Abstract Unmanned Aerial Vehicles (UAVs) enabled Aerial Base Stations (UABSs) have been studied widely in future communications. However, there are a series of challenges such as interference management, trajectory design and resource allocation in the scenarios of multi-UAV networks. Besides, different performances among UABSs increase complexity and bring many challenges. In this paper, the joint downlink transmission power control and trajectory design problem in multi-type UABSs communication network is investigated. In order to satisfy the signal to interference plus noise power ratio of users, each UABS needs to adjust its position and transmission power. Based on the interactions among multiple communication links, a non-cooperative Mean-Field-Type Game (MFTG) is proposed to model the joint optimization problem. Then, a Nash equilibrium solution is solved by two steps: first, the users in the given area are clustered to get the initial deployment of the UABSs; second, the Mean-Field Q (MFQ)-learning algorithm is proposed to solve the discrete MFTG problem. Finally, the effectiveness of the approach is verified through the simulations, which simplifies the solution process and effectively reduces the energy consumption of each UABS.