The invention discloses an unmanned aerial vehicle
base station enhanced network optimization method for a narrow-band
Internet of Things. The method comprises the following steps: the height is optimized when deploying an unmanned aerial vehicle
base station through the
radius of a certain load
base station; the unmanned aerial vehicle base
station covers all congestion networks and paralyzed networks in the load base
station to the maximum extent; then, the deep
Q learning network is applied to optimize the path for deploying the unmanned aerial vehicle base
station, it is ensured that the unmanned aerial vehicle base station can arrive at the designated deployment position in the shortest time, then shunt service is provided for the network or an airspace communication network is established, and therefore the communication
service quality is improved. According to the method, the intelligence of the unmanned aerial vehicle is improved through deep
reinforcement learning, human resources are reduced, the congestion network is optimized, network
paralysis is solved, the communication
service quality of the network is improved, and the purpose of optimizing the network is achieved.