Automatic recognition of communication signal modulation based on neural network

Abstract

In order to solve the problem of low modulation recognition rate of digital communication signals and the difficulty of selecting the appropriate decision threshold, the paper features a recognition method for communication signal modulation. The paper constructs characteristic parameters for recognizing signals in the cyclic frequency domain, and uses a 3-layer neural network as a classifier to identify the modulation mode. The experiment indicates that it can recognize 2FSK, 4FSK, 8FSK, BPSK, QPSK, MSK and 2ASK When signal to noise ratio (SNR) is higher than 0 dB, the recognition rate achieves 95%. The results suggest that recognition of communication signal modulation based on neural network is accurate and feasible.