Research On Channel Estimation Techniques For Massive MIMO Systems

Due to the huge advantages of multiple antennas in terms of improving the utilization of frequency bands and system capacity,the expansion of the MIMO dimension,namely,the massive MIMO technology will be an important direction for the future development of mobile communication technologies,but the pilot overhead of massive MIMO systems will be huge.This is a serious problem,especially considering multi-cell cellular systems.The overhead of using multi-cell and multi-user orthogonal pilots will further increase.In addition,for large-scale MIMO systems,the theoretical performance is limited by the reference of neighboring cells.Reuse of signal resources faces more serious pilot pollution problems.How to reduce the pilot overhead and design a channel estimation scheme that is consistent with large-scale MIMO systems has become a key issue in the process of large-scale MIMO theory going into practical applications.In this paper,based on the angle-domain sparse theory of large-scale MIMO channels,an angle-domain pilot design scheme and a dual-sparse-channel model in the time-domain angular domain are proposed,and channel estimation is performed based on compressed sensing.The details are as follows:The huge training overhead of obtaining channel state information first in the BS has been considered as the main challenge in the frequency FDD massive MIMO cellular network.In order to solve this problem,we propose an angular-domain pilot design and channel estimation scheme to reduce the required overhead by exploiting the angular channel sparsity.Specifically,we first use the directional reciprocity of the FDD channel to propose the downlink dominant angle set estimation,which introduces an index calibration algorithm to handle the effects of different wavelengths in the FDD system.Then,an orthogonal pilot design scheme with its corresponding feedback algorithm is given for channel estimation.The simulation results show that our proposed angular-domain pilot design and channel estimation scheme can provide good MSE performance,greatly reduce the pilot overhead,and achieve greater downlink throughput.Secondly,based on the characteristics that the large-scale MIMO time domain is sparse in the angular domain,a sparse dual-channel model in the time-domain angle domain is given.Compared with only the sparse channel model in the time domain or the angle domain,the noise can be suppressed better,and at the same time A generation of mobile communications provides a viable channel estimation model.Based on compressed sensing technology,channel estimation and computer simulation methods for large-scale MIMO-OFDM systems under the dual sparse channel model in the time domain are proposed.Multi-antennas are statistically modeled in the diagonal domain and time fluctuations are added,resulting in a dual-sparse channel model in the time-domain angular domain and channel estimation using OFDM techniques.Compared with thetraditional sparse and angular sparse flat fading channel models,the designed time domain double-sparse model can reduce the complexity of large-scale MIMO channel estimation.