Share This Article:

Enhanced Spectrum Utilization for Existing Cellular Technologies Based on Genetic Algorithm in Preview of Cognitive Radio

Abstract Full-Text HTML Download Download as PDF (Size:529KB) PP. 917-926
DOI: 10.4236/ijcns.2009.29107    4,502 Downloads   8,485 Views   Citations

ABSTRACT

This paper attempts to find out the distributed server-based dynamic spectrum allocation (DSA) within liberalized spectrum sharing regulation concept as an alternative to existing regulation based on fixed frequency spectrum allocation schemes towards development of cognitive radio for coverage-based analogy. The present study investigates a scenario where a block of spectrum is shared among four different kinds of exemplary air interface standards i.e., GSM, CDMA, UMTS and WiMAX. It is assumed to offer traffic in an equally likely manner, which occupy four different sizes of channel bandwidths for different air interfaces from a common pooled spectrum. Four different approaches for spectrum pooling at the instance of spectrum crunch in the designated block are considered, viz. channel occupancy through random search, existing regulation based on fixed spectrum allocation (FSA), FSA random and channel occupancy through Genetic Algorithm (GA) based optimized mechanism to achieve desired grade of service (GoS). The comparisons of all the approaches are presented in this paper for different air interfaces which shows up to 55% improvement in GoS for all types of air interfaces with GA-based approach in comparison to existing regulations.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

K. SRIDHARA, A. NAYAK, V. SINGH and P. DALELA, "Enhanced Spectrum Utilization for Existing Cellular Technologies Based on Genetic Algorithm in Preview of Cognitive Radio," International Journal of Communications, Network and System Sciences, Vol. 2 No. 9, 2009, pp. 917-926. doi: 10.4236/ijcns.2009.29107.

References

[1] M. P. Olivieri, G. Barnett, A. Lackpour, A. Davis, and P. Ngo, “A scalable dynamic spectrum allocation system with interference mitigation for teams of spectrally agile software defined radios,” New Frontiers in Dynamic Spectrum Access Networks, pp. 170–179, November 2005.
[2] J. Mitola III, “Cognitive radio an integrated agent architecture for software defined radio,” Dissertation, Doctor of Technology, Royal Institute of Technology (KTH), Sweden, May 2000.
[3] Paul Burns, “Software defined radio for 3G,” Artech House, Inc., 2003.
[4] J. Hwang and H. Yoon, “Dynamic spectrum management policy for cognitive radio: An analysis of implementation feasibility issues,” New Frontiers in Dynamic Spectrum Access Networks, 3rd IEEE Symposium, Digital Object Identifier, pp. 1–9, October 2008.
[5] S. Haykin, “Cognitive radio: Brain-Empowered wireless communications,” IEEE Journal on Selected Areas in Communications, Vol. 23, No. 2, February 2005.
[6] Bruce A. Fette., editor, “Cognitive radio technology,” Elsevier Inc., 2006.
[7] S. Almeida, J. Queijo, and L. M. Correia, “Spatial and temporal traffic distribution models for GSM,” Vehicular Technology Conference, Vol. 1, pp. 131–135, September 1999.
[8] A. Y. Zomaya, Senior Member, IEEE, and Michael Wright, “Observations on using genetic-algorithms for channel allocation in mobile computing,” IEEE Transactions on Parallel and Distributed Systems, Vol. 13, No. 9, September 2002.
[9] S. S. M. Patra, K. Roy, S. Banerjee, and D. P. Vidyarthi, “Improved genetic algorithm for channel allocation with channel borrowing in mobile computing,” IEEE Transactions on Mobile Computing, Vol. 5, No. 7, July 2006.
[10] M. Melanie, “An introduction to genetic algorithm,” MIT press, Cambridge, 1999.
[11] D. Maldonado, B. Le, A. Hugine, T. W. Rondeau, and C. W. Bostian, “Cognitive radio applications to dynamic spectrum allocation: A discussion and an illustrative example,” New Frontiers in Dynamic Spectrum Access Networks, First IEEE International Symposium, pp. 597–600, November 2005.
[12] P. Leaves, S. Ghaheri-Niri, R. Tafazolli, L. Christodoulides, T. Sammut, W. Staht, and J. Huschke, “Dynamic spectrum allocation in a multi-radio environment: Concept and algorithm,” 3G Mobile Communication Technologies, Second International Conference on (Conference Publication No. 477), pp. 53–57, March, 2001.
[13] J. Zhao, H. T. Zheng, and G. H. Yang, “Distributed coordination in dynamic spectrum allocation networks,” New Frontiers in Dynamic Spectrum Access Networks, pp. 259–268, November 2005.
[14] Viswanathan and Thiagarajan, “Telecommunication switch- ing systems and networks,” Prentice-Hall, New Delhi, 1992.
[15] D. Thilakawardana, K.Moessner, and R.Tafazolli, “Darwinian approach for dynamic spectrum allocation in next generation systems,” IET Communications, Centre for Communication Systems Research, University of Surrey, Guildford, UK, 2008.

  
comments powered by Disqus

Copyright © 2019 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.