Triple- Threshold Energy Detection with Adaptive Intermediate Threshold for Cooperative Spectrum Sensing

In cognitive radio (CR) networks, the non-licensed users access dynamically the available resources with the requirement to avoid causing interference for the licensed users. Therefore, the non-licensed or secondary users (SUs) have to use spectrum sensing (SS) algorithms to detect accurately the presence of the signals transmitted by licensed or primary users (PUs). Using a single SU SS can be problematic, especially in urban environments with many large obstacles that can fade or even block the reception of the PU signal. A solution for this is to use cooperative SS algorithms that assume to have more SUs collaborating for increasing the probability to detect the PU signal presence. Another component of the CR network is the fusion center (FC) that collects the individual detection information from SUs and based on this, it takes the final decision about the presence or absence of the PU signal. In this paper, we analyze a cooperative SS algorithm using a triple-threshold energy detection (ED) algorithm in each SU and a simple voting rule for the final decision at the FC node. We also investigate the cooperative SS detection performance dependence on the FC voting rule and an adaptive control mechanism for the intermediate detection threshold in each SU to minimize the global decision error probability (DEP).