Dynamic Sensing Strategies for Efficient Spectrum Utilization in Cognitive Radio Networks

For cognitive radio (CR) networks with user hierarchy, the sensing strategy with "listen-before-talk" (LBT) policy plays a key role in spectrum utilization and primary user (PU) protection. However, existing sensing strategies do not handle satisfactorily the randomness of both user locations and channel conditions in the network environment, resulting in inefficient spectrum utilization. To cope with such randomness, this paper develops three dynamic sensing strategies that can adaptively schedule the sensing slots/cycles according to the online link conditions without assuming knowledge of the PU traffic model. The proposed strategies can improve the efficiency of spectrum utilization while being robust with respect to the uncertainty in the PU traffic pattern. To maximize spectrum utilization, the proposed strategies are formulated through closed-form expressions. Efficient methods are introduced to compute the optimal values of the parameters used in the strategies, such as sensing time and sensing threshold. Simulations verify that the proposed sensing strategies offer an evident improvement on the spectrum utilization of the CR network.