The Automatic Modulation Recognition (AMR) of communication signals is very important for both civil and military communication, especially in the situation of non-cooperative communication or communication confrontation, such as signals identification, electronic confrontation, software radio, military threat analysis, etc. Additionally, the parameter estimation of signals will be a great help in interference suppression, developing improved condition for successful recognition and demodulation.Some of the existing traffic signal modulation recognitionprocessing algorithms each have their own advantages are better atsome signal processing algorithms for the other few studies and Some algorithms is still in the theoretical stage and under the existing communication channels through some special signal processing of less. This review focuses on these issues for some useful especially to try and improve the various algorithms and implementations withcomputer and other hardware to do some research.This paper is focused on the application of pattern recognition in AMR. Several AMR algorithms are discussed which are based on the analysis of statistical characteristics of the modulation parameters, or cluster algorithm, or high order cumulant, or time_frequency domain analysis, such as Wigner_ville Distribution, Wavelet Transform, or character abstraction from spectral correlation of communication signals. Some improved solutions to the above algorithms are proposed. Performance comparisons are provided by simulations which prove the feasibility of the proposed algorithm and point out the corresponding application prerequisites.
Source: http://www.it-paper.com/communications-signals-modulation-of-computer-simulations.html
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