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Research On Acquisition Method Of Downlink Channel State Information For Massive MIMO Systems

Posted on:2019-08-25Degree:MasterType:Thesis
Country:ChinaCandidate:S J YeFull Text:PDF
GTID:2428330590965698Subject:Electronic and communication engineering
Abstract/Summary:PDF Full Text Request
Massive Multiple-Input Multiple-Output(MIMO)technology has greater performance advantages than traditional MIMO technology and has been considered to be one of the key technologies of the fifth-generation mobile communication technology.However,to take advantage of the massive MIMO technology,both the base station(BS)and the user equipment(UE)need to obtain the channel state information(CSI).With a large number of antennas,the BS needs a sharp increase in the pilot and feedback overhead to obtain the downlink CSI.Therefore,this thesis studies how to obtain accurate downlink CSI with low overhead.The main research contents and innovations are as follows:1.The characteristics of the traditional MIMO technology are introduced,and the advantages and challenges of the massive MIMO are analyzed in this thesis.Then some domestic and foreign studies on the CSI acquisition in the massive MIMO system are summarized.In addition,the fading model of the wireless channel and the common CSI acquisition scheme in the traditional MIMO system are analyzed.Based on this,the typical channel estimation and channel feedback methods in massive MIMO systems are analyzed.2.A massive MIMO channel model with temporal and spatial correlation is introduced in this thesis.Based on this model,a downlink CSI acquisition scheme is proposed.In this scheme,the Kalman filtering technique is used at the UE to improve the channel estimation quality.The channel correlation is used to reduce the CSI dimension and the CSI feedback overhead.The training sequence is dynamically designed by the BS according to the channel prediction error covariance matrix,which improves the channel estimation quality.The channel prediction error covariance matrix is calculated by the BS using Kalman filter technology,which avoids the feedback problem of this information.Simulation results show that the proposed scheme can achieve better performance than the CSI acquisition scheme in the reference.3.The basic principle of compressed sensing,angular domain channel model and channel characteristics of massive MIMO-OFDM systems are analyzed in this thesis.The sparseness of the angular domain channel and the temporal correlation of the support set are studied.Based on this,a CSI acquisition scheme based on compressed sensing is proposed,which includes two parts: CSI acquisition with unknown support set and CSI acquisition with known support set.In the part of CSI acquisition with unknown support set,the iterative hard threshold algorithm and sparsity adaptive matching pursuit algorithm are improved by using the priori information and temporal correlation of the support set,which improves the channel estimation performance.In the part of CSI acquisition with known support set,the support set information of the angular domain channel is used to effectively reduce the pilot overhead.At the same time,an effective pilot design and CSI feedback scheme are also provided.
Keywords/Search Tags:massive MIMO, channel state information, temporal and spatial correlations, compressed sensing
PDF Full Text Request
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