Fast Time-varying Channel Estimation For Wireless Communication Systems On High Speed Railways

High speed railways is gaining increasing popularity among Chinese due to its convenience,flexibility and high efficiency.Meanwhile,the researches of the fifth generation(5G)wireless communication technology are emerging.Therefore,wireless communication on high speed railways,as a fundamental and challenging application scenario of the 5G communication technology,is brought into the focus of experts and scholars.One critical technology to be analyzed is fast time-varying channel estimation on high speed railways in order to meet the performance requirements of 5G wireless communication.Owing to the extremely complicated geographical environment and high velocity,high speed railway scenarios have dramatic difference compared with normal scenarios.Consequently,traditional estimators are no longer suitable for estimating channels on high speed railways.This paper aims at investigating novel channel estimators and testifying their performance through real environments via simulations.To begin with,this paper introduces three typical scenarios on high speed railways and illustrates their corresponding properties.A comprehensive evaluation model with multiple typical scenarios is constructed,and based on which the channel parameters is measured.The features of wireless communication channel on high speed railways are discussed and a reasonable model associated with the measured channel parameters is established.Then,the orthogonal frequency division multiplexing(OFDM)technology utilized in wireless link transmission and the frame structure defined in physical layer of 5G networks are given.Next,the basis expansion model(BEM),an estimator that diverts the estimation of channel parameters into the estimation of basis coefficient,is harnessed for that it can abridge the estimation parameters.Note that the property of channels on high speed railways keep changing with geographic positions of the train,which could result in the inconsistent performance of estimation because that the basis matrices of existing BEMs are constant.Then,the lower bound of mean square error of BEM is derived and the optimal basis matrix is formed by the eigenvectors of channel correlation matrix.We find that the optimal basis matrix is especially appropriate for high speed railway environment after analysis.Notice that the trains always follow the same tracks.Therefore,at a fixed position the channels among different times are strongly correlated.This improved BEM is entitled as historical information based basis expansion model(HiBEM).The LS method is applied to recover the basis coefficient based on pilots.At the same time,to alleviate spectrum congestion,iterative expectation maximization(EM)algorithm is leveraged to compute the basis coefficients of HiBEM without requiring pilots.Finally,performance of various channel estimators and their algorithm complexity are analyzed and compared through computer simulations.It is found that the high-speed-railway-suited HiBEM is computationally efficient and performs better.In addition,the results of link level simulation show that the system throughput of HiBEM can satisfy the requirement of 5G wireless communications.