Performance analysis of spectrum sensing with mobile SUs in cognitive radio networks

Spectrum sensing is a critical component for cognitive radio networks. Most of the spectrum sensing algorithms and performance analysis, however, assume that the secondary users are stationary. In this paper, we investigate the performance analysis of spectrum sensing by mobile secondary users. Two performance metrics, false alarm probability and miss detection probability, are thoroughly investigated. In addition, a new performance metric, expected transmission time, is designed to factor the secondary users´ mobility. The random waypoint based mobility model is adopted for secondary users. For spectrum sensing by mobile secondary users, a critical variable is the distance between the primary user and mobile secondary users. We mathematically model this distance, and derive its probability distribution. At last, the expressions are derived for all three performance metrics, the false alarm probability, the miss detection probability, and the expected transmission time. Extensive simulations are performed, and the results are consistent with the theoretical analysis. It is concluded that the mobility of secondary users has significant impact on miss detection probability, but not on false alarm probability.