Abstract
Wireless networks communicate with each other using radio spectrum bands which are assigned to license owners. Due to the fixed spectrum assignment policy, a large portion of the spectrum stays unused. The aim of cognitive radio is enabling users which do not hold a license to be able to access the spectrum assigned to license owners. In the channel assignment problem, the objective is to assign channels to unlicensed users in order to maximize channel utilization without causing any interference to licensed users. In this study, we propose a hyper-heuristic approach to solve the channel assignment problem in cognitive radio networks. Results show that our approach gives high channel utilization rates by allowing unlicensed users to access the channels owned by licensed users. The results are promising and promote further study.
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Notes
- 1.
The plots for all 72 instances can be seen on the web page at http://web.itu.edu.tr/egazioglu/cr.
References
Haykin, Simon: Cognitive radio: brain-empowered wireless communications. IEEE J. Sel. Areas Commun. 23(2), 201–220 (2005)
Mitola, J., Maguire, G.Q.: Cognitive radio: making software radios more personal. IEEE Pers. Commun. 6(4), 13–18 (1999)
Mitola, J.: Cognitive radio–an integrated agent architecture for software defined radio (2000)
FCC: Notice of proposed rule making and order, et docket no. 03–322 (2003)
Su, W., Matyjas, J.D., Batalama, S.: Active cooperation between primary users and cognitive radio users in heterogeneous ad-hoc networks. IEEE Trans. Signal Process. 60(4), 1796–1805 (2012)
Ahmed, E., Gani, A., Abolfazli, S., Yao, L.J., Khan, S.U.: Channel assignment algorithms in cognitive radio networks: taxonomy, open issues, and challenges. IEEE Commun. Surv. Tutor. (99), 1–1 (2014)
Peter Ross: Hyper-heuristics. In: Search methodologies, pp. 529–556. Springer (2005)
Hoos, H.H., Stützle, T.: Stochastic Local Search: Foundations & applications. Elsevier (2004)
Tragos, E.Z., Zeadally, S., Fragkiadakis, A.G., Siris, V.A.: Spectrum assignment in cognitive radio networks: a comprehensive survey. IEEE Commun. Surv. Tutor. 15(3), 1108–1135 (2013)
Cowling, P., Kendall, G., Soubeiga, E.: A hyperheuristic approach to scheduling a sales summit. In: Practice and Theory of Automated Timetabling III, pp. 176–190. Springer (2001)
Burke, E.K., Hyde, M., Kendall, G., Ochoa, G., Özcan, E., Woodward, J.R.: A classification of hyper-heuristic approaches. In: Handbook of Metaheuristics, pp. 449–468. Springer (2010)
Burke, E., Kendall, G., Newall, J., Hart, E., Ross, P., Schulenburg, S.: Hyper-heuristics: an emerging direction in modern search technology. In: Handbook of Metaheuristics, pp. 457–474. Springer (2003)
Stützle, M.E., Dorigo, T.: Ant colony optimization (2004)
Ergin, F.C., Uyar, A., Yayimli, A.: Investigation of hyper-heuristics for designing survivable virtual topologies in optical wdm networks. In: Applications of Evolutionary Computation, pp. 1–10. Springer (2011)
Eiben, A.E., Smith, J.E.: Introduction to Evolutionary Computing. Springer Science & Business Media (2003)
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Gazioglu, E., Etaner-Uyar, A.S., Canberk, B. (2015). A Novel Hyper-Heuristic Approach for Channel Assignment in Cognitive Radio Networks. In: Matoušek, R. (eds) Mendel 2015. ICSC-MENDEL 2016. Advances in Intelligent Systems and Computing, vol 378. Springer, Cham. https://doi.org/10.1007/978-3-319-19824-8_3
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DOI: https://doi.org/10.1007/978-3-319-19824-8_3
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