Research On The Modulation Classification For Ofdm Signals

Modulation identification for communication signals is a still important problem in the communication signal processing, it is required to identify the modulation format and modulation parameters in the complicated signal environment with noise, and to provide reference for farther analysis and processing. Modulation format is one of the most important characteristics used to distinguish communication signals. After analyzing the received signal, the objective of modulation identification is to decide the modulation format and estimate the modulation parameters of the communication signal without any priori knowledge about the signal information content. With the development of communication technology, the spatial signals are more and more complicated and dense. It results in that output of the receiver doesn't contains only one signal, which makes the modulation identification more difficult, and as results, there comes more demands for the research of modulation identification of communication signals.For the last several decades, researchers explored many methods to solve the problem of the modulation identification for modulation signals, especially the single carrier signal, but the research on multi-carrier signal is very rare. Based on this reason, inter-class and intra-class recognition of OFDM signal is made. Several valuable and important results which bring forth new ideas are achieved and listed as the following: 1. There are fewer papers dealing with the inter-class recognition of OFDM signals. In this paper, algorithms for this problem are produced, which are based on the higher order cumulants and Euclidean distance.2. From papers we know that the algorithm of intra-class recognition for OFDM signal has a very complex computation and its range on the study of modulation type is very narrow. In this paper we improve that algorithm and study covering a wide field from the basic analog signal to digital signal. It is shown by the results that the algorithm is stable with a low complexity and it has a high correct rate to classify the modulation of OFDM signal.