Many studies have been done in cognitive radios to maximize the network efficiency. There is always a trade-off between sensing and transmission time which has been addressed fully in the literature. There is also some missed idle times during the waiting phase when secondary user finds the channel busy. Therefore, the longer the transmission time is, the higher the successfully delivered bits would be and the higher the missed idle times in the waiting stage would be expected. In this work, we formulate these missed idle times to addressed this trade-off. Furthermore, interference due to PU re-occupancy is modelled in successful transmitted time and in collision probability. Moreover, we derive secondary user’s packet delay distribution using phase type model at which retransmission due to collision results from both sensing error and PU re-occupancy is considered. Thanks to derived delay distribution, any statistical moments of delay could be found as a closed form mathematical expression. These moments can be used as constraints for applications with delay sensitive packets. Numerical results are given to clarify the network metrics. Finally, the optimized values for sensing and transmission time are computed using genetic algorithm in order to maximize access efficiency. Many studies have been done in cognitive radios to maximize the network efficiency. There is always a trade-off between sensing and transmission time which has been addressed fully in the literature. There is also some missed idle times during the waiting phase when secondary user finds the channel busy. Therefore, the longer the transmission the time is, the higher the successfully delivered bits is be the higher the missed idle times in the waiting stage would be expected. In this work, we formulate these missed idle times to addressed this trade -off. Furthermore, interference due to PU re-occupancy is modeled in successful transmitted time and in collision probability. Moreover, we derive secondary user’s packet delay distribution using phase type model at which retransmission due to collision results from both sensing error and PU re Thanks to derived delay distribution, any statistical moments of delay could be found as a closed form mathematical expre ssion. These moments can be used as constraints for applications with delay sensitive packets. Finally, the optimized values ​​for sensing and transmission time are computed using genetic algorithm in order to maximize access efficiency.