Research On Channel Estimation Based On Orthogonal Pilots For STBC MIMO-OFDM System

Multiple input multiple output(MIMO)and orthogonal frequency division multiplexing(OFDM)are the core technologies of 4G,and also the key technologies of 5G In the process of channel transmission,signal will suffer from multi-path fading,Doppler shift,and additive white Gaussian noise(AWGN),which will cause inter symbol interference(ISI)and inter carrier interference(ICI),and affect the correct reception of signal.Therefore,channel estimation plays a decisive function in the performance of MIMO-OFDM system,and the correct transmission of signal requires accurate channel estimation technology.Therefore,this thesis focuses on the research of channel estimation in MIMO-OFDM system.The main work done is as follows:(1)The current pilot based channel estimation methods utilize a large number of pilots to estimate the channel,which reduce the spectral efficiency and data transmission rate.At the same time,the channel estimation results are seriously affected by AWGN.To solve these problems,this thesis designs a Haar wavelet decision feedback(DF)channel estimation method.First,it just requires inserting one block pilot symbol in front of the first OFDM symbol to estimate the initial channel frequency response(CFR).Then,the CFR at other OFDM symbols could be obtained through the process of iterative DF channel estimatio a At last,it could suppress the AWGN existing at the estimated channel impulse response(CIR)effectively,based on a time-domain threshold which is a standard deviation of AWGN obtained by Haar wavelet decomposition.Experimental results demonstrate that the designed method has better bit error rate(BER)and normalized mean square error(NMSE)performance than the conventional least square(LS)and discrete Fourier transform(DFT)methods,and also inproves the spectral efficiency and data transmission rate.(2)In MIMO-OFDM system,there is interference among antennas,and the complexity of channel estimation is high,which is seriously affected by AWGN.To solve these problems,this thesis designs a singular value decomposition(SVD)channel estimation method in space-time block coding(STBC)MIMO-OFDM system First,STBC is utilized to obtain diversity gain and resist channel fading.Then,orthogonal pilot sequences are designed to suppress the interference among antennas.At last,according to the minimum mean square error(MMSE)criterion,the MMSE channel estimation method is derived.To further reduce the computational complexity,SVD is used to decompose the channel autocorrelation matrix.Experimental results demonstrate that the designed method has better BER performance than the conventional LS and threshold methods in static channel However,this method could not adapt to the dynamic channel environment.(3)In view of the fact that SVD method could not adapt to the dynamic channel environment,this thesis designs a Kalman filter(KF)channel estimation method,which could be applied to STBC MIMO-OFDM system with two transmit antennas,two receive antennas and four transmit antennas,four receive antennas at the same time.First,for the STBC MIMO-OFDM system with four transmit antennas and four receive antennas,a new orthogonal space-time codeword is adopted,and the orthogonal pilot sequences are designed to suppress the interference among antennas.Next,the prediction and update characteristics of KF are researched,and the state space model is established for STBC MIMO-OFDM system Then,the CFR is estimated iteratively according to the KF estimation equation.At last,to further improve the accuracy of KF channel estimation,the threshod is utilized to suppress the AWGN in the CIR estimated by KF method.Experimental results demonstrate that the designed method could track the dynamic channel well and has better BER and NMSE performance than SVD,DFT,and LS methods.At the same time,the STBC MIMO-OFDM system with four transmit antennas and four receive antennas has higher diversity gains and higher ability of resisting channel fading than two transmit antennas and two receive antennas.