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17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.7.2 Pre-conditions | The network Operator deploys 5G NPN network in industrial park to provide energy as a service “GreenPark” for the industry park customer M. The “GreenPark” service can provide high data rate communication service and higher reliability service either. The industry customer M has subscribed the high data rate service with SLA “H”. The network Operator also provides a replaceable SLA “E2H” which can be used during off-peak working time. This replaceable SLA can reduce energy consumption by changing the energy state of a cell, a network element and/or a network function belong to the 5G NPN (e.g. to “energy saving” state), and the action can be activated either by pre-configured policy or by notification from customer M. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.7.3 Service flows | 1. Customer M asks the “GreenPark” Operator to provide the “GreenPark” energy consumption information and its communication services network performance statistic information (e.g. the data rate, packet delay and packet loss) per hour during the working time (e.g. from 9am to 5pm) in the industrial park.
2. The operator acquires the energy consumption information of the 5G NPN serving customer M every hour.
3. At the same time, operator collects the network performance statistic information (e.g. average data rate, average packet delay and average packet loss) from the 5G NPN serving customer M every hour.
4. The operator provides the energy consumption information of the 5G NPN serving the customer M and the network performance statistic information from the 5G NPN e.g. the average data rate, average packet delay and average packet loss during the working time in the industrial park.
5. According to the pre-configured policy with customer M, the Operator changes the energy state of the 5G network functions of the 5G NPN serving customer M for energy saving. The operator continues to acquire the energy consumption information and collects the network performance statistic information from the 5G NPN under new energy state and provides this information together to the customer M. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.7.4 Post-conditions | Customers M can get the not only the energy consumption information but also the average data rate, average packet delay and average packet loss from 5G NPN during the working time and off-peak working time. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.7.5 Existing features partly or fully covering the use case functionality | The QoS monitoring requirements have been specified in the TS22.261 section 6.23. But it has not any consideration on energy consumption. Some related requirements are listed below:
The 5G system shall be able to provide real time QoS parameters and events information to an authorized application/network entity.
NOTE 2: The QoS parameters to be monitored and reported can include latency (e.g. UL/DL or round trip), jitter, and packet loss rate.
The 5G system shall support different levels of granularity for QoS monitoring (e.g. per flow or set of flows)
The 5G system shall support an update/refresh rate for real time QoS monitoring with a specified value (e.g., at least one update per second)
In TR 28.829 [25], there are solutions of collect network information of energy utility via OA&M.
In TR28.913 [26], section 4.6, the key issue is to add reliability KPI into the URLLC network slice energy efficiency formula. In this key issue, the energy efficiency is calculated in the 3GPP domain, the related information is not exposed together to external. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.7.6 Potential new requirements needed to support the use case | [PR.5.7.6-1] Subject to Operator policy and consent by the customer, the 5G system shall be able to collect and expose to the authorized third party, through same update rate e.g. hourly or daily, the energy consumption information for the network functions serving the customer, together with the network performance statistic information for the services provided by that network functions.
NOTE: The network performance statistic information could be the data rate, packet delay and packet loss, etc.
[PR.5.7.6-2] Subject to Operator policy, the 5G system shall provide means for the trusted 3rd party, to configure which network performance statistic information (e.g. the data rate, packet delay and packet loss) for the communication service provided to the customer, needs to be exposed along with the energy consumption information of the network functions serving the customer. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8 Use case on Application energy efficiency monitoring | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8.1 Description | Next generation mobile communication systems are expected to accommodate more demanding services, e.g., XR, AI/ML which will require much energy consumption at the device side as well as the network side. The impact on devices and the network to support these services will be huge and sometimes unpredictable.
When Operator A is deploying a communication service to meet the application service requirements (e.g. gaming app requirements), the customer (e.g. service provider or vertical) needs to make sure that the application service doesn’t consume significant energy for the end users as well as for the data network side.
