Design Of Compressed Channel Estimation In Mobile Communication System

With the continuous evolution of the mobile communication system and mobileInternet,the service provided by the wireless communication system is also rising along with the increasing demand of people.In order to improve the power efficiency of the system and further improve the spectrum utilization,the fifth generation(5G)system is on the large scale antenna transmission technology research.The wireless transmission technology of MIMO-OFDM(Multiple-Output and Orthogonal Frequency Division Multiplexing)system and large-scale MIMO system are the foundation and core technology of 5G wireless transmission.The channel estimation algorithm of traditional MIMO-OFDM wireless system does not make full use of the inherently sparsity of wireless channel,which leads to that channel estiamtion accuracy and the rate of spectrum resource utilization is not high,In recent years,CS(compressive sensing)is widely used in the process of channel estimation reconstruction signal,which not only reduces the hardware requirements of the system but also greatly reduces the compression rate.In order to ensure the transmission performance of the system,accurate channel estimation is an indispensable part,the channel estimation method of MIMO-OFDM system and large-scale MIMO system based on compression sensing has very practical significance significant for the future development of mobile communications.The characteristics of wireless communication channel and the theory of compressed sensing are analysed and the MIMO-OFDM system and the MIMO system model explored in this thesis.According to the characteristics of MIMO-OFDM in wireless transmission system,we can make the original signal is recovered with higher accuracy by introducing the expansion factor and appropriate increase in the number of iterations to select the matching atom more accurate based on the OMP(Orthogonal Matching Pursuit)algorithm.In addition,a large-scale MIMO system is studied based on the MIMO-OFDM system,using a block-optimized orthogonal matching tracking algorithm to estimate the channel.The computational complexity of the algorithm can be redeced by optimizing the measurement matrix.Finally,the simulation of the system is carried out by MATLAB,in the comparison and analysis with the traditional basic channel estimation method,the channel estimation methods are adopted in this thesis,the SNR and BER of signal recovery has improved significantly.