Research And Design Of Channel Estimation Algorithm Based On Sparse Approximation In MIMO OFDM System

With the rapid growth of data flow in mobile communication system,people's demand for wireless communication is also increasing.In order to improve the spectrum utilization of the system with limited spectrum resources,multi antenna technology emerges.Although MIMO OFDM system inherits the double advantages of MIMO and OFDM,it can effectively resist the multipath effect of wireless channel and reduce the frequency selective fading,but it also faces the increasingly difficult channel generated by the combination of the two.In general,the wireless channel is sparse,and compressed sensing theory can be used to reconstruct sparse signal.Therefore,this paper discusses and studies the sparse channel estimation algorithm of MIMO OFDM system based on compressed sensing theory,The main contents of this paper are as follows:(1)When the number of antennas on the base station side of MIMO OFDM system tends to infinity,the certainty of channel matrix is enhanced,and the transmission power of mobile client can be arbitrarily small.Therefore,this paper proposes a sparse channel estimation algorithm based on Re IMV-OMP by using the infinite measurement vector(IMV)model in the theory of compressed sensing.The sparse channel estimation problem is modeled as the sparse signal reconstruction problem based on compressed sensing,and the IMV model is simplified and dimensionally reduced by theoretical derivation,thus greatly reducing the complexity of channel estimation.Finally,compared with the sparse channel estimation algorithm based on block optimal orthogonal matching pursuit(BOOMP),the simulation results show that the sparse channel estimation algorithm based on Re IMV-OMP has better performance.(2)In view of the fact that the sparsity of wireless channel cannot be tracked in real-time in the practical application of MIMO OFDM system,this paper proposes a new algorithm of channel estimation based on the change of residual energy.This algorithm uses the characteristic of the change of residual energy and improves the decision condition of algorithm iteration stop on the basis of the traditional samp algorithm,so that the algorithm no longer needs the prior information of noise energy,which can be more accurate It reduces the number of iterations of the algorithm.Finally,the simulation results show that the algorithm based on residual energy change has better performance.