Possible high energy consumption or low energy efficiency of the application service can lead to an application layer adaptation at the service provider’s domain to deal with this. An example of application layer adaptation would be to trigger the adaptation of the service level due to high expected energy consumption for the given application in a certain service area (e.g. edge service area).
The Application service Energy Efficiency (AEE) can be monitored and predicted at the 5GS and can be exposed as a monitoring event to the Service Provider to allow an application layer action. Such monitoring may relate to whether the AEE is sustainable for a given service area and time of the day, or can be provided when the energy consumption for the application service is reaching the upper bound (upper bound can be set based on the SLA). The monitoring result can be exposed either periodically or event-based (e.g. when upper threshold is reached as defined in Energy-related KPIs) subject to the application service provider’s requirement (based on the SLA). |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8.2 Pre-conditions | The service provider X wants to deploy an application service (e.g., gaming service) in a given service area and for a target number of users, where the service is expected to be communicated via 5G network “N” of the 5GS of operator A. The application service may have different service levels, which may be different KPIs associated with the service, and can correspond e.g., to different levels of automation or video quality targets.
The service provider X subscribes to the operator A for the “App EnergyEff Moni” feature with the requested service level(s) to monitor whether the application service is energy-efficient when using 5G system of operator A for the given service level(s).
The operator A and service provider X have agreed on certain energy efficiency target for the application service and optionally for given service levels. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8.3 Service flows | 1. Service provider X asks the “App EnergyEff Moni” of Operator A to provide the predicted application service energy efficiency information for App Service #1 and one or more service modes for a given service area and time of the day.
2. The 5G system of operator A acquires the energy consumption information of related 5G system functions serving the App Service #1 of service provider X. Such information can be derived per application service and can include statistical data related to the application service energy consumption within a given service area.
Then, the 5G system of operator A calculates or predicts the AEE for the application service #1 and optionally the service mode X, based on the acquired energy consumption information.
3. Operator A exposes the calculated or predicted AEE for the application service #1 (and optionally the service mode X) to the Service Provider X.
4. Service Provider X configures or adapts the application service parameters based on the Operator A feedback. Such adaptation of the application service parameters can be for instance the application server re-location to an edge data network to enhance the energy efficiency for the application. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8.4 Post-conditions | Service provider X can get the energy related statistics or predictions for the application service #1, independently from NG-RAN deployment scenarios, and this can help either adapting the application service parameters (e.g. service levels, application relocation) or configuring the application service in an energy-efficient manner. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8.5 Existing features partly or fully covering the use case functionality | EE TS 28.310 [6] specifies the work in 3GPP related to energy efficiency. It specifies use cases relating to energy efficiency such as switching off edges UPFs for low-latency communication in certain geographical areas when no user is actively using them. Based on the scenarios the document presents requirements to be considered to support energy efficiency. The main requirements among them are requirements related to Power, Energy and Environmental measurements as well as requirements concerning energy saving.
This use case uses the existing 3GPP features as input for the application-level energy efficiency prediction, without providing an overlapping capability. In particular, the energy monitoring and optimization tasks in OAM cannot consider per application / session energy monitoring/predictions, and are limited to the energy calculation and monitoring per managed element (e.g. NG-RAN, UPF, network slice...). |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8.6 Potential new requirements needed to support the use case | [PR.5.8.6-1] Based on operator policy and service agreement between the operator and application service provider, the 5G system shall be able to derive energy efficiency information for one or more application services, and expose energy efficiency information notifications to the application service provider.
NOTE: The granularity of energy efficiency information notifications could vary according to different situations, for example, application service energy consumption can be acquired based on means of averaging or applying a statistical model for the energy consumed by the application sessions within the application service in the service area, etc.
[PR.5.8.6-2] Based on operator policy and service agreement between the operator and application service provider, the 5G system shall be able to provide means to predict the energy efficiency per application service, and expose the predicted energy efficiency information to the application service provider.
