On Multiuser Pairing And Beamforming Techniques For Massive MIMO Downlink

With the continuous development of wireless communication technologies,the demand for high-rate data communication is increasing.To meet the demand for communication services,multi-user data transmission scheme of Massive MIMO system has drawn more attention.The multi-user data transmission scheme of the Massive MIMO system can reasonably utilize spatial resources and use the same time-frequency resource to transmit information required by multiple users.However,antenna array size and space resources are also limited.How to design a better multi-user transmission scheme and use more limited space resources to transmit more user information is the focus of today's research.In this paper,the Massive MIMO multi-user pairing algorithm and the Massive MIMO multi-user beamforming algorithm are used to optimize the pairing factor and design a better beam to optimize the Massive MIMO multi-user transmission scheme.The main research contents and contributions of the thesis are as follows:1.The traditional multi-user pairing algorithms in Massive MIMO downlink are analyzed.Aiming at the problem of inaccurate pairing of traditional user pairing algorithms based on the main-path information,the power information is employed in the thesis to weight the direction information to solve this problem.Aiming at the low efficiency of traditional user-pairing algorithm based on interference power ratio,the resource pool is designed and the mutual interference is considered in the thesis to solve this problem.Then,since the traditional algorithms are sensitive to the accuracy of channel estimation,this thesis proposes an improved multi-user pairing algorithm based on beam pattern.By comparing the proposed algorithms with the traditional algorithms,the proposed algorithms can achieve the fast and accurate matching of multiple users.Moreover,the proposed algorithms in this thesis for multi-user pairing can achieve better system performance.Finally,based on MATLAB software,the Massive MIMO performance evaluation platform is built.And the conclusions from the theoretical analysis are verified by simulations.The simulation results are consistent with the theoretical analysis results.2.The Massive MIMO downlink multi-user beamforming algorithms are analyzed.The goals of the multi-user beamforming algorithm are to ensure the beamforming gain and suppress the multi-user interference.Based on the goals,in the scene of only angle information can be obtained,an improved null trap beamforming algorithm based on beam pattern is proposed,in which the accuracy of the null position,the maximum depth of the depression,the minimum beam distortion and the maximum beamforming gain are taken into account.A beamforming weight vector is obtained by designing a reasonable convex optimization problem and solving the optimization problem.Finally,the performance simulation of the proposed algorithm is carried out based on the performance evaluation platform.Compared with the traditional algorithm,simulation results show the proposed algorithm has higher beamforming gain and more accurate and deeper nulling.In the scenario where only channel response information can be obtained,an improved null trap beamforming algorithm based on channel response information is proposed.Since the proposed algorithm does not need to estimate the angle information,it can meet the needs of more Massive MIMO application scenarios.Compared with the traditional algorithms,the proposed algorithm shows better system performance.In order to analyze the practicability of the algorithm,the complexity of the proposed beamforming algorithm is analyzed.In addition,the optimization idea of the algorithm complexity is proposed and the complexity of improved algorithm is analyzed.Finally,the proposed algorithms are simulated and analyzed based on the simulation platform.The proposed multi-user pairing algorithms in Massive MIMO downlink in this thesis have advantages in terms of pairing accuracy,pairing efficiency and the resistance to channel estimation error compared with the traditional algorithms.The proposed multi-user beamforming algorithms in Massive MIMO downlink has advantages in reducing multi-user interference,ensuring beamforming gain,and improving system spectrum utilization compared with the traditional algorithms.