Probability-based model for unlicensed spectrum utilization in cognitive radio networks

In cognitive Radio Networks (CRNs), to utilize the available opportunities on the primary spectrum effectively; secondary transmitters should have a prior knowledge about the number of primary channels that are predicted to be available and hence the periods of time the secondary users can maintain the channel(s) to efficiently schedule their data while satisfying the constrains of the delivered application. More importantly, such an efficient utilization can improve the network performance and reduce the collisions and interference between CRN users. In this paper, we use the probability of obtaining an idle set of primary channels to model the probability of holding the available PUs channel(s) for a period of time adequate to deliver the scheduled data for a specific secondary user. The PUs channels are assumed to independently follow the two-state Markov Model in changing their availability state. We consider different cases for the activity levels of primary users over CRN channels and compare the approximated availability distribution in each case against the exact one using extensive MATLAB simulations for validation. These models are then employed to obtain the desired channel(s) holding probability for two cases of secondary users existence in a CRN.