[PR.5.8.6-3] Based on operator policy and service agreement between the operator and application service provider, the 5G system shall enable the application service provider to subscribe, update, and unsubscribe for energy efficiency information notifications.
5.9 Use case on renewable energy consumption information exposure |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.9.1 Description | According to a recent GSMA report [20], all major operators have set up targets to reduce carbon intensity from 50% to 70% in next couple of years with the ultimate goal of achieving net-zero emissions. Though 5G NR offers improved energy-efficiency, new 5G use cases and the wider adoption of 5G NR will result in an increased number of sites and antennas, which may offset these gains if left unmitigated.
To address this, cut down on emissions and increase network efficiency, operators have an interest in powering their network using renewable energy sources to reduce emissions and enhance network efficiency. It is also important for operators to understand and track the proportion of energy consumed in their networks that is sourced from renewable sources, which can be made available to customers and authorized third parties. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.9.2 Pre-conditions | The network operator R has deployed a 5G network "N" and is promoting its services as "Green Energy". This is due to the fact that 60% (this could be any % number, 60% is just provided as an example) of the energy required for network operations is sourced from renewable resources. The government is providing tax credits to companies using renewable energy, and R provides its customers with information about the proportion of renewable energy consumed and renewable energy certificates (RECs) [21], if applicable.
Company X, which places a high value on environmental sustainability, has subscribed to R’s Green Energy services requesting for minimum ratio of renewable energy used for the communication service. R provides X with a dedicated slice (or NPN) guaranteeing this minimum ratio. R provides periodic reporting information regarding the percentage of renewable energy consumed. As a result, X is eligible to receive tax credits from the government for its purchase of renewable energy. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.9.3 Service flows | 1. Customer X subscribes to the ‘Green Energy’ service for its warehouse, provided by operator R.
2. The warehouse is served by a limited “X” number of base stations and the core network could be hosted in a central cloud location that is powered by renewable energy.
3. Operator R provides a dedicated network slice that utilizes a minimum 80% renewable energy for customer X’s NPN at their warehouse. The 5G system will not actively monitor the dedicated resources for energy consumption.
4. Operator R periodically calculates statistics about the ratio of renewable energy consumption of the network elements used within the customer X’s dedicated slice (or NPN).
5. Customer X receives periodic report every month regarding the ratio of renewable energy consumption from Operator R.
6. Operator R supplies customer X with the requested information.
7. Customer X can advertise that it is committed to a “Green Energy” and is using 80% renewable energy for the dedicated communications service at its warehouse. Additionally, Customer X can also claim tax credits from the government. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.9.4 Post-conditions | Customer X can get a dedicated network slice or NPN utilizing a minimum ratio of renewable energy used by the network serving its warehouse.
Customer X receives a periodic report on the ratio of renewable energy used by the network serving its warehouse. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.9.5 Existing features partly or fully covering the use case functionality | None. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.9.6 Potential new requirements needed to support the use case | [PR.5.9.6-1] Subject to operator’s policy, the 5G system shall enable the operation of a dedicated network above a minimum ratio of renewable energy as requested by an authorized 3rd party.
NOTE 1: This requirement does not imply that the 5G system will actively monitor the dedicated resources.
[PR.5.9.6-2] Subject to operator’s policy, the 5G system shall be able to provide to a 3rd party the reporting of the ratio of renewable energy used to provide dedicated communication service to the 3rd party on periodic basis.
NOTE 2: The reporting period could be set, e.g., on monthly or yearly basis. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10 Use case on supporting carbon-aware communication service | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10.1 Description | Global warming caused by excessive emissions of GHG (Green House Gas, e.g., carbon dioxide) due to human activity (e.g., burning fossil fuels for electricity generation) is the main driver to climate change, which poses a significant threat to society and the environment. To achieve carbon neutrality, it is important to reduce the GHG incl. carbon emissions in the first place rather than offset them later. Recent advancements in communication capabilities of networks (e.g., 5GS) enables a wide range of services (e.g., AR/XR). However, the rising demand for communication services in turn triggers a rising demand for energy and a greater risk of an even higher resulting GHG footprint. 3GPP plays a crucial role in the ICT sector to enable the deployment of these technologies on a global scale and therefore must also play a central role in enabling a sustainable future.
