Research On Sparse Channel Estimation In Millimeter Wave Massive MIMO System

The combination of Millimeter wave(MmWave)and Multiple Input Multiple Output(MIMO)technology can further realize the communication requirements of low delay,high reliability and high throughput.Massive MIMO technology uses.many antennas,so the dimension of channel matrix is very large,which increases the complexity of channel estimation.However,the large path loss of MmWave leads to a small number of effective paths in the channel,so the Mm Wave channel matrix is sparse.Channel estimation restores the channel matrix,which provides the basis for beam selection and configuration.It directly affects the performance of the whole communication system and plays an important role in wireless mobile communication.Therefore,this thesis focuses on sparse channel estimation in mm Wave massive MIMO systems.In view of the defect that the number of spatial directions V retained by the Support Detection(SD)algorithm when solving channel vectors is fixed and cannot adapt to noise changes,In this thesis,an Adaptive Support Detection based on Nosie(NASD)channel estimation algorithm is proposed.According to the distribution law of non-sparse values and the relation of noise amplitude in beamspace channel,the algorithm can make the number of selected spatial directions change adaptively with the change of noise amplitude under different SNR.Simulation results show that the NASD algorithm can effectively reduce the influence of noise on the accuracy of channel estimation when the V value is small.When the V value is high,more effective information can be retained and better recovery performance can be achieved.Compared with the original SD algorithm,the average spectrum efficiency of NASD algorithm is improved by 20%,and the accuracy of channel estimation is improved by 4.43dB.Path number has an important influence on the accuracy of channel estimation.For the channel estimation algorithm based on 2 Dimensional Discrete Fourier Transform(2DDFT),the deficiency of path number must be known in advance when solving channel parameters.In this thesis,the Path Number Adaptive 2DDFT(PNA-2DDFT)algorithm is designed.The algorithm can get the path number in the current channel adaptively in the outer loop according to the relationship between the path number and the estimation error,and then solve the path number in the inner loop using 2DDFT algorithm.The simulation results show that the PNA-2DDFT algorithm can achieve the same or even better performance than 2DDFT without knowing the path number.Compared with NASD,PNA-2DDFT improves the spectral efficiency by 22%and the accuracy of channel estimation by 12.32dB.