Selective spectrum sensing and access based on traffic prediction

In cognitive radio (CR) networks, the ability to capture a frequency slot for transmission in a vacant channel has a significant impact on the spectrum efficiency and quality of service (QoS) of a CR user. Important factors include spectrum handoff, transmission rate and delay. This paper proposes a framework for sensing and selecting channels that have the highest probability of appearing idle while reducing the corresponding sensing time. In contrast to previous work, we consider the practical issues encountered by a CR user in a wireless environment, such as discontinuous target frequency bands and limited spectrum sensing ability. We examine the spectrum sensing scheme in terms of packet loss ratio (PLR). The simulation results show that the proposed spectrum sensing strategy can decrease the probability of packet losses in the discontinuous spectrum environment and improve spectrum efficiency.