Spectral Efficiency Improvement and Power Control Optimization of Massive MIMO Networks

Higher requirements must be put forward about wireless signal transmission in harsh environments. Energy loss mitigation, channel estimation, noise interference reduction demands high quality of service in wireless communication. In the fifth generation wireless communication, massive multiple-input...

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Main Authors: Xiu Zhang, Hao Qi, Xin Zhang, Liang Han
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9320607/
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spelling doaj-d36022a93ec8438f97f240744a79e36b2021-08-23T23:00:18ZengIEEEIEEE Access2169-35362021-01-019115231153210.1109/ACCESS.2021.30511709320607Spectral Efficiency Improvement and Power Control Optimization of Massive MIMO NetworksXiu Zhang0https://orcid.org/0000-0003-3817-0227Hao Qi1Xin Zhang2https://orcid.org/0000-0003-3846-5498Liang Han3https://orcid.org/0000-0002-8281-9794Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin, ChinaTianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin, ChinaTianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin, ChinaTianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin, ChinaHigher requirements must be put forward about wireless signal transmission in harsh environments. Energy loss mitigation, channel estimation, noise interference reduction demands high quality of service in wireless communication. In the fifth generation wireless communication, massive multiple-input multiple-output (MIMO) networks have been used and play a significant role to fulfill the requirements. Cell-Free massive MIMO networks are recognized as possible solution in the future wireless communication. Spectral efficiency (SE) is a very important index in assessing massive MIMO networks. This article tries to optimize both SE and power control of cell-free massive MIMO networks. Both uplink and downlink transmission are included in the study. The optimization model contains both SE and power control of massive MIMO networks. To tackle the model, a novel ensemble method is developed inspired by ensemble learning. The ensemble method is built up on the neighborhood field optimization method. The goodness of the developed ensemble method is verified by comparing with genetic algorithm, gradient descent method and Newton method. Extensive simulations are performed to study the optimization of SE and power control. Different wireless sensors are taken into consideration to simulate different requirements of massive MIMO networks. The results demonstrate the effectiveness of the proposed method for applying in massive MIMO networks.https://ieeexplore.ieee.org/document/9320607/Massive multiple-input multiple-outputneighborhood field optimizationoptimizationpower controlspectral efficiency
collection DOAJ
language English
format Article
sources DOAJ
author Xiu Zhang
Hao Qi
Xin Zhang
Liang Han
spellingShingle Xiu Zhang
Hao Qi
Xin Zhang
Liang Han
Spectral Efficiency Improvement and Power Control Optimization of Massive MIMO Networks
IEEE Access
Massive multiple-input multiple-output
neighborhood field optimization
optimization
power control
spectral efficiency
author_facet Xiu Zhang
Hao Qi
Xin Zhang
Liang Han
author_sort Xiu Zhang
title Spectral Efficiency Improvement and Power Control Optimization of Massive MIMO Networks
title_short Spectral Efficiency Improvement and Power Control Optimization of Massive MIMO Networks
title_full Spectral Efficiency Improvement and Power Control Optimization of Massive MIMO Networks
title_fullStr Spectral Efficiency Improvement and Power Control Optimization of Massive MIMO Networks
title_full_unstemmed Spectral Efficiency Improvement and Power Control Optimization of Massive MIMO Networks
title_sort spectral efficiency improvement and power control optimization of massive mimo networks
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2021-01-01
description Higher requirements must be put forward about wireless signal transmission in harsh environments. Energy loss mitigation, channel estimation, noise interference reduction demands high quality of service in wireless communication. In the fifth generation wireless communication, massive multiple-input multiple-output (MIMO) networks have been used and play a significant role to fulfill the requirements. Cell-Free massive MIMO networks are recognized as possible solution in the future wireless communication. Spectral efficiency (SE) is a very important index in assessing massive MIMO networks. This article tries to optimize both SE and power control of cell-free massive MIMO networks. Both uplink and downlink transmission are included in the study. The optimization model contains both SE and power control of massive MIMO networks. To tackle the model, a novel ensemble method is developed inspired by ensemble learning. The ensemble method is built up on the neighborhood field optimization method. The goodness of the developed ensemble method is verified by comparing with genetic algorithm, gradient descent method and Newton method. Extensive simulations are performed to study the optimization of SE and power control. Different wireless sensors are taken into consideration to simulate different requirements of massive MIMO networks. The results demonstrate the effectiveness of the proposed method for applying in massive MIMO networks.
topic Massive multiple-input multiple-output
neighborhood field optimization
optimization
power control
spectral efficiency
url https://ieeexplore.ieee.org/document/9320607/
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AT haoqi spectralefficiencyimprovementandpowercontroloptimizationofmassivemimonetworks
AT xinzhang spectralefficiencyimprovementandpowercontroloptimizationofmassivemimonetworks
AT lianghan spectralefficiencyimprovementandpowercontroloptimizationofmassivemimonetworks
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