Research On Blind Estimation Technology Of Spread Spectrum Signal In Complex Channel Environment

Spread spectrum signals are widely used in different fields such as military communications,civil communications,and satellite communications because of their low interception rate,anti-interference,and code division multiple access.Due to the application of spread spectrum signals in various fields,the channel environment for signal transmission has also become more severe.For cooperative communication scenarios,the spreading sequence is known to the receivers.Therefore,the spread spectrum sequence can be used to despread the received signal to obtain the transmitted information.However,for the non-cooperative receivers,the unknown spreading sequence and the complexity of the channel environment make it more difficult to obtain transmission information.Therefore,it is of great significance to study the blind despreading of spread spectrum signals in a complex channel environment.This thesis focuses on the blind estimation technology of spread spectrum signal under complex channel environment.The main contents are as follows:1.A blind estimation scheme for spread spectrum signals in a complex channel environment is proposed.Based on the analysis of the influence of doppler shift,multipath and interference signals on spread spectrum signals in the channel environment,corresponding solutions are proposed.Three schemes are proposed to solve the influence of doppler frequency shift,doppler frequency change and interference signal: pseudo code period reconstruction to correct the influence of doppler frequency shift on symbol width;through dechirping can eliminate the influence of doppler frequency changes,so we can accurately estimate the signal frequency.In the case where the interference power is greater than the transmission signal power,the interference signal can be reconstructed to eliminate the influence of interference.2.For the multipath short-code DSSS signal received by a single channel,the equivalent channel estimation of the phase convolution of the multipath channel and the spreading sequence is obtained by the method of subspace decomposition in the case of a single user.For signals sent by multiple users,the ILSP algorithm is used to find the composite channel of the multipath channel and the spreading sequence,and get the spreading sequence.After the spreading sequence is obtained,the generator polynomial and initial phase of the spreading sequence are obtained by using the properties of the shift register.The spreading sequence is reconstructed to reduce the error of directly estimating the spreading sequence.3.For multipath short-code DSSS signals received by multi-channel receiver,the parallel factor model without inter-symbol interference and the rank L-L-1 tensor model with symbol interference are studied.The two models are applied in the blind estimation of spread spectrum signals,and simulations are used to verify them respectively.4.For synchronous long-code DS-CDMA signals received by multi-channel receiver,based on the missing tensor model,an innovative algorithm based on coupled tensor decomposition is proposed.This algorithm uses the relationship between the spreading sequence of the non-periodic long-code signal and the spreading gain to construct the received signal into a tensor model with a coupled relationship.The identifiability condition of the coupled tensor is analyzed,and an ALS algorithm based on the decomposition of the coupled tensor is proposed.Simulation shows that the proposed model can effectively reduce the bit error rate of blind estimation.