Automatic Modulation Recognition Of Digital Communication Signals

Modulation format is one of the most important characteristics used to distinguish communication signals. In many applications, it is required to monitor the activities of these signals, identify their characteristics, even to intercept the signal information content. So modulation identification for communication signals becomes a still important problem in the intercepted signal processing.The objective of modulation identification is to decide the modulation format and estimate the modulation parameters of the communication signals without any priori knowledge about the signal information content in the complicated signal environment with noise after analyzing the received signal, and to provide reference for farther analysis and processing. With the development of communication technology, the spatial signals are more and more complicated and dense. As results, there comes more demands for the research of modulation identification of communication signals.In near these decades, researchers explored many methods to solve the problem of the modulation identification for different modulation signals. This dissertation makes a study on the modulation identification of communication signals. It introduces the methods of how to extract characteristics of signals and how to design classifiers.At first, the wavelet transformation theory is introduced in this paper. Wavelet transform has good characteristics of localizing time and frequency and multi-resolution performance, it is also an effective technique for extracting the transient characteristics from different digital modulation signals without any prior knowledge. The wavelet transformations of four kinds of different digital communication signals are deduced theoretically and the modulation identifier is constructed based on the transformation results. The inter-class and infra-class modulation type classification is investigated i two kinds of signal-to-noise ratio environments.Then, according to the theory analysis, a digital modulation identification method based on the neural network is designed. The structure and training algorithm of MLP network is discussed in detail in this paper. The experimental results are satisfying, which are gained in different SNR conditions. These results reflect the capability and performance of both methods. This thesis summarizes their advantages and disadvantages.This thesis makes helpful researches on modulation recognition of communication signals. In the future, much work needs to be done in this field..