The adoption of alternative sustainable sources of energy incl. renewable energy (e.g., solar, wind, hydropower, geothermy) and nuclear power could help offset the GHG footprint of energy generation based on fossil fuels, even though their corresponding environmental impact also need to be considered. From an ICT standpoint and, 3GPP system in particular, the energy used by network nodes can be from varied energy with different related levels of environmental impact incl. GHG emissions. Due to the highly variable and unpredictable nature of renewable energy sources (Mother Nature’s dictate), the average GHG emissions per consumed energy unit varies substantially by time and location. Hence, it is critical to take temporal and spatial dimensions of energy sources into account to provide communication services not only for a better traceability of the energy sources used but in turn for enabling a more sustainable energy use.
In the following use case, telecom operator provides the estimation of carbon emissions for the services.
Note that ADEME, the French Agency for Ecological Transition, has introduced a methodological standard for the environmental assessment of digital services. [24] According to this standard, “internet service providers and telecoms operators (physical and virtual) for fixed and mobile networks must inform their subscribers of the amount of data consumed and indicate the equivalent in greenhouse gas emissions.” The objective is to communicate on a monthly bill the carbon impact of a subscriber using the mobile network of operator 1 in <Month YEAR> with a consumption of <DV> GB is: <X> g CO2 eq. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10.2 Pre-conditions | Eva uses her XR device during the commute. This XR device receives 5G service from the mobile network operator A.
The 5G system operated by operator A is powered by both of renewable energy (e.g., solar energy) and non-renewable energy (e.g., coal).
Carbon intensity, defined as the quantity of CO2 equivalent emission per unit of final energy consumption for an operational period of use (e.g., gCO2 per kW·h), is used to estimate the amount of carbon emissions incurred by the 5G system operations. Such carbon intensity information can be collected from a third party.
The operator A offers a “carbon-aware communication service” which provides the estimated carbon emissions of communication services. The estimation is based on the subscriber’s data volume, the operator’s energy consumption and the carbon intensity of network. The estimated carbon emissions information is exposed to the service provider B. Users can acquire the estimated carbon emissions from the service provider B.
Eva loves our planet, so she prefers to know how her requested services produce carbon emissions. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10.3 Service flows | 1. Eva subscribes the communication service provided by operator A.
2. During the commute between the home and the workplace, Eva wears her XR device and enjoys the immersive entertainment via 5G system operated by operator A.
3. During the service time, the 5G system incurs carbon emissions due to the energy consumption.
4. The operator A collects the carbon intensity information of energy consumption from an authorized third party.
5. By "carbon-aware communication service”, the operator A calculates the estimated carbon emissions for the service and exposes the estimated carbon emissions result to the service provider B.
6. From the service provider B, Eva can know the estimation of carbon emissions for her requested service from the operator A. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10.4 Post-conditions | Eva can enjoy low-carbon XR entertainment with the awareness of its environmental impacts. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10.5 Existing features partly or fully covering the use case functionality | None. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10.6 Potential new requirements needed to support the use case | [PR.5.10.6-1] Subject to user consent, operator policy and regulatory requirements, the 5G system shall be able to provide a mechanism to expose to the authorized third parties the energy efficiency information (e.g., including the estimated carbon emissions) related to a subscriber based on the subscriber’s data volume over a specific period of time, the operator’s energy consumption, and the carbon intensity of operator’s network.
NOTE 1: The carbon intensity of operator’s network can be provided by an authorized third party and can vary based on locations.
NOTE 2: The granularity of reporting (e.g., per month) is not discussed in this study.
