The invention provides a
signal shielding method based on deep
reinforcement learning, and belongs to the technical field of
artificial intelligence and communication crossing. The method comprises the steps that S1, a large number of historical
wireless communication signals are acquired to construct a
data set to
train a
signal interference strategy generation model; s2, deploying the
signal interference strategy generation model to a signal shielding device; s3, verifying and analyzing the signal shielding instruction to obtain a shielding parameter, collecting a real-time
wireless communication signal, and inputting the real-time
wireless communication signal and the shielding parameter into a deployed
signal interference strategy generation model to obtain a real-
time signal interference strategy; and S4, the signal shielding device modulates the real-time interference signal based on the real-
time signal interference strategy, and the power
amplifier performs power amplification on the real-time interference signal and then transmits the real-time interference signal to the outside through the
radio frequency antenna so as to perform signal shielding. The method has the advantages that the accuracy, the real-time performance and the expansibility of signal shielding are greatly improved, and the
power consumption of signal shielding is reduced.