Autosoft Journal

Online Manuscript Access

A Novel Solution to the Cognitive Radio Decision Engine Based on Improved Multi-Objective Artificial Bee Colony Algorithm and Fuzzy Reasoning



Targeting at the parameters reconfiguration of a cognitive radio system, a novel cognitive decision engine (CDE), based on an improved multi-objective artificial bee colony (IMOABC) algorithm and fuzzy reasoning, is proposed. First, a group of Pareto optimal solutions were obtained by applying IMOABC to solve CDE, and an optimal solution that meets user needs was selected by fuzzy reasoning. Such IMOABC algorithm was integrated into society cognitive strategies. New production and preservation mechanisms of individuals and parallel hybrid coding and multi-dimensional evolution strategies are evaluated. The proposed algorithm was evaluated on a set of standard test functions. Combined with the multi-carrier communication system, the simulation experiments are performed for reconfiguring of the physical layer parameters, and the results are able to satisfy user needs.



Total Pages: 9
Pages: 643-651


Manuscript ViewPdf Subscription required to access this document

Obtain access this manuscript in one of the following ways

Already subscribed?

Need information on obtaining a subscription? Personal and institutional subscriptions are available.

Already an author? Have access via email address?


Volume: 23
Issue: 4
Year: 2017

Cite this document


Akbari, Reza et al. "A Multi-Objective Artificial Bee Colony Algorithm." Swarm and Evolutionary Computation 2 (2012): 39-52. Crossref. Web.

Baldo, N., and M. Zorzi. "Fuzzy Logic for Cross-Layer Optimization in Cognitive Radio Networks." IEEE Communications Magazine 46.4 (2008): 64-71. Crossref. Web.

Deb, K. et al. "A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II." IEEE Transactions on Evolutionary Computation 6.2 (2002): 182-197. Crossref. Web.

Gong D. W. Tien Tzu Hsueh Pao/acta Electronica Sinica

Karaboga, Dervis, and Bahriye Basturk. "A Powerful and Efficient Algorithm for Numerical Function Optimization: Artificial Bee Colony (ABC) Algorithm." Journal of Global Optimization 39.3 (2007): 459-471. Crossref. Web.

Karaboga, Dervis et al. "A Comprehensive Survey: Artificial Bee Colony (ABC) Algorithm and Applications." Artificial Intelligence Review 42.1 (2012): 21-57. Crossref. Web.

Kaur, Kiranjot, Munish Rattan, and Manjeet Singh Patterh. "Biogeography-Based Optimisation of Cognitive Radio System." International Journal of Electronics 101.1 (2013): 24-36. Crossref. Web.

Ma, Lianbo et al. "Cooperative Artificial Bee Colony Algorithm for Multi-Objective RFID Network Planning." Journal of Network and Computer Applications 42 (2014): 143-162. Crossref. Web.

Mitola, J., and G.Q. Maguire. "Cognitive Radio: Making Software Radios More Personal." IEEE Personal Communications 6.4 (1999): 13-18. Crossref. Web.

Omkar, S.N. et al. "Artificial Bee Colony (ABC) for Multi-Objective Design Optimization of Composite Structures." Applied Soft Computing 11.1 (2011): 489-499. Crossref. Web.

Pradhan, Pyari Mohan, and Ganapati Panda. "Comparative Performance Analysis of Evolutionary Algorithm Based Parameter Optimization in Cognitive Radio Engine: A Survey." Ad Hoc Networks 17 (2014): 129-146. Crossref. Web.

Rieser C. J. Biologically inspired cognitive radio engine model utilizing distributed genetic algorithms for secure and robust wireless communications and networking

Tizhoosh H. R. Proceedings of International Conference on Computational Intelligence for Modeling Control and Automation

Xue, Yu et al. "A Hybrid Evolutionary Algorithm for Numerical Optimization Problem." Intelligent Automation & Soft Computing 21.4 (2014): 473-490. Crossref. Web.

"Journal of Information and Computational Science." n. pag. Crossref. Web.

"Journal of Information and Computational Science." n. pag. Crossref. Web.

Zhao, Caidan et al. "Performance Analysis of the Multiple Antenna Asynchronous Cognitive MAC Protocol in Cognitive Radio Network for IT Convergence." Intelligent Automation & Soft Computing 20.1 (2014): 61-75. Crossref. Web.

Zhao, Nan, Shuying Li, and Zhilu Wu. "Cognitive Radio Engine Design Based on Ant Colony Optimization." Wireless Personal Communications 65.1 (2011): 15-24. Crossref. Web.


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present


TSI Press
18015 Bullis Hill
San Antonio, TX 78258 USA
PH: 210 479 1022
FAX: 210 479 1048