5.11 Use case on Temporarily pooling communication services over a geographical area for energy saving |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.11.1 Description | One of the strategies to save energy within mobile networks is to shut down some RAN nodes at times of low usage. Eventually only one communication service would be used. Thus, there is a potential for further gain to be exploited by pooling the communication service on a local basis among operators at times of low usage.
Agreements could be put in place between operators so that in the low load periods (e.g., night time) only one of multiple mobile networks may be active in an area and will provide communication service to the subscribers of all networks, whereas the other networks can apply cell shutdown of their own infrastructure to obtain network energy savings.
Alternatively, based on risks of power outage nationwide/regionwide, regulators could ask operators to “optimize” their coverage e.g., shutdown some nodes in overlapping coverage areas during energy peak hours and/or in specific geographical areas, whilst still guaranteeing minimum coverage/service (in particular emergency calls).
This can also apply between NPN operators and/or with PLMN operators. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.11.2 Pre-conditions | - OP1 and OP2 are two PLMN operators.
- There is an overlap coverage between OP1 and OP2, which both provide mobile communication services to their subscribers on various bands.
- There are mutual agreements between OP1 and OP2 allowing them to provide communication services to the subscribers of the other network, in case it is not active in an area for low load. They define e.g. on a daily basis or specific locations a time when the communication service pooling starts and ends, and can include other parameters like preferred bands etc.
- OP3 operates an NPN dedicated to a factory around its campus, which is mainly used for IIoT purposes, but also for employees.
- There is a business agreement between the OP1 and OP3, i.e. OP3 users can be served by OP1 network (but not the other way around) based on certain conditions. At night, OP3 shuts down its network when the machines are off, as the little remaining traffic is generated by some employees staying late or overnight. The agreement requests OP1 to provide access to OP3 UEs during the night hours for this type of traffic.
- UE 1 belongs to OP1. UE 2 belongs to OP2. UE 3 belongs to OP3. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.11.3 Service flows | Figure 5.11-1: Basic service scenario of communication service pooling for energy saving
1) At 8PM, OP3 (“beneficiary” network) starts informing its currently served UEs within a specific area that it will shut down its network and request them to move to OP1 (“donor” network). It can also indicate the time when it will resume connectivity (e.g. 8AM).
2) OP1 accepts OP3’s UEs onto its network based on “EE-based communication service pooling” reason (it wouldn’t have without agreement).
3) Once OP3 detects no UE is served anymore on its network, it shuts down its network
4) On the next morning at 8AM, OP3 powers up its network again in that area
5) OP3 UEs return to OP3
6) OP1 stop serving OP3 UEs.
Furthermore, as this is an industrial campus area, traffic for OP2 is low this Saturday (only OP3 factory is working). Based on its EE KPIs in that area and according to the agreement with OP1, OP2 decides to shut down its cells until Monday morning 6AM with the same mechanism. OP1 starts serving OP2 UEs under its own network during this time. In this case the decision is dynamic and not only based on fixed times, but on other conditions, within the agreed conditions between operators (e.g., anytime during weekends). |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.11.4 Post-conditions | After OP2 and OP3 have shut down their networks, their subscribers can still be served via OP1.
OP2 subscribers under “EE-based communication service pooling” are not charged differently when served by OP1 network, with respect to when they are under OP2 network coverage. OP2 may be charged by OP1 as per their company agreement, e.g. based on a flat cost, per subscriber, data volume, duration etc.
OP3 may also be charged by OP1 as per their company agreement. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.11.5 Existing feature partly or fully covering use case functionality | Network sharing is an existing technique used to save resources across operators (see in clause 6.21 of TS 22.261), which could be leveraged for “communication service pooling” for energy saving purposes.
However, current network sharing agreements are mainly on a permanent basis with little flexibility in time and space. Indirect network sharing is a promising technique that can be considered for this use case.
