Energy Efficiency Augmentation in Massive MIMO Systems through Linear Precoding Schemes and Power Consumption Modeling

Author:

Asif Rao Muhammad1,Arshad Jehangir2ORCID,Shakir Mustafa1,Noman Sohail M.3,Rehman Ateeq Ur45

Affiliation:

1. Department of Electrical Engineering, The Superior College Lahore, Lahore, Pakistan

2. Electrical and Computer Engineering Department, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan

3. Department of Cell Biology and Genetics, Shantou University Medical College, Shantou, Guangdong 515041, China

4. College of Internet of Things Engineering, Hohai University, Changzhou 213022, China

5. Department of Electrical Engineering, Government College University, Lahore 54000, Pakistan

Abstract

Massive multiple-input multiple-output or massive MIMO system has great potential for 5th generation (5G) wireless communication systems as it is capable of providing game-changing enhancements in area throughput and energy efficiency (EE). This work proposes a realistic and practically implementable EE model for massive MIMO systems while a general and canonical system model is used for single-cell scenario. Linear processing schemes are used for detection and precoding, i.e., minimum mean squared error (MMSE), zero-forcing (ZF), and maximum ratio transmission (MRT/MRC). Moreover, a power dissipation model is proposed that considers overall power consumption in uplink and downlink communications. The proposed model includes the total power consumed by power amplifier and circuit components at the base station (BS) and single antenna user equipment (UE). An optimal number of BS antennas to serve total UEs and the overall transmitted power are also computed. The simulation results confirm considerable improvements in the gain of area throughput and EE, and it also shows that the optimum area throughput and EE can be realized wherein a larger number of antenna arrays at BS are installed for serving a greater number of UEs.

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

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