A Primary Traffic Aware Opportunistic Spectrum Sensing for Cognitive Radio Networks

Spectrum sensing is adopted to detect the presence of primary users in cognitive radio networks. Considering the sensing overhead, it is not always a good choice that the secondary user senses the channel all the time. In this paper, we propose an opportunistic spectrum sensing decision method according to the primary user's traffic. First, the traffic of primary user is observed and estimated. For estimating the parameters of the primary traffic, the Maximum Likelihood estimation is adopted and the confidence interval is calculated based on finite observed samples. Then, according to the estimated primary traffic information, a decision criterion is proposed for determining whether to sense the channel. The simulation results show that the performance of the proposed opportunistic sensing scheme is much better than that when sensing at every timeslots and very close to that in the ideal case in which the primary traffic information is obtained perfectly.