Outage probability minimization for vehicular networks via joint clustering, UAV trajectory optimization and power allocation

In this paper, we consider the vehicular uplink communication scenario where vehicles in the same lane travel in a direction within the coverage of the base station. Due to the long communication distance and poor signal quality at the cell edge, an unmanned aerial vehicle (UAV) is used as a mobile relay to improve the communication quality. Our goal is to minimize the communication outage probability by jointing vehicle clustering with UAV trajectory optimization and power allocation of each node. Since the cluster head position, UAV position and power of each node are coupled, the primary complex problem is divided into three sub-problems namely vehicle clustering, trajectory optimization and power allocation. Firstly, the improved K-means clustering algorithm is used for vehicle clustering by addressing the minimum-maximum distance criterion. In order to adapt to the changing network topology, the cluster head vehicle is determined dynamically. Then the joint Lagrangian gradient ascent method is used to determine the UAV position and the power of each vehicle through alternate iterations. The simulation results show that the proposed joint optimization scheme (J-CTOPA) is better than the equal power scheme with fixed relay position (FR-EP) and the power allocation scheme with cruise relay trajectories (CT-PA). The results also show that faster convergence and stronger stability can be achieved while the outage probability is reduced.