Performance Metrics in Cognitive Radio Networks

Abstract

In Cognitive Radio Networks (CRN), the main aim is to allow the secondary users (SUs) to identify the empty bands and use them to transmit or receive data opportunistically. Primary users (PUs) have the priority to use a channel, while the secondary users must vacant this channel once a primary user requests it. An attack known in cognitive radio networks as a Primary User Emulation Attack (PUEA) aims to prevent the SU from using the empty bands. In this paper, an analytical and experimental approach is presented to mitigate the PUEA. This approach is based on obtaining the Probability Density Functions (PDFs) of the received powers at the secondary users from malicious nodes and also from the primary transmitter in the cognitive network. Then, these obtained PDFs are used in Neyman-Pearson composite hypothesis test to measure the performance metrics (probability of false alarm and miss detection in the network). The results proved that the performance metrics were greatly influenced by the network area, where the secondary user is located, and the threshold value λ used in the decision rule. Also, there are boundaries for the λ choices that cannot be overtaken.