Dissertation > Excellent graduate degree dissertation topics show

Modulation Recognition of Digital Communication Signals in Multipath Channels

Author: YinChangYi
Tutor: LiBingBing
School: Xi'an University of Electronic Science and Technology
Course: Communication and Information System
Keywords: Modulation Recognition Cyclic Spectrum Characteristic quantities Correlation coefficient RBF Neural Network
CLC: TN911.3
Type: Master's thesis
Year: 2011
Downloads: 109
Quote: 1
Read: Download Dissertation

Abstract


With the rapid development of communication technology , communication system and modulation of the signal is becoming increasingly diversified , are becoming increasingly complex communications environment , so that makes communication signal modulation recognition becomes more difficult . Most of the existing methods are based communication environment for ideal conditions , the white Gaussian noise interference or multipath interference under the impact . So far in the low signal-to-noise ratio , multipath interference environment modulation recognition technology is still hot and difficult in the field . Gaussian white noise multipath channel under this article presents a recognition method based on the modulation of the signal cyclic spectrum . The method first set in the loop spectral domain experience gate limit to reduce the impact of noise on the feature amount , and then use the spectral properties of the signal cycle , by solving the correlation coefficient under the cyclic spectrum certain frequencies and cycle frequency as a feature amount to overcome multipath interference , extracted six anti-multipath interference characteristic quantities . Theoretical analysis and simulation experiments illustrate these characteristic quantities to eliminate the impact of multipath channel parameters , is an effective , stable signal modulation recognition feature value . Finally, we proposed an improved genetic algorithm to the feature set of the digital signal modulation recognition , merit-based selection , screening the characteristic quantities combination best suited to be identified signal set from the amount of extracted six features . The method makes use of selection and elimination excellent changes in population size adaptively adjust the crossover and mutation probability identification signal to select to be the optimal combination of characteristic quantities . Finally threshold hard-decision tree classifier and RBF neural network classifier to identify the results demonstrate the feasibility and effectiveness of the method under the multipath channel , low signal-to-noise ratio conditions .

Related Dissertations

  1. Study on Risk Identification and Evaluation of Manufacturing Green Products R & D,F205;F224
  2. SAR image can be matched study,TN957.52
  3. AC Drive Sliding Control Algorithm,TP273
  4. Based on RBF artificial neural network in the application of PCB drilling process,TN405
  5. Networked Control System Fault Diagnosis and Fault Tolerant Control,TP273
  6. Linear guide system Elevator single electromagnetic levitation RBF neural network sliding mode control,TP273
  7. Optimization algorithm based on artificial intelligence Melt Index Prediction Modeling Optimization,TQ325.14
  8. Image registration based on the rotation angle calculation methods sand,TP391.41
  9. Robust and adaptive unmanned helicopter Tolerant Control Technology,V249.1
  10. Ballistic midcourse target polarization characteristics and feature extraction studies,TN953
  11. The Influence Analysis of Shandong Three Industrial Structure Evolution Exerting on Employment Structure,F249.27
  12. The Detection and Parameters Estimation of Dsss Signals Based on Correlation and Cyclic Spectrum Method,TN914.42
  13. Research on Feature Extraction Algorithm and Dataset Construction Technology in Membrane Protein Classification,Q51
  14. Turn-off angle optimization of switched reluctance motor control strategy based on the opening of,TM352
  15. EEG-EMG Synergistic Analysis and Correlation Study Based on External-Source Load Inspiration,R87
  16. Based on a class of complex industrial process control of the steady-state optimization,TP183
  17. Study on intrusion detection method of ultrasonic echo envelope characteristics,TP274.53
  18. Research and Application for the Grating Subdividing of Moire Fringes Based on the Neural Network,TP274
  19. Research of Computer Control System in the Ndfeb Hydrogen Crushing Process,TP273.5
  20. Study of Recognition for Hand-drawn Elec-tronic Component Symbnol Based on Radia Ba-sis Function Neural Networks,TP391.41
  21. Research and Application on the Software Process Measurement Based on Statistical Process Control,TP311.52

CLC: > Industrial Technology > Radio electronics, telecommunications technology > Communicate > Communication theory > Modulation theory
© 2012 www.DissertationTopic.Net  Mobile