A non-periodic sensing strategy for improved throughput in cognitive radio networks

This paper deals with a smart sensing strategy in an overlay cognitive radio network, to effectively exploit secondary-user (SU) transmitting opportunities, while preserving primary-user (PU) interference. Specifically, we consider a non-periodic sensing policy characterized by different transmitting and silence periods, and we derive closed-form expressions for the average SU throughput and interference in AWGN and fading channels, assuming a Poisson alternating renewal process for the PU traffic. Our analysis, confirmed by computer simulations, shows that the proposed strategy can increase the throughput with respect to a classical periodic sensing policy. Furthermore, optimal transmitting and silence periods can be identified for a given sensing time, trading off throughput for PU interference.