Maximizing Minimum Phase Difference Based Hybrid Beamforming for Multiuser mmWave Massive MIMO systems

2018 ◽  
Author(s):  
Yadi Ding ◽  
Anzhong Hu
Keyword(s):  
Phase Difference ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Minimum Phase ◽  
Hybrid Beamforming

Hybridly Connected Structure for Hybrid Beamforming in mmWave Massive MIMO Systems

2018 ◽  
Vol 66 (2) ◽  
pp. 662-674 ◽  
Author(s):  
Didi Zhang ◽  
Yafeng Wang ◽  
Xuehua Li ◽  
Wei Xiang
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Connected Structure ◽  
Hybrid Beamforming

Hybrid Beamforming for Multi-User Massive MIMO Systems

2018 ◽  
Vol 66 (9) ◽  
pp. 3879-3891 ◽  
Author(s):  
Xiaoyong Wu ◽  
Danpu Liu ◽  
Fangfang Yin
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Hybrid Beamforming

scholarly journals Hybrid Beamforming With Selection for Multiuser Massive MIMO Systems

2018 ◽  
Vol 66 (15) ◽  
pp. 4105-4120 ◽  
Author(s):  
Vishnu V. Ratnam ◽  
Andreas F. Molisch ◽  
Ozgun Y. Bursalioglu ◽  
Haralabos C. Papadopoulos
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Hybrid Beamforming ◽  
Selection For

scholarly journals Spatio-Radio Resource Management and Hybrid Beamforming for Limited Feedback Massive MIMO Systems

Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1061 ◽  
Author(s):  
Hedi Khammari ◽  
Irfan Ahmed ◽  
Ghulam Bhatti ◽  
Masoud Alajmi
Keyword(s):  
Massive Mimo ◽  
Fourier Transforms ◽  
Mimo Systems ◽  
Limited Feedback ◽  
Base Station ◽  
Discrete Fourier Transforms ◽  
Beam Selection ◽  
Sum Rate ◽  
Hybrid Beamforming ◽  
Csi Feedback

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.

scholarly journals An improvement to hybrid beamforming precoding scheme for mmWave massive MIMO systems based on channel matrix

2021 ◽  
Vol 23 (1) ◽  
pp. 285
Author(s):  
Zahra Amirifar ◽  
Jamshid Abouei
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Wireless Systems ◽  
Achievable Rate ◽  
Percentage Difference ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Hybrid Beamforming ◽  
Mimo Technology

<p>The massive multiple-input multiple-output (MIMO) technology has been applied innew generation wireless systems due to growing demand for reliability and high datarate. Hybrid beamforming architectures in both receiver and transmitter, includinganalog and digital precoders, play a significant role in 5G communication networksand have recently attracted a lot of attention. In this paper, we propose a simple andeffective beamforming precoder approach for mmWave massive MIMO systems. Wefirst solve an optimization problem by a simplification subject, and in the second step,we use the covariance channel matrixfCk=Cov(Hk)andBk=HkHHkinstead of chan-nel matrixHk. Simulation results verify that the proposed scheme can enjoy a highersum rate and energy efficiency than previous methods such as spatially sparse method,analog method, and conventional hybrid method even with inaccurate Channel StateInformation (CSI). Percentage difference of the achievable rate ofCk=Cov(Hk)andBk=HkHHkschemes compared to conventional methods are 2.51% and 48.94%, re-spectively.</p>

Calibration of Phase Shifter Network for Hybrid Beamforming in mmWave Massive MIMO Systems

2020 ◽  
Vol 68 ◽  
pp. 2302-2315 ◽  
Author(s):  
Xizixiang Wei ◽  
Yi Jiang ◽  
Qingwen Liu ◽  
Xin Wang
Keyword(s):  
Massive Mimo ◽  
Phase Shifter ◽  
Mimo Systems ◽  
Hybrid Beamforming
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