Research On Tensor-based Signal Detection And Parameter Estimation In MIMO Relay System

With the rapid development of communication technology,communication has penetrated into people's life and affected every aspect of human life.At the same time,the increasing number of users also put forward higher requirements on the connection density and spectrum efficiency of the communication system.In order to meet these requirements,new technologies such as non-orthogonal multiple access(NOMA),multiple input and multiple output(MIMO)have received extensive attention.In the promotion and application of these technologies,communication signal processing is an indispensable part.However,the traditional signal processing methods are faced with the problem of mutual restriction between communication performance and computational complexity,which makes the promotion and application of related communication technologies greatly restricted.The method of channel estimation and signal detection based on tensor provides a new way to solve the problem of traditional communication signal processing.In communication signal processing,channel estimation and multi-user detection are two very important issues.This article aims to study tensor-based channel estimation and signal detection technology,and conduct in-depth research on three tensor models at the receiving end.The idea of low rank decomposition,two-way MIMO relay system and coding technology are combined to separate signals from different source nodes,and new channel estimation and signal detection methods are proposed.The main research of this article is as follows:(1)In order to solve the problem of increasing number of users,a channel estimation method with flexible antenna configuration is proposed for the two-way AF relay system with CCFD technology.The method consists of three parts :self-interference cancellation,multi-way matrix modeling and channel estimation.At the sides of the two users,the proposed method simultaneously transmits thedesigned pilot sequences to the relays,and the relays perform self-interference cancellation,and then amplify and forward the received signals to users.The proposed channel estimation method does not require channel estimation and iteration at the relays,which reduce the burden of the relays.Simulation results show that compared with the existing least squares(LS),two-stage training(TST)and non-iterative P?KRF channel estimation methods,the proposed method has higher channel estimation accuracy,and it can operate under more flexible antenna configurations,which has practical significance.(2)In order to obtain more accurate channel statement information(CSI),a high accuracy Channel estimation method is proposed for two-way MIMO relay systems.The proposed method encodes the transmitted signals at both users and the relay respectively.At the same time,the symbol matrix is constructed in multiple Khatri-Rao product forms,providing additional diversity to the system.At the receiving end,each user constructs a Tucker-2 model for the received signal,and uses a non-iterative T-KPLS algorithm to fit the Tucker-2 model to jointly estimate all CSI in the communication system.Compared with the existing bidirectional/unidirectional channel estimation methods,the proposed method does not need to send training sequences,and can directly estimate channel and symbol matrices by using SVD decomposition,which has higher spectrum utilization and channel estimation accuracy.Simulation results verify the effectiveness of the proposed method.(3)For two-way MIMO relay systems,simplified space-time(ST)encoding are used at both source nodes.The target of each source node is to receive the signal from another node.At the other source node,the received signal constitutes a third-order tensor,which satisfies the parallel Tucker-2(PARATUCK2)model.Exploiting this structure,we present a novel semiblind united alternating least squares(Uni-ALS)receiver for jointly estimating the transmitted symbols and the individual channels.Parameter identifiability and uniqueness conditions are analyzed.The simulation results show that the semi-blind receiver has better performance than the TST receiver.