Jondral, “A Cognitive Radio Receiver Supporting Wide-BandSensing,” IEEE International Conference on Communications Workshops, Beijing, 19-23 May 2008, pp. 499 503.
[9] J. G. Proakis, “Digital Communications,” 4th Edition, McGraw-Hill, Boston, 2000.
[10] S. T. Chung and A. J. Goldsmith, “Degrees of Freedom in Adaptive Modulation: A Unified View,” IEEE Transactions on Communications, Vol. 49, No. 9, 2001, pp. 15611571.
[11] D. E. Goldberg, “Genetic Algorithms in Search, Optimization & Machine Learning,” Addison Wesley, Boston, 1989.
[12] T. P. Hoehn and C. C. Pettey, “Parental and Cyclic-Rate Mutation in Genetic Algorithms: An Initial Investigation,” Proceedings of Genetic and Evolutionary Computation Conference, Orlando, 1999, pp. 297-304.
[13] J. H. Holland, “Adaptation in Natural and Artificial Systems,” University of Michigan Press, Ann Arbor, 1975.
[14] F. Herrera, M. Lozano and A. M. Sánchez, “A Taxonomy for the Crossover Operator for Real-Coded Genetic Algorithms. An Experimental Study,” International Journal of Intelligent Systems, Vol. 18, No. 3, 2003, pp. 309-338.
[15] G. F. Luger, “Atrificial Intelligence: Structures & Strategies for Complex Problem Solving,” 4th Edition, Addison-Wesley, Boston, 2002, 856 Pages.
[16] M. Negnevitsky, “Artificial Intelligence: A Guide to Intelligent Systems,” Addison-Wesley, Boston, 2002, 394 Pages.

comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.