Channel Quality Estimation in 3D Drone Base Station for Future Wireless Network

Due to its agility, high maneuverability, and cost-effective features, drone base stations (DBSs) are expected to be a key component of the next-generation wireless communication platforms. In this paper, we propose an adaptive and accurate air-to-ground (A2G) wireless channel quality based on long short-term memory (LSTM) in a 3D aerial base station deployment. The proposed method can achieve 95.71% link quality estimation (LQE) accuracy. Thus, the proposed system can provide promising and reasonable LQE in a dynamic and complex drone-aided wireless communication environment.