State-based probabilistic spectrum sensing in Cognitive Radio Networks

Abstract

Cognitive Radio networks (CRNs) implement dynamic spectrum sensing and management techniques to address the underutilization of limited available spectrum in wireless networks. Both dynamic and opportunistic spectrum sensing techniques are frequently used by the cognitive radios (CRs) to identify the spectral holes in licensed spectrum of the primary users (PUs) and allocate these bands to the unlicensed secondary users (SUs). In this paper we have presented a state-based probabilistic sensing model for primary and secondary user nodes to access the communication channel. Simulations are performed to measure the uniform and cumulative distribution functions the degree of the primary nodes, and channel accessing probabilities for the secondary nodes.