FCM based adaptive threshold selection mechanism in spectrum detection

Energy detection is an important method in cognitive radio for secondary users to achieve spectrum detection, where detecting parameter setting is a key problem. However, as the network environment changes, some crucial detection parameters, such as detector threshold, will change as well. Thus it is necessary to obtain detection parameters accurately and timely. To solve this problem, an optimal threshold in energy detection over the additive white Gaussian noise channel is deduced and then an adaptive method is proposed to find the optimal threshold based on fuzzy C-means (FCM). Priori information about signal to noise ratio and the initial threshold is not required in this method. Only clustering according to the similarities and differences of the received energy samples needs to be achieved, and then select the energy samples with the minimum degrees of membership differences as the optimal threshold. Matlab simulation results show that the proposed mechanism has a good degree of fitting with the deduced optimal detector threshold over the additive white Gaussian noise channel. © 2015, Chinese Institute of Electronics. All right reserved.