Cognitive unmanned aerial vehicle channel optimization method and system based on reinforcement learning

The invention provides a cognitive unmanned aerial vehicle channel optimization method and system based on reinforcement learning, and relates to the field of unmanned aerial vehicle network optimization. The optimization method comprises the following steps: establishing a cognitive radio network by taking a user directly served by a ground base station as a main user and taking an unmanned aerial vehicle serving an edge user by an air base station as a secondary user; and detecting the load state of the current ground base station: if detecting that the current ground base station is overloaded, further listing user positions and user channels in the current predetermined communication area, taking users at the edge of the communication area and users in unfavorable channels as optimization target users, and executing network optimization service on the optimization target users. According to the cognitive unmanned aerial vehicle channel optimization method provided by the invention, the service quality of