Optimization of Sensing Time in Energy Detector Based Sensing of Cognitive Radio Network

In cognitive radio network, spectrum sensing methods detect the existence of primary users to utilize spectrum holes for secondary users. When it is found that there are no busy primary users then secondary users are allowed to transmit through the spectrum. During the transmission process of secondary users, there may be collision between secondary users. This leads to decrease in the throughput of the samples of secondary users. In this paper, a mathematical expression for collision between samples of secondary users is derived using Poisson distribution. It is found that by optimizing sensing time, the probability of collision can be set below a predefined threshold as well as the throughput of secondary users can be increased under given probability of detection and under different signal-to-noise ratio conditions of the transmitted channels in the cognitive radio network. Optimization of sensing time is done using Human behavior based particle swarm optimization (HBPSO). By doing this, the probability of collision between samples of secondary users is minimized and a high value of system throughput (~90%) is obtained.