Joint Sensing Adaptation and Resource Allocation for Cognitive Radio with Imperfect Sensing

In cognitive radio networks, imperfect spectrum sensing causes harmful interferences or low utilization of unused bands, depending on an access policy of the secondary system. Since these losses have a trade-off relationship, it is hard to decide proper sensing and access policies for the licensed bands. To deal with this problem, we propose a joint algorithm for sensing adaptation and opportunistic resource allocation. The joint optimization problem minimizes the total expected cost of the losses and utilities which are likely generated for the secondary system. To protect the primary system and ensure the secondary system's utility, we employ an average interference threshold constraint and a QoS constraint for the secondary system. Two types of average secondary utilities are considered for the QoS constraint; one is averaged over only transmitted frames and the other is averaged over total frames. Based on energy detection, we derive feasible ranges of sensing threshold to satisfy the constraints. Simulation results show that the proposed scheme dynamically adapts sensing threshold depending on the network environment and minimizes the total cost of the secondary system. In addition, we investigate the performance of the proposed scheme with the two types of the secondary utility.X112625sciescopu