Login



Other Articles by Author(s)

Elhachmi Jamal



Author(s) and WSEAS

Elhachmi Jamal


WSEAS Transactions on Communications


Print ISSN: 1109-2742
E-ISSN: 2224-2864

Volume 16, 2017

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.



Dynamic Spectrum Allocation in Cognitive Radio Cellular Networks

AUTHORS: Elhachmi Jamal

Download as PDF

ABSTRACT: last years, Cognitive radio (CR) has emerged as an efficient technology to exploit the unused available spectrum resources; it can sense and use spectrum in an opportunistic manner without creating any harm to cognitive users. In this article a cognitive spectrum allocation procedure is proposed. Artificial Neural network (ANN) an intelligent learning technique is used which works to improving wireless communication for cognitive radio mobile terminal, to reduce the optimization complexity and improve the decision quality. The criteria for the spectrum allocation problem had been analyzed and the common objectives to solve it have been determinate. Evaluation results show that our technique achieved significant allocations in large and complex wireless communication system. Results also show the improvement in the user satisfaction over other techniques in CR.

KEYWORDS: Cognitive radio, spectrum allocation, wireless communications, neural network.

REFERENCES:

[1] Akyildiz, I.F., B.F. Lo and R. Balakrishnan, 2011. “Cooperative Spectrum Sensing in Cognitive Radio Networks:A Survey Physical Communication” (Elsevier) Journal, 4: 40-62.

[2] J. Mitola, G. Maguire, “Cognitive radio: making software radios more personal”, IEEE Personal Communications, vol. 6, no. 4, pp. 13- 18,Aug.1999.

[3] Amraoui, A., Benmammar, B., Bendimerad, “F.T.: Accès Dynamique au Spectre dans le Contexte de la Radio Cognitive”. In: 2ième édition de la conférence nationale de l’informatique (JEESI 2012), ESI, Oued-Smar (Alger), Algérie (Avril 2012).

[4] S. Haykin, “Cognitive radio: brain-empowered wireless communications,” IEEE Journal on Selected Areas in Communications, vol. 23, no. 2, pp. 201-220, Feb. 2005.

[5] Po-Kai Tseng, Wei-Ho Chung, Pi-Cheng Hsiu, “Minimum Interference Topology Construction for Robust multi-hop cognitive radio networks”. WCNC 2013: 101-105.

[6] J. Neel, (2006) “Analysis and Design of Cognitive Radio Networks and Distributed Radio Resource Management Algorithms”, Faculty of the Virginia Polytechnic Institute and State University.

[7] Zheng, J., C.H. Chen, J.Y. Cheng, S. Lei, 2009. “Cognitive radio: methods for the detection of free bands”. International Conference on Networks Security, Wireless Communications and Trusted Computing. IEEE. 2: 343-345.

[8] Atiq Ahmed, M.Mubashir Hassan, Osama Sohaib, Walayat Hussain and M.Qasim Khan, ”An Agent Based Architecture for Cognitive Spectrum Management” Australian Journal of Basic and Applied Sciences, 5(12): 682-689, 2011 ISSN 1991-8178.

[9] J.Elhachmi and Z.Guenoun, “Distributed Frequency Assignment Using hierarchical Cooperative Multi-agent System”, Int. J. Communications, Network and System Sciences, Vol.4 No.11, 2011 , PP.727-734.

[10] S. Huang, X. Liu, and Z. Ding, “ Optimal Transmission Strategies for Dynamic Spectrum Access in Cognitive Radio Networks ”, Mobile Computing, IEEE Transactions on 8 (12), 1636-1648

[11] Q. Zhao, L. Tong, A. Swami, and Y. Chen, “Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework,” IEEE Journal on Selected Areas in Communications (JSAC): Special Issue on Adaptive, Spectrum Agile and Cognitive Wireless Networks, vol. 25, no. 3, pp. 589–600, 2007.

[12] Y. Chen, Q. Zhao, and A. Swami, “Joint design and separation principle for opportunistic spectrum access in the presence of sensing errors,” IEEE Transactions on Information Theory, vol. 54, no. 5, pp. 2053–2071, 2008.

[13] A. Mishra, S. Banerjee, and W. Arbaugh. Weighted coloring based channel assignment for WLANs. Mobile Computing and Communications Review (MC2R), 9(3), 2005.