Minimization of Service Interruption (MINT) as defined in clause 6.31 of TS 22.261 in another existing feature, which has specified that “UEs can obtain service in the event of a disaster, if there are PLMN operators prepared to offer service. The minimization of service interruption is constrained to a particular time and place. To reduce the impact to the 5G System and EPS of supporting Disaster Roaming, the potential congestion resulting from an influx or outflux of Disaster Inbound Roamers is taken into account.”. Requirements exist, e.g., “to provide means to enable a UE to access PLMNs in a forbidden PLMN list if a Disaster condition applies and no other PLMN is available except for PLMNs in the forbidden PLMN list”.
Disaster roaming is further specified in clauses 4.4.3.3.1 and 3.10 of TS 23.122.
However, this use case is not related to disaster condition. Furthermore, differently from disaster roaming, there may be no detection of failure of home PLMN by the UE, and the pooling (i.e., roaming) duration may be known in advance. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.11.6 Potential new requirements needed to support the use case | [PR.5.11.6-1] Subject to regulatory requirements and operators’ policies, the 5G system shall support temporary pooling of communication services of multiple operators on a single operator within a geographical area.
NOTE 1: policies may include predefined times/locations, energy consumption/efficiency thresholds, preferred bands etc.
[PR.5.11.6-2] Subject to regulatory requirements and operators’ policies, the 5G system shall enable an operator providing communication service pooling to serve UEs of other operators.
[PR.5.11.6-3] Subject to operators’ policies, the 5G system shall enable a UE to display the subscriber’s home operator network name during communication service pooling, even when this UE is served by another operator.
[PR.5.11.6-4] The 5G system shall be able to support collection of charging information associated with a UE served using communication service pooling. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12 Use case on supporting communication service with best-effort renewable energy consumption | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12.1 Description | Climate change caused by excessive emissions of GHG (Green House Gas, e.g., carbon dioxide) due to human activity (e.g., burning fossil fuels for electricity generation) is the main driver to climate change, which poses a significant threat to society and the environment. Toward the goal of carbon neutrality, it is important to reduce the GHG incl. carbon emissions in the first place rather than offset them later. Recent advancements in cellular technologies (e.g., 5GS) that enable a wide range of applications has led to an explosive growth of service demands in networks. ICT sector is expected to account for 20% of the global energy consumption by 2040. 3GPP plays a crucial role in the ICT sector to enable the deployment of these technologies on a global scale and therefore must also play a central role in enabling a sustainable future.
To reduce the carbon footprint, telecom operators are utilizing more renewable energy (e.g., solar, wind) that does not release carbon dioxide when producing electricity. The energy used by network can be from varied energy with different related levels of environmental impact incl. GHG emissions. Due to the highly variable and unpredictable nature of renewable energy sources, the supply of renewable energy varies substantially by time and location.
In the following use case, telecom operator provides communication service considering the supply of renewable energy, in which operator utilizes renewable energy sources in a best-effort manner while ensuring the QoS levels of services to be met. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12.2 Pre-conditions | Eva has video calls with her family during the commute. She receives 5G service from the mobile network operator A.
The 5G system operated by operator A is powered by both of renewable energy (e.g., solar energy) and non-renewable energy (e.g., coal). The ratio of renewable energy is determined as the ratio of the power that is used from renewable energy sources as a percentage of total power usage in a given time unit. Calculation of ratio of renewable energy is done by means of averaging or applying a statistical model.
The operator A offers a “green communication service option” for which the supply of renewable energy is additionally considered during the provision of the services to users. If the green communication service option is determined to be enabled by the operator A, the operator A utilizes renewable energy sources in a best-effort manner while ensuring the QoS levels of services still be met.
The operator A monitors the supply of renewables in 5GS and the network operates on different ratios of renewable energy over time. The operator may also report to user the statistics of ratio of renewable energy for providing the requested communication service.
Eva loves our planet, so she subscribes the green communication service option which utilize as much renewable energy as possible without sacrificing the quality of serve for her video calls.
NOTE: This green service ensures that QoS level criteria continues to be met (i.e., there is no trade-off between energy efficiency and service quality) since the usage of renewable energy is just a best effort attempt. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12.3 Service flows | 1. During the commute, Eva has video calls with her family via the 5G system operated by operator A.
