Affiliations: [a] Department of Computer Science, University of Zululand, Kwadlangezwa, South Africa
| [b] Department of Electrical Engineering/F’SATI, Tshwane University of Technology, Pretoria, South Africa
Correspondence:
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Corresponding author. Olukayode A. Oki, Department of Computer Science, University of Zululand, X1001, Kwadlangezwa 3886, South Africa. Tel.: +27 784859979/+123825880; E-mails: okikayode@gmail.com; olwalto@tut.ac.za.
Abstract: Spectrum decision is the capability of Secondary Users to choose the best accessible spectrum band to satisfy a user’s Quality of Service (QoS) requirements. Spectrum decision comprises three primary functions; spectrum characterization, spectrum selection and dynamic reconfiguration of cognitive radio. The study of dynamic reconfiguration of transceiver parameters in spectrum decision making has been motivated because of its importance to the realization of efficient spectrum utilization and management in distributed mobile cognitive radio networks. Spectrum decision making in a distributed cognitive radio network is crucial, so as to ensure that an appropriate frequency and channel bandwidth are selected to meet the QoS requirements of different types of applications and to maintain the spectrum quality. In attempting to address the issue of dynamic reconfiguration of transceiver parameters in decision making for cognitive radio networks, different approaches can be found in the literature. However, due to some of the challenges associated with these approaches such as high computational complexity, ambiguity, non-repeatability and non-deplorability of these classical approaches, researchers are still trying to explore other techniques that will be less ambiguous, more efficient, more understandable and easier to deploy in a highly dynamic environment like distributed cognitive radio networks. Hence, this paper reviews the existing approaches, identifies the challenges and proposes a biologically inspired optimal foraging approach to address the decision making problem and other problems relating to the existing approaches.
