Coalition formation based malicious user detection scheme in cognitive radio networks

In cognitive radio networks, a critical issue is to exploit the spectrum holes based on spectrum sensing while avoiding interference to the primary users. However, the reliability of sensing is uncertain. In order to increase the probability to access the channel, cognitive users may report false detection results and become malicious users (MUs), which could significantly degrade the performance of spectrum sensing. In this paper, we proposed an energy efficient MUs detection algorithm which is able to perform coalition-based cooperative detection and spatial correlation with Geary´C theory to maximize the probability of MUs detection. The problem is reformulated as a coalition game with the theoretical certification of its stability. Simulation results show that our algorithm is able to achieve a significant improvement while saving the energy in the MUs detection process compared with other algorithms in the literature.