scholarly journals Energy Efficiency in Massive MIMO-Based 5G Networks: Opportunities and Challenges

2017 ◽  
Vol 24 (3) ◽  
pp. 86-94 ◽  
Author(s):  
K. N. R. Surya Vara Prasad ◽  
Ekram Hossain ◽  
Vijay K. Bhargava
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
5G Networks

scholarly journals Towards Optimal Energy Efficiency in Cell-Free Massive MIMO Systems

2021 ◽  
pp. 1-1
Author(s):  
A. Papazafeiropoulos ◽  
H. Q. Ngo ◽  
P. Kourtessis ◽  
S. Chatzinotas ◽  
J. M. Senior
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Optimal Energy

scholarly journals Secrecy Spectrum and Energy Efficiency Analysis in Massive MIMO-Enabled Multi-Tier Hybrid HetNets

2020 ◽  
Vol 4 (1) ◽  
pp. 246-262 ◽  
Author(s):  
Anum Umer ◽  
Syed Ali Hassan ◽  
Haris Pervaiz ◽  
Leila Musavian ◽  
Qiang Ni ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Efficiency Analysis ◽  
Energy Efficiency Analysis

scholarly journals Maximizing Energy Efficiency for Consumption Circuit Power in Downlink Massive MIMO Wireless Networks

2017 ◽  
Vol 7 (6) ◽  
pp. 2977 ◽  
Author(s):  
Adeeb Salh ◽  
Lukman Audah ◽  
Nor Shahida M. Shah ◽  
Shipun A. Hamzah
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Data Rate ◽  
Optimal Number ◽  
Zero Forcing ◽  
High Data ◽  
Circuit Power

<span>Massive multi-input–multi-output (MIMO) systems are crucial to maximizing energy efficiency (EE) and battery-saving technology. Achieving EE without sacrificing the quality of service (QoS) is increasingly important for mobile devices. We first derive the data rate through zero forcing (ZF) and three linear precodings: maximum ratio transmission (MRT), zero forcing (ZF), and minimum mean square error (MMSE). Performance EE can be achieved when all available antennas are used and when taking account of the consumption circuit power ignored because of high transmit power. The aim of this work is to demonstrate how to obtain maximum EE while minimizing power consumed, which achieves a high data rate by deriving the optimal number of antennas in the downlink massive MIMO system. This system includes not only the transmitted power but also the fundamental operation circuit power at the transmitter signal. Maximized EE depends on the optimal number of antennas and determines the number of active users that should be scheduled in each cell. We conclude that the linear precoding technique MMSE achieves the maximum EE more than ZF and MRT</span><em></em><span>because the MMSE is able to make the massive MIMO system less sensitive to SNR at an increased number of antennas</span><span>.</span>

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