Performance Analysis of Multi-Layer Urban Air Mobility Networks With Directional Antennas Based on Poisson Line Process

Urban Air Mobility (UAM) utilizes aerial aircraft to solve urban transportation challenges, which is expected to become an important application scenario of low-altitude intelligent networking. Reliable communication performance is important to ensure the flight safety and efficiency of aircraft. However, there is currently a lack of a more realistic modeling and analysis method for UAM networks. In this paper, we propose a new performance analysis framework to analyze the coverage performance of UAM networks served by ground base stations (BSs). The route is modeled as a Poisson Line Process (PLP) and the aircraft along the route are modeled as a one-dimensional (1D) Poisson Point Process (PPP). In order to improve the coverage performance, we equip the ground BSs with directional antenna. Based on the modeling, we derive the expression of distance distribution, assoication probability, the Laplace transform of interference power and coverage probability. Besides, machine learning is combined to determine optimal antenna beamwidth maximinzing the coverage probability, which has a guiding role in the deployment of UAM networks.