scholarly journals Multiuser Beamforming with Limited Feedback for FDD Massive MIMO Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Senyao Zheng ◽  
Hui Zhao ◽  
Long Zhao ◽  
Jie Mei ◽  
Weimin Tang

This paper discusses the multiuser beamforming in FDD massive MIMO systems. It first introduces the feature of FDD massive MIMO systems to implement multiuser beamforming schemes. After that, considering the realistic implementation of multiuser beamforming scheme in FDD massive MIMO systems, it introduces the knowledge of channel quantization. In the main part of the paper, we introduce two traditional multiuser beamforming schemes and analyse their merits and demerits. Based on these, we propose a novel multiuser beamforming scheme to flexibly combine the merits of the traditional beamforming schemes. In the final part of the paper, we give some simulation results to compare the beamforming schemes mentioned in the paper. These simulation results show the superiority of the proposed beamforming scheme.

Author(s):  
Guanghui Fan ◽  
Jinlong Sun ◽  
Bamidele Adebisi ◽  
Tomoaki Ohtsuki ◽  
Guan Gui ◽  
...  

Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1061 ◽  
Author(s):  
Hedi Khammari ◽  
Irfan Ahmed ◽  
Ghulam Bhatti ◽  
Masoud Alajmi

In this paper, a joint spatio–radio frequency resource allocation and hybrid beamforming scheme for the massive multiple-input multiple-output (MIMO) systems is proposed. We consider limited feedback two-stage hybrid beamformimg for decomposing the precoding matrix at the base-station. To reduce the channel state information (CSI) feedback of massive MIMO, we utilize the channel covariance-based RF precoding and beam selection. This beam selection process minimizes the inter-group interference. The regularized block diagonalization can mitigate the inter-group interference, but requires substantial overhead feedback. We use channel covariance-based eigenmodes and discrete Fourier transforms (DFT) to reduce the feedback overhead and design a simplified analog precoder. The columns of the analog beamforming matrix are selected based on the users’ grouping performed by the K-mean unsupervised machine learning algorithm. The digital precoder is designed with joint optimization of intra-group user utility function. It has been shown that more than 50 % feedback overhead is reduced by the eigenmodes-based analog precoder design. The joint beams, users scheduling and limited feedbacK-based hybrid precoding increases the sum-rate by 27 . 6 % compared to the sum-rate of one-group case, and reduce the feedback overhead by 62 . 5 % compared to the full CSI feedback.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xue Zhang ◽  
Feng Zhao

In mmWave massive MIMO systems, traditional digital precoding is difficult to be implemented because of the high cost and energy consumption of RF chains. Fortunately, the hybrid precoding which combines digital precoding and analog precoding not only solves this problem successfully, but also improves the performance of the system effectively. However, due to the constant mode constraint introduced by the phase shifter in the analog domain, it is difficult to solve the hybrid precoding directly. There is a solution which divides the total optimization problem into two stages to solve, that is, first fix the digital precoding matrix, solve the analog precoding matrix, and then optimize the digital precoding matrix according to the obtained analog precoding matrix. In this paper, a high energy-efficient hybrid precoding scheme is proposed for the subconnection structure. In the first stage, the optimization problem can be decomposed into a series of subproblems by means of the independent submatrix structure of the analog precoding matrix. When the optimized analog precoding matrix is obtained, the digital precoding matrix can be solved by the minimum mean error (MMSE). Finally, the digital precoding matrix is normalized to satisfy the constraint conditions. The simulation results demonstrate that the performance of the proposed algorithm is close to that of fully digital precoding based on subconnection structure and better than that of the existing algorithms. In addition, this paper presents the simulation analysis of the algorithm performance under imperfect channel state information. Simulation results show that when the estimation accuracy of channel state information is 0.8, the spectral efficiency of the proposed algorithm can already be maintained at a good level.


2021 ◽  
Author(s):  
Xin Wang ◽  
Xiaolin Hou ◽  
Lan Chen ◽  
Yoshihisa Kishiyama ◽  
Takahiro Asai

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