The Research On Channel Estimation Technology Of OFDM Systems

The future wireless mobile communication systems are expected to provide ubiquitous, high-quality, and high-rate mobile multimedia transmission. Orthogonal Frequency Division Multiplexing (OFDM) is the most promising technology in mobile communication in 4G because of its excellent bandwidth efficiency and robustness against multipath fading and impulse noise. The radio channel is frequency selective and time-varying in OFDM system. In order to obtain the real-time and precise channel state information to complete accurate coherent demodulation, a dynamic estimation of channel is necessary. The dissertation will focus on channel estimation of OFDM system.Firstly, in this dissertation, the statistic properties of multipath and time-varying in general wireless channel is described, and the channel model based on WSSUS (Wide-sense stationary uncorrelated scattering) hypothesis is analyzed. Channel characteristics of OFDM wireless transmission, especially the effect of multipath and Doppler frequency to system performance, are also analyzed. In the mean time, a general wireless channel model with both effects in simulations of OFDM system is constructed.Secondly, in the dissertation, the basic theory of OFDM system is described and the channel estimation technology is researched. Some classical estimation methods, such as Least square and Minimum mean square error, are introduced and then some improvements are proposed. The interpolation methods based on comb-type pilot arrangement are also described. All of these methods are simulated in MATLAB. And the performances are analyzed and compared.Thirdly, this dissertation researches channel estimation in time-varying channel and complete channel estimation in time and frequency-selective fading environment using kalman filter. In OFDM systems, time-varying channels destroy the orthogonality between subchannels and cause interchannel interference (ICI). In order to get right estimation result, a kalman filter based on comb-type pilot signal and a kalman filter based on decision-direct method are proposed for channel estimation. Meanwhile, in the method of kalman filter based on comb-type pilot signal the result is refined using frequency-domain correlation and covariance matrix of estimation error in minimum mean-squared error sense. The simulation results show that both channel estimation methods can achieve good performance.