Method and apparatus for modulation recognition of signals based on cyclic residual network

An electronic device, comprising a processor, a communication interface, a memory, and a communication bus, through which the processor, the communication interface and the memory communicate with each other;

• the memory is configured for storing computer programs;
• the processor is configured for performing a method for modulation recognition of signals based on a cyclic residual network when executing the computer programs stored in the memory, the method comprising:
• obtaining a signal matrix of a to-be-recognized signal, and extracting real part information and imaginary part information of the signal matrix;
• wherein, the to-be-recognized signal is a signal whose modulation is to be recognized;
• generating, according to the extracted real part information and the extracted imaginary part information, a real-and-imaginary-part feature matrix of the to-be-recognized signal;
• converting, according to a preset matrix conversion method, the real-and-imaginary-part feature matrix into an amplitude-and-phase feature matrix;
• the amplitude-and-phase feature matrix carries amplitude features and phase features of the to-be-recognized signal, and an amount of information of features carried by the amplitude-and-phase feature matrix varies with an amount of information carried by the to-be-recognized signal;
• and
• inputting the amplitude-and-phase feature matrix into a pre-trained cyclic residual network to obtain a modulation mode corresponding to the to-be-recognized signal;
• wherein the cyclic residual network is obtained by training according to a preset number of sample feature data items of the to-be-recognized signal and a classification label for the sample feature data items;
• the sample feature data items comprise a sample amplitude-and-phase feature matrix;
• and the cyclic residual network comprises:
• a plurality of gated recurrent units (GRU) configured for processing the amplitude-and-phase feature matrix.