Cooperative Cognitive Intelligence for Internet of Vehicles

To resolve the contradictions between the increasing demand of vehicular wireless applications and the shortage of spectrum resources, high mobility, short link lifetime, and spectrum efficiency, a novel cognitive radio (CR) and efficient management of spectrum in vehicular communication is required. Therefore, to exhibit the importance of spectral efficiency, a system model is proposed for cooperative centralized and distributed spectrum sensing in vehicular networks. The proposed architecture is used to minimize both the spectral scarcity and high mobility issues. Furthermore, we analyze the decision fusion techniques in cooperative spectrum sensing for vehicular networks. In addition, a system model is designed for decision fusion techniques using renewal theory, and then, we analyze the probability of detection of primary channel and the average waiting time for CR user or secondary user in PU transmitter. Finally, mathematical analysis is performed to check the probability of detection and false alarm. The results show that the cooperative cognitive model is more suitable for vehicular networks that minimize interference and hidden PU problem.