Performance Evaluation of Cognitive Radio Networks with Imperfect Spectrum Sensing and Bursty Primary User Traffic

In this paper, we introduce a four-dimensional continuous-time Markov chain model to evaluate the performance of cognitive radio networks. In such networks, secondary (unlicensed) users may opportunistically use the frequency channels not currently occupied by primary (licensed) users in order to increase the utilization of the wireless spectrum. Secondary users perform channel sensing before as well as during transmission in order not to interfere with primary users. The proposed model assumes that primary users arrive according to a bursty arrival process and moreover takes the possible occurrence of sensing errors (false alarms and misdetections) into account. Several performance measures including the collision rate between primary and secondary users, the blocking probabilities of primary or secondary users, and the mean delay of secondary users are derived and illustrated through numerical examples. The results show that the system performance strongly depends on the degree of burstiness in the arrival process of primary users. It is also observed that the quality of service of the primary network can be seriously compromised due to misdetection by secondary users.