2. Eva subscribes the green communication service option provided by operator A, which ensures the QoS level of service to be met and utilize renewable energy sources in a best-effort manner.
3. The operator A monitors the supply of renewables for its 5G system, which varies substantially by time and/or location due to the highly variable and unpredictable nature of renewable energy sources.
4. During early morning, the operator A is able to provide communication service to Eva with 40% of ratio of renewable energy since solar power is plentiful and most of users don’t use services.
5. During the busy evening, many users request communication services at the same time, so the operator A is only able to provide communication service to Eva with 20% of ratio of renewable energy since the required energy consumption for network operation becomes more and the solar energy supply is decreasing.
6. Periodically, the operator reports to Eva the ratio of renewable energy for providing her communication service.
7. By "green communication service option” provided by operator A, the service requested by Eva use renewables as much as possible and Eva is still satisfied with the quality of video calls. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12.4 Post-conditions | Eva can enjoy video calls with the satisfied quality of service while reducing her carbon footprint. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12.5 Existing features partly or fully covering the use case functionality | None. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12.6 Potential new requirements needed to support the use case | [PR.5.12.6-1] Subject to user consent and operator’s policy, the 5G system shall be able to expose to a subscriber the ratio of renewable energy used for the subscriber’s dedicated communication service on periodic basis.
[PR.5.12.6-2] The 5G system shall be able to collect charging information associated with a subscribed service based on the ratio of renewable energy used for providing the service.
NOTE: Calculation of ratio of renewable energy as described in the preceding requirements is done by means of averaging or applying a statistical model. The requirements do not imply that some form of 'real time' monitoring is required. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13 Use case on energy as service criteria for 5G environment adaptation | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13.1 Description | It is becoming more important and challenging for operators and cloud/data service providers to reduce carbon emissions while providing for the best-in-class with optimal service plans to end-users. Many operators including cloud/data service providers run their services on top of multiple virtualized infrastructure environments with different hardware/software having various energy consumptions.
Often, operators are unaware of their own individual network functions’ power consumption or requirements, and how they behave with 5GS procedures for end-to-end service quality. Thus, operators should be able to measure and control their network functions with energy-based requirements.
In addition, individual network functions should be able to process, register, discover, select, load (re)balance and overload-control based on their current or predicted energy consumption. This would allow operators to fully control and optimize energy consumption internally, and/or based on various service plans for verticals and end-users. For example, using a ‘dynamic energy saving plan’ in mind, during a non-busy hour, the operator should be able to provide a service with a limited number of features, smaller capacity and/or relaxed SLA.
Figure 5.13-1: energy as service criteria for 5G environment adaptation |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13.2 Pre-conditions | 5G system supports individual network functions monitoring of energy consumption.
It also supports for registration, discovery, selection, load-(re)balance and overload-control of individual network functions based on their energy consumption. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13.3 Service flows | 1. David and John are subscribed to operator A with different service plans.
2. During operator’s A 5G service time over the 24 hours, depending on the number of subscribers and various service plans, the individual or groups of network functions are adapted, migrated and/or scaled based on their energy-efficiency requirements and plans.
3. Operator A has the ability to set their individual network functions to operate (e.g., for UE registration, NF selection, etc.) based on their current or predicted energy consumption.
4. By regularly measuring energy consumption of the individual network functions, operator A has the ability to fully optimize their energy savings whilst also maintaining a high service quality along with the time-of-the day. Based on how their network functions behave with energy-saving characteristics and controls, they can provide means to coordinate the operation of individual network functions to target global optimization of energy consumption within the 5G network. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13.4 Post-conditions | David is satisfied and enjoys his lower pricing plan with the awareness of carbon emission.