[14] N. Nie and C. Comaniciu. Adaptive channel allocation spectrum etiquette for cognitive radio networks. In Proceedings of IEEE Dynamic Spectrum Access Networks (DySPAN’05), Baltimore, USA, Nov. 2005.

[15] 21]- J. O. Neel, J. H. Reed, and R.P. Gilles. Convergence of cognitive radio networks. In Proceedings of Wireless Communications and Networking Conference (WCNC’04), Atlanta, USA, Mar. 2004.

[16] L. Cao and H. Zheng. Distributed spectrum allocation via local bargaining. In Proceedings of IEEE SECON’05), Santa Clara, California, USA, Sep. 26-29 2005.

[17] M. Felegyhazi, M. Cagalj, J. P. Hubaux, « Efficient MAC in Cognitive Radio Networks: A Game-Theoretic Approach », Transactions on Wireless Communications (TWC), , vol. 8, no. 4, April , 2009.

[18] S. Gandhi, C. Buragohain, L. Cao, H. Zheng, and S. Suri, “A general framework for wireless spectrum auctions,” the 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), pp. 22–33, 2007.

[19] D. Cabric, A. Tkachenko, and R. W. Brodersen, “Experimental study of spectrum sensing based on energy detection and network cooperation,” in Proc. First International Workshop on Technology and Policy in Accessing Spectrum (TAPAS). New York, NY, USA: ACM Press, 2006.

[20] H. Zheng and L. Cao. Device-centric spectrum management. In Proceedings of IEEE DySPAN’05), Baltimore, USA, Nov. 8-11 2005.

[21] A. Amraoui, B. Benmammar, F. Krief, FT. Bendimerad. 'Intelligent Wireless Communication System Using Cognitive Radio'. IJDPS International Journal of Distributed and Parallel Systems. Vol.3, No.2, March 2012. pp: 91-104.

[22] R.Deka, S.Chakraborty,J.Sekhar Roy, “ OPTIMIZATION OF SPECTRUM SENSING IN COGNITIVE RADIO USING GENETIC ALGORITHM “, Ser: Elec. Energ, Vol. 25, No 3, pp. 235 – 243, December 2012.

[23] M. Kaur and M. Uddin, 'Optimization of QoS Parameters in Cognitive Radio Using Adaptive Genetic Algorithm,' International Journal of Next-Generation Networks (IJNGN), vol. 4, no. 2, pp. 1-15, 2012.

[24] T. Siddique and A. Azam, 'Spectrum Optimization in Cognitive Radio Networks Using Genetic algorithms,' Blenkinge Institute of Technology, Sweden, 2010.

[25] E. hossain, D. Niyan, Zhu Han, “Dynamic Spectrum Access and management in cognitive radio networks”, Cambridge University Press 2009.

[26] C. R. Aguayo Gonzales, et al, “Design and Implementation of an Open-Source SoftwareDefined Cognitive Radio Testbed”, submitted to IEEE Journal on Selected Areas of Communication (J-SAC).

[27] W. Wang, X. Liu, and H. Xiao, “Exploring Opportunistic Spectrum Availability in Wireless Communication Networks,” Proc. IEEE Vehicular Technology Conf. (VTC), Sept. 2005.

[28] R.Vaidya,T.Giang, D.Terzopoulos: ' NEATRacing :An Evolutionary Neural Network Implementation”, UCLA June 2008, CS 275 Artificial Life.

[29] J.ELHACHMI and Z. GUENNOUN, « Merging gradual neural networks and Genetic algorithm for Dynamic Channel Assignment Problem”. Mediterranean Telecommunication Journal vol.2, n°1,pp. 14-19. Janvier 2012.

[30] E. Adamopoulou, K. Demestichas and M Theologou,'Enhanced Estimation of Configuration Capabilities in Cognitive Radio,' IEEE Communications Magazine, 46(4):pp. 56-63, 2008.

WSEAS Transactions on Communications, ISSN / E-ISSN: 1109-2742 / 2224-2864, Volume 16, 2017, Art. #41, pp. 362-369


Copyright © 2017 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

Bulletin Board

Currently:

The editorial board is accepting papers.


WSEAS Main Site