Abstract
This paper represents a scheme for solving the problem that is faced by the Secondary Users for channel switching in Cognitive Radio networks. In this work, an efficient proactive channel selection and switching framework called Best Fit Channel Switching (BFCS) is proposed to minimize the amount of channel switching overhead for SUs between different channels. Based on channel usage information of PU and application specific parameters, One State Transition Probability (OSTP) and Two State Transition Probability (TSTP) are calculated. Then with the help of OSTP and TSTP a list of best channels for switching is obtained. Thus the proposed scheme enables the SUs to proactively predict the future spectrum availability status and switch to the best channel for communication when any PU arrives amidst of its current transmission. The proposed method is compared with the existing methods to evaluate its performance for parameters like channel switching cost.
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