scholarly journals Deep Learning for Direct Hybrid Precoding in Millimeter Wave Massive MIMO Systems

2019 ◽  
Author(s):  
Xiaofeng Li ◽  
Ahmed Alkhateeb
Keyword(s):  
Deep Learning ◽  
Millimeter Wave ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Hybrid Precoding

Deep Learning Based Hybrid Precoding Technique for Millimeter-Wave Massive MIMO Systems

2021 ◽  
Author(s):  
Islam Osama ◽  
Mohamed Rihan ◽  
Mohamed Elhefnawy ◽  
Sami Eldolil
Keyword(s):  
Deep Learning ◽  
Millimeter Wave ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Hybrid Precoding

Dynamically Connected Hybrid Precoding Scheme for Millimeter-Wave Massive MIMO Systems

2018 ◽  
Vol 22 (12) ◽  
pp. 2583-2586
Author(s):  
Xiaorong Jing ◽  
Lianghong Li ◽  
Hongqing Liu ◽  
Shaoqian Li
Keyword(s):  
Millimeter Wave ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Hybrid Precoding

Performance Analysis of Different Hybrid Precoding Schemes in 5G mmWave massive MIMO Systems

2021 ◽  
Vol 11 (09) ◽  
pp. 1696-1700
Author(s):  
Md. Mizanul Hoque ◽  
Md. Masud Karim ◽  
Md. Mustafa Kamal ◽  
Md. Kayesh ◽  
Sawkat Osman
Keyword(s):  
Energy Consumption ◽  
Performance Analysis ◽  
Millimeter Wave ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Cellular Communication ◽  
Low Energy ◽  
System Complexity ◽  
Hybrid Precoding ◽  
Energy Consuming

Millimeter-wave (mmWave) communication is most likely to appear as a aspiring technology in the upcoming generation of cellular communication (5G). To confront several challenges (e.g., system complexity, energy consumption etc.), hybrid precoding is largely investigated in mmWave massive MIMO systems due to its low energy consuming nature and reduced system complexity.

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