The strategy used for sensing in a cognitive radio network affects the white space that secondary users (SUs) perceive and hence their throughput. For example, let the average time interval between consecutive sensing be fixed as τ. There are several possible ways to achieve this mean value. The SU may sense the channel at equal intervals of length τ or sense it at randomly spaced intervals with mean value τ and guided by, for example, geometric distribution, uniform distribution, etc. In the end the strategy selected does affect the available white space and throughput as well as the resources spent on sensing. In this paper we present a discrete time Markov chain model for cognitive radio network and use it to obtain the efficiency of sensing strategies. The system studied is one in which we have a saturated source of secondary users. These assumptions do not in any ways affect our results.