Research On Channel Estimation Schemes Based On Spatial Signatures In Massive MIMO Systems

With the rapid increase of mobile users and emerging scenarios in recent years,massive MultiInput Multi-Output(Massive MIMO)technology has been generally recognized by academia and industry.Its advantages include high spectral and energy efficiency,high system capacity,high spatial resolution,and simple transceiver design.And massive MIMO has been widely recognized as one of the key technologies for the 5th generation mobile communication(5G).However,due to the limitations of the systems' spectrum resource overhead,computing resource overhead,and pilot contamination issues,the implementation and deployment of massive MIMO still face certain challenges.In addition,accurate channel state information(CSI)between the base station and the user is the most basic guarantee of the wireless communication systems.Therefore,the channel estimation technologies are a problem worth studying.This thesis studied the channel estimation problems for the three-dimension MIMO(3D MIMO)systems and nested array Massive MIMO systems.Specifically,the contributions are summarized as follows:Firstly,this thesis studied the channel estimation problem in the multi-user 3D MIMO systems,and proposes a low complexity channel estimation algorithm for 3D MIMO systems with the uniform planar array(UPA)at base station(BS)using paired spatial signatures.With the aid of antenna array theory and array signal processing,firstly 3D channel modeling based on the angle between the direction of arrival(DOA)and the x-direction of the array antenna,and the angle between the DOA and the y-direction of the array antenna.And 3D MIMO channels can be projected onto the x-and y-directions,respectively.Then,channel estimation for multiuser uplinks using small amount of training resources,which is divided into two phases.The first phase is the uplink preamble phase,which assigns each user an orthogonal pilot,and obtains the paired spatial signatures and optimal rotation angle of each user through the same pilot sequence.We also propose a user grouping strategy based on three-dimension angle-division multiple access(3D-ADMA)to ensure that the user's spatial signatures do not overlap.The second phase is much coherence times after the preamble phase,which assigns the same pilot sequence within a group and assigns orthogonal pilot sequences between groups,and the channel state information of the user's x-and y-directions is recovered by the paired space signatures and optimal rotation angle of each user obtained in the preamble phase,respectively.And dynamically updating the user's paired spatial signatures and optimal rotation angle utilizes the obtained channel components of x-and y-directions.Finally,the channel components of the x-and y-directions are reconstructed by the updated user's space signatures and the optimal rotation angle,and the 3D MIMO channel is generated by the Kronecker product.Compared with the conventional channel estimation method of a 3D MIMO system under UPA using a low rank model,the proposed methods greatly reduce the computational complexity without reducing the estimated performance,it is carried out with limited training resources,and the pilot resource overhead of the system is greatly reduced by the 3D-ADMA packet and the two-stage pilot allocation.Various numerical results are provided to corroborate the proposed studies.Then,this thesis explores the channel estimation problems of single cell multi-user nested array massive MIMO systems.In the nested array massive MIMO systems,because the structure of the nested array is an irregular and non-uniform array,some common processing methods cannot be used for signal processing.Therefore,this paper designs a virtual conversion matrix that can convert the nested array channel into an equivalent virtual uniform array channel.Therefore,this paper designs a virtual conversion matrix that can convert the nested array channel into an equivalent virtual uniform array channel.Due to the multiplexing of the multi-user pilot sequence,the signal transmission will be interfered by other users in the group.To eliminate interference,this paper proposes a channel estimation algorithm based on successive interference cancellation(SIC).First,in the uplink preamble phase,orthogonal pilot sequences are assigned to each user,and obtain the channel estimation of each user through the LS estimation algorithm,from which the virtual conversion matrix,spatial signatures,and optimal rotation angle of each user are extracted.Then,they are grouped according to spatial signatures,orthogonal pilots are allocated between groups,and the same pilot sequence is allocated within the groups.In the inter-group transmission phase,the SICbased interference cancellation algorithm eliminates interference caused by virtual conversion.Finally,the channel estimation of each user is obtained.Various numerical results are provided to corroborate the proposed studies.