Optimal Energy Efficiency Based Power Adaptation for Downlink Multi-Cell Massive MIMO Systems

In this paper, the power transmission and energy efficiency (EE) in downlink multi-cell massive multiple-input-multiple-output (MIMO) systems are investigated and optimized. Most of the existing works do not take into account different user's quality of service (QoS) requirements. These models...

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Main Authors: Vahid Khodamoradi, Aduwati Sali, Oussama Messadi, Asem A. Salah, Mohanad M. Al-Wani, Borhanuddin Mohd Ali, Raja Syamsul Azmir Raja Abdullah
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9256345/
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spelling doaj-e367deba1fff4a52a2e0bd41830f60e02021-03-30T04:34:02ZengIEEEIEEE Access2169-35362020-01-01820323720325110.1109/ACCESS.2020.30375309256345Optimal Energy Efficiency Based Power Adaptation for Downlink Multi-Cell Massive MIMO SystemsVahid Khodamoradi0https://orcid.org/0000-0003-3185-6672Aduwati Sali1https://orcid.org/0000-0002-1692-6516Oussama Messadi2Asem A. Salah3https://orcid.org/0000-0001-6184-2314Mohanad M. Al-Wani4https://orcid.org/0000-0003-1736-679XBorhanuddin Mohd Ali5Raja Syamsul Azmir Raja Abdullah6https://orcid.org/0000-0002-9375-2038Department of Computer and Communication Systems Engineering, Faculty of Engineering, Wireless and Photonic Networks Research Centre of Excellence (WiPNET), Universiti Putra Malaysia, Selangor, MalaysiaDepartment of Computer and Communication Systems Engineering, Faculty of Engineering, Wireless and Photonic Networks Research Centre of Excellence (WiPNET), Universiti Putra Malaysia, Selangor, MalaysiaDepartment of Computer and Communication Systems Engineering, Faculty of Engineering, Wireless and Photonic Networks Research Centre of Excellence (WiPNET), Universiti Putra Malaysia, Selangor, MalaysiaDepartment of Computer System Engineering, Faculty of Engineering and Information Technology, Arab American University at Palestine, Jenin, PalestineDepartment of Computer and Communication Systems Engineering, Faculty of Engineering, Wireless and Photonic Networks Research Centre of Excellence (WiPNET), Universiti Putra Malaysia, Selangor, MalaysiaDepartment of Computer and Communication Systems Engineering, Faculty of Engineering, Wireless and Photonic Networks Research Centre of Excellence (WiPNET), Universiti Putra Malaysia, Selangor, MalaysiaDepartment of Computer and Communication Systems Engineering, Faculty of Engineering, Wireless and Photonic Networks Research Centre of Excellence (WiPNET), Universiti Putra Malaysia, Selangor, MalaysiaIn this paper, the power transmission and energy efficiency (EE) in downlink multi-cell massive multiple-input-multiple-output (MIMO) systems are investigated and optimized. Most of the existing works do not take into account different user's quality of service (QoS) requirements. These models also depend on a fixed transmit power consumption, which cannot reflect the actual EE levels concerning QoS. Therefore, in this paper, a new base station (BS) transmit power adaptation is firstly introduced, termed the BSTPA method. The transmitted power is adapted to channel condition and user-level QoS including data rate requirement and maximum allowable outage probability to minimize the total BS radiated power. An analytical closed-form expression of the average BS transmit power adaptation is derived. Then, a corresponding iterative optimization algorithm is proposed to maximize the average EE per BS and obtain the optimal design parameters. The proposed optimization algorithm aims to globally achieve the optimal EE value with the optimal amount of data rate, the number of BS antennas, and users. Simulation results are demonstrated to verify our analytical findings. For a wide range of different design parameters, the results indicate that the proposed method obtains remarkably higher EE levels compared to the conventional scenario, particularly if per-antenna circuit power is very small. The optimization results show that the case with lower per-antenna circuit power can achieve about 4.5 times better EE gain than the case with higher per-antenna circuit power with 13.3% optimum data rate improvement.https://ieeexplore.ieee.org/document/9256345/Energy efficiency (EE)massive MIMOquality of service (QoS)base station (BS) transmit power
collection DOAJ
language English
format Article
sources DOAJ
author Vahid Khodamoradi
Aduwati Sali
Oussama Messadi
Asem A. Salah
Mohanad M. Al-Wani
Borhanuddin Mohd Ali
Raja Syamsul Azmir Raja Abdullah
spellingShingle Vahid Khodamoradi
Aduwati Sali
Oussama Messadi
Asem A. Salah
Mohanad M. Al-Wani
Borhanuddin Mohd Ali
Raja Syamsul Azmir Raja Abdullah
Optimal Energy Efficiency Based Power Adaptation for Downlink Multi-Cell Massive MIMO Systems
IEEE Access
Energy efficiency (EE)
massive MIMO
quality of service (QoS)
base station (BS) transmit power
author_facet Vahid Khodamoradi
Aduwati Sali
Oussama Messadi
Asem A. Salah
Mohanad M. Al-Wani
Borhanuddin Mohd Ali
Raja Syamsul Azmir Raja Abdullah
author_sort Vahid Khodamoradi
title Optimal Energy Efficiency Based Power Adaptation for Downlink Multi-Cell Massive MIMO Systems
title_short Optimal Energy Efficiency Based Power Adaptation for Downlink Multi-Cell Massive MIMO Systems
title_full Optimal Energy Efficiency Based Power Adaptation for Downlink Multi-Cell Massive MIMO Systems
title_fullStr Optimal Energy Efficiency Based Power Adaptation for Downlink Multi-Cell Massive MIMO Systems
title_full_unstemmed Optimal Energy Efficiency Based Power Adaptation for Downlink Multi-Cell Massive MIMO Systems
title_sort optimal energy efficiency based power adaptation for downlink multi-cell massive mimo systems
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description In this paper, the power transmission and energy efficiency (EE) in downlink multi-cell massive multiple-input-multiple-output (MIMO) systems are investigated and optimized. Most of the existing works do not take into account different user's quality of service (QoS) requirements. These models also depend on a fixed transmit power consumption, which cannot reflect the actual EE levels concerning QoS. Therefore, in this paper, a new base station (BS) transmit power adaptation is firstly introduced, termed the BSTPA method. The transmitted power is adapted to channel condition and user-level QoS including data rate requirement and maximum allowable outage probability to minimize the total BS radiated power. An analytical closed-form expression of the average BS transmit power adaptation is derived. Then, a corresponding iterative optimization algorithm is proposed to maximize the average EE per BS and obtain the optimal design parameters. The proposed optimization algorithm aims to globally achieve the optimal EE value with the optimal amount of data rate, the number of BS antennas, and users. Simulation results are demonstrated to verify our analytical findings. For a wide range of different design parameters, the results indicate that the proposed method obtains remarkably higher EE levels compared to the conventional scenario, particularly if per-antenna circuit power is very small. The optimization results show that the case with lower per-antenna circuit power can achieve about 4.5 times better EE gain than the case with higher per-antenna circuit power with 13.3% optimum data rate improvement.
topic Energy efficiency (EE)
massive MIMO
quality of service (QoS)
base station (BS) transmit power
url https://ieeexplore.ieee.org/document/9256345/
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