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Research On Channel Estimation Techniques For OFDM Systems In Time-frequency Dual-selection Channel Environment

Posted on:2019-04-02Degree:MasterType:Thesis
Country:ChinaCandidate:X Y LuFull Text:PDF
GTID:2428330596950347Subject:Communication and Information System
Abstract/Summary:PDF Full Text Request
With the rapid development of human society,the transmission environment of the channel is more and more complex,and the transmission performance of the communication system is greatly affected by the time selective fading and the frequency selective fading.Therefore,we need to analyze the channel environment,establish the model of time-frequency dual-selection channel,and combine the channel estimation technology in OFDM technology to estimate the channel accurately,restore the signal and improve the performance of the wireless communication system as far as possible.Therefore,OFDM channel estimation algorithm in time-frequency dual-selection channel environment is the main research in this paper.In this paper,the transmission characteristics are analyzed firstly,and the influence of time selective fading and frequency selective fading on the signal is mainly studied.Based on the statistical characteristics of wireless channel,a time-frequency dual-selection channel model is established,and then some basis expansion model functions which can describe the time-frequency dual-selection channel are analyzed,and the fitting of various basis expansion models and time-frequency dual-selection channels is analyzed by simulation.The traditional LS,MMSE and LMMSE channel estimation algorithm are deduced,we derive the basis function coefficient estimation algorithm based on the basis expansion model and channel estimation algorithm,which can be used to fit the time-frequency dual-selection channel,and transform estimate the channel state parameter to estimate the basis function coefficient.To reduce the amount of calculation from LN ? to(7)1(8)?(10)LQ.The improved algorithm is mainly aimed at the deficiency of the LS channel coefficient estimation algorithm based on the basis expansion model,and proposes a LMMSE algorithm based on the basis expansion model,which verifies that the LS algorithm based on the basis expansion model is affected by the noise,and the performance is inferior to the LMMSE algorithm based on the basis expansion model.From another point of view,a Kalman filter algorithm based on the basis expansion model is proposed to reduce the computational load for Kalman filtering which can track time-frequency dual-selection channel.Furthermore,a square root Kalman filtering algorithm is proposed to solve the problem of Kalman filtering channel estimation algorithm based on basis expansion model,which simplifies the calculation of Kalman filter parameter and improves the estimation performance.The simulation results show that the square root Kalman filtering algorithm based on the basis expansion model is superior to the Kalman filtering algorithm based on the basis expansion model in performance.
Keywords/Search Tags:output-orthogonal frequency division multiplexing, time selective fading, frequency selective fading, basis expansion model, least squares algorithm, linear minimum mean square error algorithm, Kalman filter algorithm
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