The Research Of Midamble Aided Channel Estimation Technology In The High-speed Railway

With the rapid development of high-speed railway, it brings great challenge to high-speed railway communication system that provides high data rate and high-quality communication to ease the increasingly urgent need of the people. The complex environment in the high-speed railway brings great challenge to the communication technologies. Therefore it is necessary to research the channel estimation technology and establish the channel model which is suitable for the high-speed railway scenario.Firstly, the characteristics of wireless mobile channel in the high-speed railway scenario are analyzed, and then a channel model which is suitable for the high-speed railway scenario is proposed by improving the COST207RA channel model based on these characteristics. At last the corresponding simulation and analysis are presented.The channel state information suffers real-time change with the rapid transformation of communication environments and the high-speed mobility of the mobile station in the high-speed railway scenario. Using the traditional channel estimation methods based on pilots and training sequences to estimate the channel state information will not track and estimate the channel in real time, so that the channel estimation error is increased and the wireless communication system performance is decreased. To track and estimate the channel in real time, a time-frequency combination channel estimation algorithm which is suitable for the high-speed railway scenario is proposed. This algorithm effectively combines pilots, Midambles and Kalman filter to achieve the channel estimation in time and frequency domains. HM is the initial channel state value and HP acts as the real channel export value initially. The complete channel values are derived by continually refreshing the state value to modify channel values. At last, the simulations are presented for the establishment of the channel model to analyze the system performance with different channel estimation algorithms, modulation methods, pilot intervals, signal-to-noise ratios and the moving speeds. The simulation results show that the time-frequency channel estimation algorithm can realize channel estimation better and improve the system reliable transmission accuracy. There are24figures,5tables and76references in this thesis.