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
Author(s):  
A. Papazafeiropoulos ◽  
H. Q. Ngo ◽  
P. Kourtessis ◽  
S. Chatzinotas ◽  
J. M. Senior

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

Author(s):  
Adeeb Salh ◽  
Lukman Audah ◽  
Nor Shahida M. Shah ◽  
Shipun A. Hamzah

<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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