Modulation Recognition On Broadband Radio Communication Signals

In the field of rapid development of wireless communication technology,the communication system is constantly developing and updating;and the mutual interference between various communication will hinder normal communication.Besides,communication environment is becoming more and more complicated.Therefore,the recognition of modulation signals is widely used in many communication systems,which includes the application of civil and military,especially in the non-cooperative communication systems.In addition,most of the satellite communication systems use MPSK and MQAM signals for information transmission.Therefore,intra-class modulation recognition of these two types of signals is the emphasis of this thesis.In this thesis,first of all,plenty of recognition algorithm for the digital modulation signals is studied,and the advantages and disadvantages of various modulation recognition algorithms are compared.And then the improved algorithms of intra-class recognition for MPSK and MQAM signals are proposed.This thesis is divided into the following four parts:Firstly,the modulation and recognition process of digital signal is introduced.The basic method for modulation recognition is based on pattern recognition method or decision theory.Secondly,the basic methods of modulation recognition are analyzed,including the time domain feature extraction,maximum likelihood estimation,amplitude characteristic parameters,wavelet transform.According to the simulation results,the advantages and disadvantages of each method are analyzed.Then,the modulation recognition for MPSK signals are mainly studied.After comparing the effectiveness of various algorithms,the MPSK signals are identified by neural network classifier.In this algorithm,the higher order cumulants is used as the characteristic parameters,and the classifier uses BP neural network.The simulation results show that this algorithm has good anti-noise performance and has high recognition efficiency for BPSK,QPSK,8PSK and 16 PSK signals at low signal-to-noise ratio.Finally,recognition algorithm for MQAM signals are studied.Two algorithms are used to identify the MQAM signals: constellation clustering,maximum likelihood estimation.The simulation results show that the algorithm based on constellation clustering can effectively identify 4QAM,16 QAM,32QAM,64 QAM,128QAM and 256 QAM under a certain SNR,and the maximum likelihood estimation method for MQAM of rectangular constellation can be recognized at Low signal-to-noise ratio.