Channel Allocation Scheme Based on Greedy Algorithm in Cognitive Vehicular Networks

With the steep increase in the number of vehicle users, the demand for channel resources is increasing. However, the limited spectrum resources can't meet this huge demands. Using cognitive radio (CR) technology in vehicular networks can effective solve this problem. In this paper, we study the channel allocation in the cognitive vehicular network (CVN), and we established a corresponding network model, channel model, service model and vehicle model for highway scenarios in CVN. In order to solve the problem of channel allocation, we proposed a Channel Allocation Scheme based on Greedy Algorithm (CASGA), which is aimed at maximize the throughput of the CVN. The proposed scheme is compared with a traditional game theory algorithm in the optimization of throughput. Simulation results show that the proposed scheme has a great advantage over traditional game theory algorithm in optimizing the throughput of the CVN.