Achievable rate approximation for massive MIMO with limited number of interfering clients

2022 ◽  
Author(s):  
Omar Abu Ella ◽  
Mohammed Elmusrati
Keyword(s):  
Massive Mimo ◽  
Achievable Rate

scholarly journals Multiuser precoding scheme and achievable rate analysis for massive MIMO system

2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Weiqiang Tan ◽  
Wei Huang ◽  
Xi Yang ◽  
Zheng Shi ◽  
Wen Liu ◽  
...  
Keyword(s):  
Massive Mimo ◽  
Mimo System ◽  
Achievable Rate ◽  
Rate Analysis ◽  
Multiuser Precoding

scholarly journals Massive MIMO in Spectrum Sharing Networks: Achievable Rate and Power Efficiency

2017 ◽  
Vol 11 (1) ◽  
pp. 20-31 ◽  
Author(s):  
Lifeng Wang ◽  
Hien Quoc Ngo ◽  
Maged Elkashlan ◽  
Trung Q. Duong ◽  
Kai-Kit Wong
Keyword(s):  
Massive Mimo ◽  
Power Efficiency ◽  
Spectrum Sharing ◽  
Achievable Rate

scholarly journals Downlink Achievable Rate Analysis in Massive MIMO Systems With One-Bit DACs

2017 ◽  
Vol 21 (7) ◽  
pp. 1669-1672 ◽  
Author(s):  
Yongzhi Li ◽  
Cheng Tao ◽  
A. Lee Swindlehurst ◽  
Amine Mezghani ◽  
Liu Liu
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Achievable Rate ◽  
Rate Analysis

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>

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