Research on Channel Feedback Algorithm in UAV Inspection Communication Subsystem of Smart Grid

With the rapid development of smart grids, inspection and maintenance of power equipment is essential. The large bandwidth, high reliability and low latency communication of 5G technology can meet the needs of drone inspections. However, the environment of the transmission line corridor is complex and changeable. During the UAV inspection, the channel environment and the channel transmission coefficient between the UAV and the base station change in real time. In order to ensure the reliability and effectiveness of communication, the UAV terminal needs to estimate and track the changed channel transmission coefficient in real time, and feed it back to the base station. Based on the Massive-MIMO millimeter wave drone communication scenario, this paper constructs the channel model of the drone terminal and the base station in this scenario and solves the estimation, trackingand and feedback of the channel state information in this scenario by fusing deep learning algorithms problem.