Adaptive joint scheduling of spectrum sensing and data transmission in cognitive radio networks

We consider a cognitive radio (CR) network that makes opportunistic use of a set of channels licensed to a primary network. During operation, the CR network is required to carry out spectrum sensing to detect active primary users, thereby avoiding interfering with them. However, spectrum sensing may cause negative effect on the performance of the CR network, as all CR communications has to be postponed during channel sensing. This paper focuses on adaptively scheduling spectrum sensing and data transmission so that negative impacts to the performance of the CR network are minimized. We first consider the case when CR nodes always have data to transmit and experience time-varying channels. Based on knowledge of channel conditions, the sensing periods are adaptively scheduled to maximize the spectrum efficiency of the CR operation. We show how optimal sensing/transmission scheduling policies can be obtained and prove some important structural properties of such optimal policies. We then consider the case when CR nodes experience both stochastic data arrival and time-varying channels. By treating each sensing period as a ´virtual sensing packet´´, we convert the problem of joint spectrum-sensing/datatransmission scheduling into a standard queueing model. Based on that, an efficient scheduling algorithm that takes into account channel and queue conditions of the CR network is proposed.