Communication Signal Modulation Recognition Based on Time-Frequency Domain Analysis and Bayesian optimized Decision Tree Algorithm

Communication signal modulation mode recognition technology plays a crucial role in communication confrontation in the modern war environment. Due to the low accuracy of the traditional communication signal recognition methods, this paper introduces a method to identify modulation modes of communication signals based on a Bayesian optimized decision tree. In this paper, a modulation mode recognition method of communication signals based on Bayesian optimization and decision tree is proposed. First, simulate the signals of different modulation modes, including frequency-shift keying modulation (FSK), frequency modulation (FM), amplitude modulation (AM). Then the signal data is processed by using the time and frequency domain feature extraction algorithm. Next, the obtained data is used to train and verify the decision tree. And the model parameters are optimized by the Bayesian method. The recognition of these three communication modulation signals is realized, and the accuracy is up to 94%.