针对复杂、时变信道下单个深度神经网络接收机计算复杂度高、空间资源需求大

Aiming at the problems of high computational complexity, large space resource requirements, and inability to achieve adaptive transmission for a single deep neural network receiver under complex and time-varying channels, an unmanned network based on Long Short Term Memory (Long Short Term Memory) network is studied. The method of aircraft channel state classification, and the design and simulation of the UAV data adaptive transmission system.

In view of the complexity, the computational complexity of a single deep neural network receiver under a time-change channel, the demand for space resources and the inability to adaptive transmission are studied, a classification method of the state of the drone channel based on the Long Short Term Memory network is studied, and the design and simulation of the adaptive transmission system of the drone data is carried out.

Aiming at the problems of high computational complexity, large space resource requirement and unable to achieve adaptive transmission of single deep neural network receiver in complex and time-varying channels, a channel state classification method for UAV Based on long short term memory network is studied, and the design and Simulation of UAV data adaptive transmission system are carried out.