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5G-Advanced 减少能源使用3GPP 第 18 版中 RAN 节能的基本指南.pdf
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5G网络优化指导
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Reducing energy use
with 5G-Advanced
The essential guide to RAN energy savings in 3GPP Release 18
White paper
Daniela Laselva and Mads Lauridsen
2
White paper
Reducing energy use with 5G-Advanced
Contents
Executive summary 3
Introduction 5
How 5G-Advanced enhancements reduce RAN energy use 6
On RAN energy use 6
RAN energy saving techniques in 3GPP Release 18 7
Techniques to enable more cell sleep opportunities 9
Techniques to enable more energy-ecient data transfer 11
3GPP-dened 5G base station power consumption model 13
Performance evaluation 15
Recommendations 17
Outlook for RAN energy savings in 3GPP Release 19 19
Summary and outlook 20
Abbreviations 21
References 22
3
White paper
Reducing energy use with 5G-Advanced
Executive summary
Communications service providers strive to provide coverage, capacity and superior service quality while
facing the challenges of ever-increasing trac volumes, carbon neutrality targets, and higher costs of
energy. Reducing the energy use of mobile networks to address these challenges is an urgent imperative.
The eorts from the industry primarily revolve around the radio access network (RAN), which has the
greatest impact as it consumes over 80% of mobile network energy. Nokia is making a continuous eort
to decrease RAN energy consumption and improve the energy eciency using the many available levers
and measures: from network modernization and renewable energy sourcing solutions to advanced energy-
saving features across the entire product portfolio.
As the radio technology strongly inuences the ability to minimize energy use, Nokia is also actively engaged in
the 3GPP standardization of new enablers in 5G-Advanced. These enablers are designed to facilitate
dynamic energy-saving techniques for 5G base stations (gNBs). The objective is to reduce gNB energy use
by operating the radios more eciently than today without compromising service quality. The key techniques
of 5G-Advanced allow the gNB to adapt active antennas, transmission power and time resources to
changes in trac load and end users’ QoS needs. Specically, these techniques allow adaptations to be
more dynamic and at a more granular level than in today’s networks. Further, they can use enhanced
feedback from the device to determine the optimal adaptation to be applied by the network. Base station
hardware can then be deactivated when the load decreases and quickly reactivated when the load increases
again, in turn reducing energy use especially during the often occurring low-to-medium load scenarios.
Nokia has been a key contributor to dene and assess the network energy-saving (NES) techniques of
5G-Advanced for their potential energy-saving gains and user throughput performance impact. As an
essential tool for the evaluation, within the 3GPP, we have dened a common evaluation methodology and,
for the rst time, a gNB power consumption model.
In this white paper, we examine the 5G RAN energy-saving techniques introduced in 3GPP Release 18,
describe how these can strengthen the broad energy-saving toolbox oered by Nokia, and provide
recommendations on their use. Dynamic adaptations of transmission power and antennas improve the
energy eciency of the base station transmissions the most and obtain 15–30% energy savings under
low-to-medium cell load levels. When looking at a daily average load, these techniques when jointly
used also provide the best tradeos between energy savings and throughput impact. The summary of
the network energy-saving gain and throughput impact obtained by the four key techniques of Release
18 standalone as well as the joint use of antenna and power adaptation (see results in the light blue)
is provided in Figure 1 for dierent cell load levels. In general, these techniques must be applied with a
careful design to mitigate the throughput loss they may cause.
This white paper concludes with our view on the anticipated additional energy-saving techniques that may
be expected beyond Release 18.
4
White paper
Reducing energy use with 5G-Advanced
Figure 1. Performance of the key Release 18 NES techniques standalone, and joint antenna and
power adaptation (light blue background) at dierent load levels in terms of NES gain and user perceived
throughput loss
1
0%
5%
10%
15%
20%
25%
30%
35%
40%
0% 5% 10% 15% 20% 25% 30% 35% 40%
User perceived throughput loss (UPT) (%)
Network energy-saving (NES) gain (%)
Low load (0 %) Medium load (20-30 %) Busy hour (40-50 %)
ETSI daily average
Cell
discontinuous
transmission
(cell DTX)
Antenna adaptation
(5 W/Antenna)
64 Tx (55 dBm)
to 32 Tx (52 dBm)
Joint antenna &
power adaptation
64 Tx 55 dBm
to 32 Tx 55 dBm
PDSCH power adaptation
for 64 Tx
5 w/antenna to [0.625-2.5]
w/antenna
SSB-less SCell in FR1 inter-band CA
1 The results are based on the 3GPP-dened base station power consumption model and performance evaluation methodology [14].
5
White paper
Reducing energy use with 5G-Advanced
Introduction
Energy consumption is one of the key metrics closely monitored by companies of every industry. It
impacts costs and, in turn, protability and is also critical in meeting commitments to reduce greenhouse
gas emissions. Market expectations for most publicly traded companies are to meet ESG (Environmental,
Social, Governance) criteria. Communications service providers (CSPs) and enterprises using wireless
networks are no exception. In the journey towards net-zero emissions, many of them have set targets to
be ‘carbon neutral’ or ‘climate neutral’ in the next decades for both Scope 1 and 2 (covering respectively
direct and indirect CO
2
emissions from purchased electricity, heating, and cooling) [1]. At the same time,
energy prices have been following an increasing trend [2], which is putting pressure on CSPs’ prot
margins, energy being one of the main cost components of the CSPs’ OPEX (operational expenses)
representing 20–25% share [3].
Since about 95% of mobile radio network product life cycle emissions occur while in use, minimizing energy
consumption during product operation is the key to achieving reduction of both emissions and OPEX. In
current mobile networks, most of the energy is consumed by the radio access network (RAN). According
to the latest GSMA report, 87% of the energy of the operators surveyed is consumed by their RANs. The
core network and data centers consume 12% and other operations account for the remaining 1%. Thus,
minimizing energy use in the RAN is the key to improving protability and achieving climate targets.
Minimizing energy use is critical also for 5G base stations. Despite being able to improve energy eciency
(bits/Joule) by up to 20 times as compared to 4G [4], 5G base stations contribute to electricity bills and
actions towards mitigating their energy consumption are required. Particular attention should be paid to
making the operations of power-hungry massive MIMO (mMIMO) radios more energy ecient during all load
scenarios.
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