AoA based sensing and performance analysis in cognitive radio networks

In the traditional research on spectrum sensing in cognitive radio networks, a channel is determined occupied by a primary user (PU) once a signal is detected, but this is not always true. There is a fair likelihood that the channel is being used by a secondary user (SU). To accurately reflect the channel status, it is significant to distinguish whether a signal from a PU or an SU on a busy channel. In this paper, we propose an Angle of Arrival (AoA) based sensing approach using the smart antenna technology. Specifically, an SU is equipped with a smart antenna and hence is capable of distinguishing the arrival angles from all incoming signals. Therefore, if the angle/direction information of the target PU is provided in advance, an SU is able to determine that a received signal is from the PU or other users by analyzing the incoming angles. We select the CAPON AoA algorithm as an example to demonstrate the effectiveness. Further, we comprehensively investigate the sensing performance including false alarm probability and miss detection probability, which has received limited attention. Extensive simulations are conducted and results demonstrate the effectiveness of the AoA based spectrum sensing approach. The limitation of this approach is pointed out as well.