Study On Parameter Estimation And Modulation Recognition Of FBMC Signal

With the advent of the internet of everything,the data traffic of mobile terminals has grown rapidly,and spectrum resources have been unable to meet human needs.A new generation of 5G mobile communication standards have been proposed to support users' new requirements in terms of increasing data rates,reducing latency,increasing regional density,increasing mobility,and increasing spectrum utilization.The standard proposes a non-quadrature modulation filter bank multi-carrier(FBMC)technology,the prototype filter design improves the spectrum utilization rate and accelerates the out-of-band radiation attenuation.The offset quadrature amplitude modulation(OQAM)technology reduces the delay of signal processing and reduces aliasing interference.The advantages of FBMC waveforms will become increasingly widespread under new demands.In the context of non-assisted communication applications,research in fields such as adaptive demodulation of FBMC signals,cognitive radio and spectrum detection are of great significance.This thesis mainly focuses on the parameter estimation and modulation recognition of the FBMC system.Its main work is as follows:(1)Aiming at the problem of subcarrier parameter estimation in FBMC signal,this thesis proposes a fourth-order cumulant to estimate the subcarrier frequency and number of FBMC signal under gaussian white noise channel.First,intercept the FBMC-OQAM signal and detect the signal spectrum to determine the range of the cycle frequency.Then,analyze the algebraic relationship between the cycle frequency and the fourth-order cumulant.Finally,it is deduced that the peak value of the fourth-order cumulant is affected by the prototype filter and only exists where its cycle frequency is equal to the subcarrier frequency.The frequency and number of sub-carriers can be effectively estimated by detecting the position and number of the peak of the fourth-order cumulant,and the parity of the overlap factor causes the unevenness of the fourth-order cumulant.(2)Aiming at the problem of channel order and signal-to-noise ratio parameter estimation of FBMC-OQAM signals under multipath channels,this thesis proposes an algorithm that inserts pilot sequences and combines cost function and cyclic autocorrelation.First,construct a pilot sequence containing FBMC-OQAM symbols at the transmitting end,calculate the cyclic autocorrelation function of the symbol,and use the time-varying autocorrelation function of ? =0 to estimate the symbol length and signal power.Then,the pilot sequence of the symbol is extracted,and the redundancy of the pilot sequence and the channel memory are combined to construct a maximum geometric mean(MGM)cost function to estimate the channel order.Finally,the pilot sequence difference is used to estimate the noise variance to obtain the signal-to-noise ratio of the channel.(3)Aiming at the problem of modulation recognition in FBMC system and low recognition rate under low signal-to-noise ratio,this thesis uses the characteristics of high-order statistics to suppress noise,and combines back propagation(BP)neural network to design automatic modulation classification(AMC)realizes the classification of the carrier signal.First,the classifier preprocesses the signal at the receiving end to obtain various order statistics.Then uses the fourth-order and sixth-order statistics to construct three characteristic parameters.Finally,uses the difference of different signal characteristic parameters to construct BP neural network recognition.Experiments show that the AMC can effectively identify PSK(2 and 4)and QAM(16,32,64,128 and 256)modulation methods in the FBMC system.