Space-time Coding For Multi-user MIMO Relay Systems Based On Asymmetric Nested Tensor Decomposition

Multi-user multiple-input multiple-output(MIMO)can simultaneously obtain spatial multiplexing gain and multi-user diversity gain,which can significantly improve system throughput and the transmission rate of users.In a multi-user MIMO relay system,space-time coding introduces the correlation between time and space on the signals sent by different antennas,thereby providing coding and diversity gain without sacrificing bandwidth,improving the transmission efficiency of the system and to effectively reduce multipath fading,it is one of the important technologies to realize the high-speed wireless data communication system with increasingly tight broadband resources.With the increase in the number of users and the demand for massive data transmission,the existing space-time coding algorithm provides limited diversity gain and cannot solve the problem of multi-user interference.It is no longer suitable for space-time coding of multi-user MIMO relay systems.In order to solve these problems,this paper proposes a space-time coding algorithm for multi-user MIMO relay system based on asymmetric nested tensor decomposition.The main research contents are as follows:First,the current matrix-based space-time coding does not make full use of the strong algebra structure of the tensor to obtain more diversity gain and coding gain for multiple channels existing in the MIMO relay system,resulting in the reliability of system not meeting the demand.After introducing the basic theory and system model of the MIMO relay system,this paper proposes an asymmetric space-time coding scheme for the one-way two-hop MIMO relay system,using different numbers at the source and relay nodes of the space-time coding matrix,which brings multiple diversity gains to improve the reliability of the system.Using this scheme,a system model of space-time coding for a one-way two-hop MIMO relay system is established.Because the model receives high-dimensional signals at the receiving end,it cannot be decomposed by the existing tensor.Therefore,this paper proposes asymmetric nested tensor decomposition and expresses the received high-dimensional signal through an asymmetric nested tensor model to solve the reception problem.Secondly,the high-dimensional received signals represented by asymmetric nested tensors cannot directly estimate the original information,and the receiving algorithm needs to be derived.Tensor mode expansion is used to decompose the asymmetric nested tensor into multiple matrix forms.A semi-blind received algorithm based on Alternating Least Squares(ALS)is derived to jointly estimate the original signal and channel information.Since the received algorithm needs to be iterated,the calculation complexity is high.Based on this,a closed-form semi-blind received algorithm is proposed to reduce the complexity of algorithm iteration without reducing the estimation accuracy.Simulation experiments verify that the proposed algorithm can improve the performance of bit error rate.Finally,in order to solve the problem of co-channel interference among multiple users in the multi-user MIMO system,beamforming technology is introduced.The beamforming criterions and algorithms are used to design a precoding matrix,which is combined with a channel to eliminate multi-user interference,and a beamforming joint space-time coding scheme is proposed.The space-time coding combined beamforming algorithm based on asymmetric nested tensor decomposition is applied to the multi-user MIMO AF relay system,and the simulation is compared with the current algorithm.Experimental results prove that the algorithm effectively solves the interference problem among multiple users and improves the performance of bit error rate.