DOUBLE THRESHOLD SPECTRUM SENSING WITH OPTIMIZATION OF SAMPLESIN COGNITIVE RADIO NETWORKS

In cognitive radio networks spectrum sensing playsa vital role to identify the presence or absence of the primary user. In conventional spectrum sensing one secondary user will makea final decision regarding the availability of licensed spectrum. But Secondary user fail to make a correct detection about thepresence of the primary user if he is in fading environmentand it causes interference to the licensed users. Therefore toavoid interference to the licensed users and to make correct detection, number of samples is increased, Which increases the probability of detection. In this paper the optimization of samplesis proposed to reduce the system overhead and also to increase the propagation time. Simulation results show the optimized value of samples for a given probability of false alarm and also the variation of probability of detection with optimized samples and false alarm is shown in the results.