Periodic Spectrum Sensing with Non-Continuous Primary User Transmissions

In this paper we present a thorough study of spectrum sensing performance in cognitive radio (CR) scenarios where the primary user (PU) transmission is not continuous. In particular, we consider a sensing scheme in which the spectrum is monitored periodically for a fraction of time. In such a situation, sensing is affected by common detection impairments, including noise and fading, as well as by the PU temporal behavior. It is thus necessary to properly design periodic sensing parameters to balance between sensing overhead and detection performance. In this context, we derive a comprehensive analytical framework which accounts for detector performance, presence of noise and fading, PU temporal statistics, and periodic sensing. The analysis allows expression of the detection and false alarm probabilities in closed-forms to capture an explicit relationship between the PU temporal statistic and periodic sensing parameters. Our results show that the temporal behavior of the PU have a significant impact on the detection performance, and therefore a proper design of the sensing parameters is important. Based on our analysis we propose useful strategies for the design of effective periodic sensing.