Sustainable Connections: Exploring Energy Efficiency in 5G Networks

Although 5G networks offer larger capacity due to more antennas and larger bandwidths, their increased energy consumption is concerning. This paper investigates energy consumption issues from widespread 5G deployment using city-scale real-world mobile network data. Our dataset includes traffic volume, energy consumption, and base station attributes spanning May 2022, July 2023, and April 2024, covering over 10,000 4G and 5,000 5G base stations. A portion of the dataset is published on GitHub. We develop high-accuracy models to profile 4G and 5G base station energy consumption, revealing 5G inefficiencies under low traffic loads. We identify energy efficiency traps where network energy efficiency drops post-5G deployment. Our study estimates the recovery time from energy efficiency traps, emphasizes that different functional regions have varying recovery levels, and analyzes the reasons for these differences. We provide recommendations for deploying and commercializing 5G to promote sustainable connectivity.

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Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1145/3680121.3697806
Citations
2
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
0.42
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article

Sustainable Connections: Exploring Energy Efficiency in 5G Networks

Schahram Dustdar, Yangzhou Du, Yong Li, Tong Li et al.
2 citations
Advanced MIMO Systems Optimization
0.42
article

Sustainable Connections: Exploring Energy Efficiency in 5G Networks

Schahram Dustdar, Yangzhou Du, Yong Li, Tong Li, Zhaocheng Wang, Y.J. Ma
article en
2 citations

Abstract

Although 5G networks offer larger capacity due to more antennas and larger bandwidths, their increased energy consumption is concerning. This paper investigates energy consumption issues from widespread 5G deployment using city-scale real-world mobile network data. Our dataset includes traffic volume, energy consumption, and base station attributes spanning May 2022, July 2023, and April 2024, covering over 10,000 4G and 5,000 5G base stations. A portion of the dataset is published on GitHub. We develop high-accuracy models to profile 4G and 5G base station energy consumption, revealing 5G inefficiencies under low traffic loads. We identify energy efficiency traps where network energy efficiency drops post-5G deployment. Our study estimates the recovery time from energy efficiency traps, emphasizes that different functional regions have varying recovery levels, and analyzes the reasons for these differences. We provide recommendations for deploying and commercializing 5G to promote sustainable connectivity.

TU Wien (AT), Tsinghua University (CN)
Affordable and clean energy
Openalex Percentile: Top 36%
Advanced MIMO Systems Optimization
0.42
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Sustainable Connections: Exploring Energy Efficiency in 5G Networks — Schahram Dustdar, Yangzhou Du, et al. · (2024) | TGRS Research Map | TGRS