Estimating Base Station Power Consumption Using Regression
Apr 1, 2019 · In this paper, we present a regression-based power consumption estimation method based on voice and data traffic provided by base stations with 2G and 3G capabilities. Our
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Apr 1, 2019 · In this paper, we present a regression-based power consumption estimation method based on voice and data traffic provided by base stations with 2G and 3G capabilities. Our
May 22, 2023 · We propose an optimal selection method for 5G base station data to achieve high-accuracy positioning estimation in indoor and outdoor environments. The proposed method is
Jun 18, 2024 · Abstract A novel method based on machine learning is proposed to estimate the electromagnetic radiation level at the ground plane near fifth‐generation (5G) base stations.
Sep 16, 2013 · We provide a parameterized linear power model which covers the individual aspects of a BS which are relevant for a power consumption analysis, especially the
Oct 23, 2024 · To this end, we first derive the closed-form expression of the average received signal power in terms of the deterministic base station (BS)-IRS-user cascaded channels over
Jun 1, 2015 · A new power estimation method is proposed for base station (BS) in this paper. Based on this method, a software platform for power estimation is developed. The
This project aims to predict energy consumption in 5G base stations using Supervised Learning Regression techniques. The goal is to model and estimate the energy consumed by different
Sep 27, 2023 · Joint Azimuth, Elevation and Delay Estimation for Single Base Station Localization in 3D IIoT September 2023 Applied Sciences 13
Jun 28, 2016 · Power Outage Estimation and Resource Dimensioning for Solar Powered Cellular Base Stations Vinay Chamola and Biplab Sikdar Abstract—One of the major issues in the
Jun 12, 2025 · One base station is configured with one operator''s three cells (1 BBU + 3 AAU). Assuming that the power consumption of 5g BBU is 350W and that of AAU is 1100W, relevant
In this paper, we present a regression-based power consumption estimation method based on voice and data traffic provided by base stations with 2G and 3G capabilities.
May 1, 2015 · The proposed method models power consumption on different abstraction levels by splitting a typical base station into several basic components at different levels in the view of
Jun 1, 2024 · A novel method based on random forest regression model for estimating the radiation level at the ground plane near 5G base stations is proposed. The key features for
Oct 1, 2021 · In this study, the idle space of the base station''s energy storage is used to stabilize the photovoltaic output, and a photovoltaic storage system microgrid of a 5G base station is
Aug 23, 2023 · Wireless propagation models play a significant role in the deployments of base stations that are used to the reference signal receiving power (RSRP) of signal receivers in a
Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption
Oct 29, 2024 · Paper proposes a base station sleep method that reduces the power consumption of a cluster of base stations by deactivating the base station with minimum traffic
Recently, with the commercialization of 5G, a new electromagnetic field (EMF) evaluation methods is need. However, conventional EMF evaluation methods are only based on
Jan 23, 2023 · In this paper, we present a power consumption model for 5G AAUs based on artificial neural networks. We demonstrate that this model achieves good estimation
Mar 1, 2024 · In this paper, a comprehensive strategy is proposed to safely incorporate gNBs and their BESSs (called “gNB systems”) into the secondary frequency control procedure. Initially,
Aug 1, 2023 · The 5G BS power consumption mainly comes from the active antenna unit (AAU) and the base band unit (BBU), which respectively constitute BS dynamic and static power
Jul 29, 2020 · In this article, a simple formula for estimating the power density from a base station for a compliance assessment is proposed. One of the most popular methods for estimating the
This research paper will fill this research gap by developing an Artificial Intelligence-based method to estimate EM radiation levels from GSM base Stations using real traffic data of the network.
In this paper we present how computer simulation can be used to estimate the mean output power and the probability cumulative distribution function of one base station output power in GSM.
Jul 29, 2022 · The ubiquity, large bandwidth, and spatial diversity of the fifth-generation (5G) cellular signal render it a promising candidate for accurate positioning in indoor environments
Only few works were focusing on the estimation of the energy based on transmitted energy, and fewer relating the former to traffic. In this paper, we present a regression-based power
Apr 21, 2024 · The dormancy technology of 5G base stations (gNBs) can achieve rapid power reduction in millisecond timescale, making it ideal potential demand response resource for
Apr 21, 2025 · By installing many base stations in strategic locations that operate in the millimeter-wave range, 5G services are able to meet serious demands for bandwidth. To evaluate the
In recent years, many models for base station power con-sumption have been proposed in the literature. The work in proposed a widely used power consumption model, which explicitly shows the linear relationship between the power transmitted by the BS and its consumed power.
The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption.
The estimation of available power can be modeled as a linear programming problem that uses the predictive model in (29). Specifically, we estimate the BESS available power P e s s a v i when r g p = 0 and the total available power P c l u a v i when r g p = 1.
Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption.
The largest energy consumer in the BS is the power amplifier, which has a share of around 65% of the total energy consumption . Of the other base station elements, significant energy consumers are: air conditioning (17.5%), digital signal processing (10%) and AC/DC conversion elements (7.5%) .
Debaillie, C. Desset, and F. Louagie, “A flexible and future-proof power model for cellular base stations,” in IEEE 81st Vehicular Tech-nology Conference (VTC Spring), 2015, pp. 1–7. S.