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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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/ |
work_keys_str_mv |
AT xiuzhang spectralefficiencyimprovementandpowercontroloptimizationofmassivemimonetworks AT haoqi spectralefficiencyimprovementandpowercontroloptimizationofmassivemimonetworks AT xinzhang spectralefficiencyimprovementandpowercontroloptimizationofmassivemimonetworks AT lianghan spectralefficiencyimprovementandpowercontroloptimizationofmassivemimonetworks |
_version_ |
1721198103011262464 |