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Improved Channel Allocation Scheme for Cognitive Radio Networks
1 Department of Computer Science, Shaheed Zulfikar Ali Bhutto Institute of Science and Technology (Islamabad Campus), Islamabad, 44000, Pakistan
2 Department of Computer Science, Arid Agriculture University (Burewala Campus), Vehari, 61040, Pakistan
3 Department of Software Engineering, Foundation University Islamabad, Islamabad, 44000, Pakistan
4 Department of Computer Engineering, Sungkyul University, Anyang, 430010, South Korea
* Corresponding Author: Sangsoon Lim. Email:
Intelligent Automation & Soft Computing 2021, 27(1), 103-114. https://doi.org/10.32604/iasc.2021.014388
Received 17 September 2020; Accepted 08 November 2020; Issue published 07 January 2021
Abstract
In recent years, wireless channel optimization technologies witnessed tremendous improvements. In this regard, research for developing wireless spectrum for accommodating a wider range of wireless devices increased. This also helped in resolving spectrum scarcity issues. Cognitive Radio (CR) is a type of wireless communication in which a transceiver can intelligently detect which communication channels are being used. To avoid interference, it instantly moves traffic into vacant channels by avoiding the occupied ones. Cognitive Radio (CR) technology showed the potential to deal with the spectrum shortage problem. The spectrum assignment is often considered as a key research challenge in Cognitive Radio Networks (CRNs). In this paper, an evolutionary optimization algorithm is proposed for channel assignment in CRNs. Evolutionary algorithms are inspired by some type of biological evolution technique. In the proposed technology we used Particle Swarm Optimization (PSO). The resulting algorithm is called differential evolution-based particle swarm optimization with the repair process (DEPSO-RP). Moreover, a repair process is introduced to remove conflicts among secondary users (SUs) to increase the spectrum in CRNs. The performance of DEPSO-RP spectrum assignment algorithm has been evaluated by extensive simulations. The proposed spectrum assignment algorithm showed better performance regarding channel assignment in comparison with other existing algorithms in the literature.
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