After this, we used the best location information to install BSs and conducted the experiment results in terms of energy consumption. The results are shown in Fig. 3. As shown in Fig. 3 b, GA-based optimization has a better energy efficiency (10–29% power saving percentage) than either DE or the legacy system (LS).
With the rapid growth of 5G technology, the increase of base stations not noly brings high energy consumption, but also becomes new flexibility resources for power system. For high energy consumption and low utilization of energy storage of base stations, the strategy of energy storage regulation of macro base station and sleep to
There are two main methods of base station (BS) energy saving, including hardware and software. For hardware energy saving, it is mainly achieved by base station equipment
No doubt that power consumption is one of the most important challenges which face the modern mobile networks. These modern networks do a nice job in multimedia services. Then, the physical downlink data transmission rate will change the Base Station (BS) power consumption. The Conventional BS (CBS) of the cellular legacy networks
Lots of works on sleep control of BSs existed. For example, the work in [22] derived the energy-optimal density of BSs in wireless cellular networks with sleep modes under a given user density and performance constraint. The work in [19] investigated an energy-efficient BS switching-off and cell topology mechanism in both macrocellular
2. Wireless network energy consumption The typical wireless network can be viewed as composed by three different sections: the Mobile Switching Center (MSC), that take care of switching and interface to fixed network;
Historically, densification of networks has implied higher energy expenditure which can add up to a significant part of operator expenses. This, in turn, can place restraints on the number of base stations in the networks. 5G New Radio (NR) is designed to enable denser network deployments and simultaneously deliver increased
The widespread application of 4G and the rapid development of 5G technologies dramatically increase the energy consumption of telecommunication base station (TBS). Remarkably, the air conditioning system accounts for a significant part of energy consumption in TBS. In this work, passive radiative sky cooling technology has
5G communication technologies are expected to provide high rate and low delay services. To meet the requirements, more base stations (BS), including macrocell BS (MacBS) and microcell BS (MicBS), have to be deployed. In this dense multi-tier heterogeneous networks, the user quality of service (QoS) can be significantly improved
Artificial intelligence technology plays an important role in 5G base station energy-saving and will effectively reduce the OPEX cost of operators and improve the market
The paper aims to provide an outline of energy-efficient solutions for base stations of wireless cellular networks. A total of 5722 studies have been figured out by using the
The base station will be serving the user environments that tend to overlap the nearby base stations area. Therefore, making the other base station to remain in a sleep state, and save the base stations energy. A binary particle swarm optimization is formulated for solving this approach to save the base stations energy.
Traditional base station energy-saving technologies are analyzed. The prospect of 5G base station energy-saving technology combined with AI technology is explored. The development direction of AI energy-saving technology has been deeply studied. The AI energy saving model and the AI-based collaborative energy saving scheme are
For high energy consumption and low utilization of energy storage of base stations, the strategy of energy storage regulation of macro base station and
Traditional cooling equipment of data centers is a computer room air conditioner (CRAC) based on mechanical vapor compression refrigeration. Its energy consumption takes up around 30–50% of the total consumption of data centers [6], [7], [8]. An example of data center energy split is shown in Fig. 1[7].
In the outdoor daily temperature range of 24–28, 28–32, 32–36, 36–40, the energy saving rate of the unit is 67.3 %, 65.2 %, 39.6 %, 6.9 %, respectively, which reduces the energy consumption of the communication base station cooling system to
In Chinese telecommunication base stations, the air conditioning energy consumption is almost 47% of the total energy consumption. However, air-to-air thermosyphon heat exchangers can be used in winter, early spring and late autumn to cool the buildings using the outdoor ambient air to significantly decrease the power consumption.
It unites the three disciplines of computer science, physiology, and philosophy, which cover a wide range of topics from expert systems (2021) FG-AI4EE D.WG3-02. Smart energy saving of 5G base station: based on AI and other emerging technologies to
Furthermore, ZTE has developed multi-dimensional (time, space and frequency) base station energy saving software technologies, comprehensively reducing power consumption of 5G base stations. Moving forward, ZTE will keep close collaboration with China Unicom to continuously innovate and build green 5G networks. ZTE is a
：. The explosive development of ICT (information and com-munication technology) industry has emerged as one of the major sources of world energy consumption. Therefore, this paper concerns about the BS (base station) energy saving issue, for most energy consumption of the communication network comes from the BSs and the core network.
The typical power consumption of 5G base station. is about 3500 watts, which is 2 - 3 tim es of 4G base station. The annual power consumption of single. macro station is as high as 2.00 -3.38
This paper introduces the basic energy-saving technology of 5G base station, and puts forward the intelligent energy-saving solutions based on artificial intelligence (AI) and big data technologies to forecast and optimize the management of 5G wireless network energy consumption. With the continuous innovation and evolution of 5G energy-saving
Data centres (DCs) and telecommunication base stations (TBSs) are energy intensive with ∼40% of the energy consumption for cooling. Here, we provide a comprehensive review on recent research on energy-saving technologies for cooling DCs and TBSs, covering free-cooling, liquid-cooling, two-phase cooling and thermal energy
A popular technology for base station energy-saving with AI is to formulate radio frequency shutdown strategies based on the results of the base station load prediction model and multi-cell coordination judgment. So it is necessary to study related methods for improving the accuracy of results. This paper proposes a solution from the perspective of data
saving technol ogy of 5G base station, com bines the Intern et. of things technolo gy, collects netw ork data with the suppo rt. of sensors, and const ructs a central ized dynamic slee p. method
The increases in power density and energy consumption of 5G telecommunication base stations make operation reliability and energy-efficiency more important. In this paper, a novel type of rack-level hybrid cooling system which combines a thermosyphon loop with a mechanical refrigeration loop was developed and applied in
This document contains Version 1.0 of the ITU-T Technical Report on "Smart energy saving of 5G base station: Based on AI and other emerging technologies to forecast and optimize the management of 5G wireless network energy consumption" approved at the ITU-T Study Group 5 meeting held online, 11-20 May 2021. Editor:
Green Cellular Network A tremendous amount of energy is consumed to operate 362 the base stations in a conventional cellular network. Green cellular network is 363 vital for GMCC [53, 54] .
This paper proposes a SOM + Kmeans two-stage clustering algorithm to adaptively cluster the daily load curve of 5G base stations and use silhouette
This paper introduces the basic energy-saving technology of 5G base station, and puts forward the intelligent energy-saving solutions based on artificial intelligence (AI) and
In this study, two energy-saving retrofit plans, a computer room air handler system with water-side economizer (Plan 1) and a loop thermosyphon system
Change Log. This document contains Version 1.0 of the ITU-T Technical Report on "Smart Energy Saving of 5G Base Station: Based on AI and other emerging technologies to forecast and optimize the management of 5G wireless network energy consumption" approved at the ITU-T Study Group 5 meeting held online, 20th May, 2021.