Research On Single Channel Mixed Signal Identification And Apcma Signal Blind Separation

The APCMA signal is an application of paired carrier multiple access(PCMA)in asymmetric mode.The main feature of the APCMA signal is that multiple small bandwidth,low power station weak signals and large bandwidth,high power main station strong signal are superimposed in time-frequency domain.The weak spectrum of each station is all in the strong signal band of the main station,and the spectrum between the weak signals of the station does not overlap with each other.This way effectively saves the spectrum resources and improves the weak signal of the station Anti-intercept performance.This paper studies the recognition algorithm of single channel mixed signal.And based on the traditional reconstruction cancellation algorithm,the problem of blind separation of APCMA signal is studied emphatically in this paper.The main work and research results of this paper are summarized as follows:Firstly,an identification algorithm based on the difference between observed signal-to-noise ratio and effective signal-to-noise ratio is proposed for single channel mixed signal identification.The algorithm first estimates the signal-to-noise ratio of the signal based on the power spectrum of the received signal.Then,after the signal matching filtering,the effective signal-to-noise ratio of the signal is obtained by using the relationship between the second moment and the fourth moment of the signal waveform.And the difference between the effective signal-to-noise ratio is used to distinguish the mixed signal and single signal.Compared with the traditional algorithm of symmetrical mixed signal and asymmetric mixed signal recognition,this algorithm has higher recognition rate,which can distinguish the mixed signal in symmetrical and asymmetrical modes from single signal.And this algorithm structure is simple.This algorithm also does not need to extract the mixed signal synchronization parameters.Secondly,aiming at the problem of blind separation of APCMA signals,the performance of traditional blind separation algorithm based on reconstruction is analyzed.In this paper,we first give the traditional reconstruction of the blind separation structure,from the point of view of the interference suppression ratio,the paper gives the theoretical analysis of the influence of the strong signal synchronization error on the reconstruction algorithm.Then,according to the factors such as different strong signal power,weak signal power,noise power,weak signal bandwidth and weak signal path in APCMA signal,the influence of various factors on the blind separation performance is analyzed in the form of simulation,for the propose algorithms to enhance the performance of blind separation to pave the way for.Thirdly,aiming at the problem of blind separation of APCMA signals,on the basis of a blind separation structure with low complexity,an efficient blind separation algorithm based on soft information joint correction is proposed.By utilizing the demodulation mutual influence between the strong and weak signals,this algorithm tries to correct the receiving symbols of strong signal with high error probability.Comparing the symbol constellation quality(soft information)of signals before and after correction,we can decide whether the hard decision values of strong and weak signals need to be modified,which efficiently reduce the demodulation error rate of strong and weak signals.The algorithm can effectively improve the blind separation performance,and the computational complexity of the algorithm is much lower than the computational complexity of the reconstruction cancellation algorithm.Finally,aiming at the problem of blind separation of APCMA signals,on the basis of the reconstruction cancellation algorithm,an iterative blind separation/decoding algorithm based on Turbo iteration is proposed.In the process of blind separation,this algorithm makes full use of the soft information of the decoded soft information and the influence between the strong and weak signals waveforms.On the one hand,the decoded soft information is utilized as the prior information of the next round iterative decoding to improve the decoding performance.On the other hand,the soft information is remapped to obtain the expected value of the symbols(soft symbols),then the performance of the reconstruction cancellation is improved by reconstructing the waveform with soft symbols.The simulation results show the effectiveness of the algorithm.After two to three iterations,the bit error rate can be reduced by three orders of magnitude.