Random periodic spectrum sensing with sensing period optimization for cognitive radio networks

A random periodic spectrum sensing scheme is proposed for cognitive radio networks. The sensing period is extended to a general form as a random variable. A generalized Markov analytical model for sensing period optimization is presented, and the optimal sensing period to maximum rewards generated by the channel is derived. Numerical examples show that sensing period does affect the maximum rewards of the channel, and the analytical model is justified by its analytical flexibility since it uses a general sensing period and hence the model can be easily adapted for the analysis of many different applications.