Research On Demodulation,Decoding And Separation Technology Of Mixed Signal Based On Prior Information Of Data Frame

As an emerging high-efficiency satellite communication system,Paired Carrier Multiple Access(PCMA)technology significantly improves the frequency band utilization of satellite channels by allowing both parties to communicate with the same frequency band resources for information transmission.Moreover,the complex channel structure of the system also makes it more resistant to interception than conventional satellite channels.While studying the problem of PCMA signal modulation recognition,this paper also focuses on the use of data frame prior information to perform parameter estimation and interpretation/separation of mixed signals.The specific research content and research results can be summarized as follows:Aiming at the problem that common PCMA signal modulation recognition algorithms cannot perform modulation recognition on PCMA signals with different sub-signal modulation methods,a modulation recognition algorithm based on sequence nonlinear transformation characteristics and suitable for Multiple Phase Shift Keying(MPSK)modulated PCMA signals is proposed.The new algorithm first uses the envelope square transformation to estimate the average power of the signal,and then uses the detection threshold delineated based on the average power of the signal and the feature of the nonlinear transformation of the signal to identify the type of signal(single signal or PCMA signal)and modulation type.The new algorithm has a simple structure,does not require timing synchronization preprocessing,and has no strict requirements on the signal oversampling multiple and rolloff factor.It can realize the modulation recognition of the MPSK modulated PCMA signal with the same subsignal power.For common mixed signal parameter estimation algorithms,each modulation parameter needs to be estimated separately,and it is more sensitive to frequency offset interference when estimating signal symbol timing offset and amplitude,a new joint parameter estimation algorithm based on multi-layer difference principle is proposed.The new algorithm uses data frame prior information,multi-layer difference,maximum likelihood,and triangular polynomial interpolation theory to realize the estimation of the starting position of the signal preamble sequence and the timing offset,and the algorithm can use the stage result to jointly estimate the signal carrier frequency offset.Also,the algorithm can use the synchronized likelihood function value to estimate the signal amplitude.The new algorithm has flexible algorithm structure,and has appropriate frequency offset capture ability when estimating timing offset and signal amplitude.Therefore,the algorithm can be applied to various complex channel environments.Aiming at the problem that the common mixed signal separation algorithm is a blind separation algorithm and does not optimize the reconstruction of weak signals,a new mixed signal interpretation/separation algorithm based on data frame prior information,iterative decoding and decision feedback fractional interval equalization processing is presented.The new algorithm improves the reliability of information restoration of mixed signals through iterative decoding and equalization processing,and realizes the separation of mixed signals by means of interference cancellation.The new algorithm can use one iterative processing to achieve an information restoration performance improvement of about 1d B,and the equalization processing for reconstructing a weak signal can also improve the information restoration performance of a weak signal by about 1.5dB.