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Communication signal modulation recognition computer simulation

Author: WangGuoQiang
Tutor: YuFan；YangJianGuang
School: Xi'an University of Technology
Course: Computer technology
Keywords: Modulation Recognition Pattern Recognition Feature Extraction Parameter Estimation
CLC: TN911.7
Type: Master's thesis
Year: 2011
Downloads: 129
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Abstract


Communication signal modulation type automatic recognition is widely used in civil communications and military communications, especially for non-cooperative communications, communications countermeasures, such as signal confirmation, electronic countermeasures, software radio, military threat analysis. Especially in popular software radio based on the current design of digital circuit module theory prevalent in the context of signal processing becomes more important, for the wideband signal processing book recognition technology of communication signals digital signal processing is the key to good communication signals Modulation identification method is the digital signal processing step, the correct identification signal modulation and demodulation of the signal filter base, in addition, important parameters estimation signal, the interference can be better removed, in order to further identify and demodulate correctly create the conditions. Some of the existing communication signal modulation recognition processing algorithms have advantages tend to be more adept at handling some signal for some algorithm or some algorithms fewer still in the theoretical stage and under the existing communication channel through some special signal processing few studies, and then, or some combination of algorithms and hardware deficiencies not suitable for computer technology in the present communication applications. This review focuses on these issues for some useful attempts and improvements especially for various algorithms combined with computers and other hardware implementations do some research. The topics to pattern recognition in the communication signal modulation recognition as the main line, respectively, for different domains based algorithms are discussed and a useful improvement, the instantaneous signal modulation parameters discussed the statistical characteristics, applications and clustering algorithm The Wigner-ville distribution of the signal, wavelet transform, spectral correlation characteristics embodied in the classification, in addition to a brief discussion of PSK signal has the cumulant features and feature extraction algorithm based on the above combined with the corresponding identification scheme to identify different modulated signals. The article also for the practical application of the algorithm proposed defects corresponding improvement program, through the combination of theory and simulation, comparative analysis of the advantages and disadvantages of various algorithms and the corresponding recognition environment. As for the clustering algorithm into the improved adaptive clustering algorithm presented so that it can better adapt to the computer for signal processing algorithm is proposed to improve the DBSCAN adaptive DBSCAN algorithm proposed and applied to the baseband signal constellation diagram weight structure, for the wavelet transform algorithm proposed in the case is closer to the actual symbol waveform generated improvements associated with the existing power spectrum based on the signal modulation recognition algorithm is too large for its hardware implementation difficulties into useful improvements related to the power spectrum is proposed based blind identification algorithm and for us in the time-frequency domain analysis Shibu Chang using the Wigner-ville distribution based on the method of calculation to try and summarizing.

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Communicate > Communication theory > Signal processing
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