Sensing parameter optimization using a new detection probability in cognitive radio networks

Sensing-throughput tradeoff (or MAC-layer sensing optimization) issues have been widely investigated in cognitive radio networks while considering the protection of primary signals in the sense of detection probability. However, the detection probability that is defined during each sensing time does not fully capture primary protection goal, because neither the detection latency until the primary signal is detected nor the unavoidable misdetection event during sensing operation are considered. Motivated by these problems, we propose a new detection probability of so-called tolerable interference time-based detection probability and investigate the effect of the sensing interval on the detection probability. Based on the new detection probability, the optimal sensing parameters in terms of sensing time and sensing interval, which not only satisfy the constraint for protection of primary signals but also achieve the maximum throughput for secondary users, are derived. Numerical analyses show the relationship between sensing interval and the new detection probability, and the optimal sensing parameters.