Genetic Algorithm Based QoS Aware Adaptive Subcarrier Allocation in Cognitive Radio Networks

Dipak P. Patil; Vishal A. Wankhede; Vijay M. Wadhai

doi:10.4236/wet.2015.64009

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Wireless Engineering and Technology > Vol.6 No.4, October 2015

Genetic Algorithm Based QoS Aware Adaptive Subcarrier Allocation in Cognitive Radio Networks ()

Dipak P. Patil, Vishal A. Wankhede, Vijay M. Wadhai

Sant Gadge Baba Amravati University, Amravat, India.

DOI: 10.4236/wet.2015.64009 PDF HTML XML 3,965 Downloads 4,510 Views Citations

Abstract

In this paper, an adaptive subcarrier allocation scheme with reconfiguration of operating parameters for Cognitive Radio Networks (CRN) is presented. A QoS-conscious spectrum decision frame work is projected, where spectrum bands are determined by considering the application requirements as well as the dynamic nature of the spectrum bands. The novel subcarrier allocation algorithm is developed to fulfill different performance objective as a solution for subcarrier allocation and power allocation problem for Cognitive Radio (CR) users in CRNs. It employs operating frequency parameter modification using Proportional Resource Algorithm and Genetic Algorithm (GA). The multi objective optimization problem with equality and inequality constraint is considered. Moreover, a dynamic subcarrier allocations scheme is developed based on GA to decide on the spectrum bands adaptively dependent on the time-varying CR network capacity. The proposed algorithm targets to achieve maximum data rate for each subcarrier, maximize the overall network throughput and maximize the number of satisfied user under the constraints of bandwidth and guarantee Quality of Service (QoS) requirement from dynamic spectrum management (DSM) perspective. Moreover, it determines the best available channel.

Keywords

Cognitive Radio, Genetic Algorithm, QoS, Subcarrier Allocation

Share and Cite:

Patil, D. , Wankhede, V. and Wadhai, V. (2015) Genetic Algorithm Based QoS Aware Adaptive Subcarrier Allocation in Cognitive Radio Networks. Wireless Engineering and Technology, 6, 87-97. doi: 10.4236/wet.2015.64009.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Federal Communications Commission (2002) Spectrum Policy Task Force Report. ET Docket No. 02-135, November.
[2]	Mitola, J. and Maguire, G.Q. (1999) Cognitive Radio: Making Software Radios More Personal. IEEE Personal Communications Magazine, 6, 6-13. http://dx.doi.org/10.1109/98.788210
[3]	Akyildiz, I.F. (2011) Cooperative Spectrum Sensing in Cognitive Radio Networks: A Survey. Physical Communication, 4, 40-62. http://dx.doi.org/10.1016/j.phycom.2010.12.003
[4]	Nie, C.C. (2005) Adaptive Channel Allocation Spectrum Etiquette for Cognitive Radio Networks. IEEE DySPAN, Baltimore, 8-11 November 2005, 269-278. http://dx.doi.org/10.1109/dyspan.2005.1542643
[5]	Zheng, H. and Cao, L. (2005) Device-Centric Spectrum Management. IEEE DySPAN, 56-65.
[6]	Hoang, A.T. and Liang, Y.-C. (2006) Maximizing Spectrum Utilization of Cognitive Radio Networks Using Channel Allocation and Power Control. IEEE 64th Vehicular Technology Conference, Montreal, 25-28 September 2006, 1-5. http://dx.doi.org/10.1109/vtcf.2006.257
[7]	Zhang, L., Liang, Y.-C. and Xin, Y. (2007) Joint Admission Control and Power Allocation for Cognitive Radio Networks. IEEE International Conference on Acoustics, Speech and Signal Processing, Honolulu, 15-20 April 2007, III-673-III-676.
[8]	Farah, J. and Marx, F. (2007) Combining Strategies for the Optimization of Resource Allocation in a Wireless Multiuser OFDM System. International Journal on Electronics Communication, 61, 665-677. http://dx.doi.org/10.1016/j.aeue.2007.01.002
[9]	Yang, L., Cao, L. and Zheng, H. (2008) Proactive Channel Access in Dynamic Spectrum Networks. Physical Communication, 1, 103-111. http://dx.doi.org/10.1016/j.phycom.2008.05.001
[10]	Marko, H., Sofie, P. and Aarne, M. (2008) Performance Improvement with Predictive Channel Selection for Cognitive Radios. IEEE CogART Workshop, 1-5.
[11]	Wood, M.K. and Dantzig, G.B. (1949) Programming of Interdependent Activities: I, General Discussion. Econometrica, 17, 193-199. http://dx.doi.org/10.2307/1905522
[12]	Dantzig, G.B. (1949) Programming of Interdependent Activities: II, Mathematical Model. Econometrica, 17, 200-211. http://dx.doi.org/10.2307/1905523
[13]	Qin, H., Su, J. and Du, Y. (2009) Multiobjective Evolutionary Optimization Algorithm for Cognitive Radio Networks. IEEE IEEC, Ternopil, 16-17 May 2009, 164-168. http://dx.doi.org/10.1109/ieec.2009.39
[14]	Gardner, W. and Brown, W. (1987) Spectral Correlation of Modulated Signal. Part I—Analog Modulation. IEEE Transactions on Communications, COM-35, 584-594. http://dx.doi.org/10.1109/TCOM.1987.1096820
[15]	Wang, P., Fang, J., Hang, N. and Lee, H. (2010) Multiantenna-Assisted Spectrum Sensing for Cognitive Radio. IEEE Transactions on Vehicular Technology, 59, 1791-1800. http://dx.doi.org/10.1109/TVT.2009.2037912