DBSCAN-based Vehicle Clustering and UAV Placement for NOMA-based Resource Management in Cellular V2X Communications

In the future wireless networks, terrestrial, aerial, space, and maritime wireless networks are integrated into a unified network to meet the needs of a fully connected global network. Nowadays, vehicular communication has become one of the challenging applications of wireless networks. In this article, we aim to address the radio resource management in Cellular V2X (C-V2X) networks using Unmanned Aerial Vehicles (UAV) and Non-orthogonal multiple access (NOMA). The goal of this problem is to maximize the spectral efficiency of vehicular users in Cellular Vehicle-to-Everything (C-V2X) networks under a fronthaul constraint. To solve this problem, a two-stage approach is utilized. In the first stage, vehicles in dense area are clustered based on their geographical locations, predicted location of vehicles, and speeds. Then UAVs are deployed to serve the clusters. In the second stage, NOMA groups are formed within each cluster and radio resources are allocated to vehicles based on NOMA groups. An optimization problem is formulated and a suboptimal method is used to solve it. The performance of the proposed method is evaluated through simulations where results demonstrate superiority of proposed method in spectral efficiency, min point, and distance.