Operator A is also satisfied because it has the ability to manage (e.g., load balance) its network functions and adapt their procedures based on energy-saving characteristics. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13.5 Existing features partly or fully covering the use case functionality | None. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13.6 Potential new requirements needed to support the use case | [PR.5.13.6.1] Subject to operator policy and regulatory requirements, the 5G system shall be able to provide a mechanism for one or more network functions to operate based on energy consumption to meet various end-user’s service requirements.
[PR.5.13.6.2] Subject to operator policy and regulatory requirements, the 5G system shall be able to provide means to coordinate the operation of individual network functions to target optimization of energy consumption within the 5G network. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14 Use case on reducing GHG footprint of Application Services | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14.1 Description | Global warming caused by excessive emissions of GHG (e.g., carbon dioxide) due to human activity (e.g., burning fossil fuels for electricity generation) is the main driver to climate change, which poses a significant threat to society and the environment. To achieve carbon neutrality, it is important to reduce the GHG incl. carbon emissions in the first place rather than offset them later. Recent advancements in communication and computing capabilities of networks (e.g., 5GS, cloud services) enables offloading tasks to networked and distributed computing nodes (e.g., edge computing, cloud computing) for a wide range of services. However, the rising demand for such services in turn triggers a rising demand for energy and a greater risk of an even higher resulting GHG footprint. 3GPP plays a crucial role in the ICT sector to enable the deployment of these technologies on a global scale and therefore must also play a central role in enabling a sustainable future.
The adoption of alternative sustainable sources of energy incl. renewable energy (e.g., solar, wind, hydropower, geothermy) could help offset the GHG footprint of energy generation based on fossil fuels, even though their corresponding environmental impact also need to be considered. From an ICT standpoint and, 3GPP system in particular, the energy used by computing nodes in networks can be from varied energy with different related levels of environmental impact incl. GHG emissions. Due to the highly variable and unpredictable nature of renewable energy sources, the supply of renewable energy varies substantially by time and location. Hence, it is critical to take temporal and spatial dimensions of energy sources into account to accomplish compute tasks not only for a better traceability of the energy sources used but in turn for enabling a more sustainable energy use to achieve those tasks.
Up until now usually a system is designed to finish compute tasks as soon as possible (high throughput) and indicate results to the requester as soon as possible (low latency). However, some compute tasks have flexibility in both when and where they are executed, i.e., such type of workload could be executed in any computing node and tolerate some delays if the workload gets completed within certain given deadline. For example, some of AI/ML training, simulation, and video processing tasks might not require a quick response, which would allow flexibility to delay the execution of the related workloads in a computing node until, e.g., the utilized energy is deemed satisfactory in terms of GHG emissions. Such flexibility further allows to route workloads to a computing node using the (most) sustainable energy sources at that moment. As part of service, 3GPP system is able to execute compute tasks in a sustainable way by leveraging such flexibility.
In addition, consuming the renewable energy immediately when they are available, instead of storing them for the future use (e.g., in a big battery system), can also bring some economic benefits to operators or service providers, because this can reduce the cost and investment for scaling the energy storage system needed by the overall system.
In the following use case, by considering the temporal and spatial information of sustainable energy source and availability, the possibility of reduction of the GHG footprint for application services is explored. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14.2 Pre-conditions | The operator A provides the computing services through the computing nodes owned by itself or other third-party companies via certain Service Level Agreement (SLA), which execute the compute tasks (e.g., offloaded by users). Each computing node is powered by renewable energy (e.g., solar energy), non-renewable energy (e.g., coal) or both. The highly variable nature of renewable energy sources makes the resulting GHG emissions by each computing node varies considerably by time and location. The high cost of large-scale energy storage system (e.g., battery system) also brings the incentive to the operator to consume the renewable energy immediately when it is produced (e.g., to reduce the cost for building the needed battery system). The ratio of renewable energy measures the ratio of the power that is used from renewable energy sources as a percentage of total power usage in a given time unit.
NOTE: Computing node is the resource to execute compute tasks belong to service provider, e.g., computing node can be a Server node hosted by an Edge Computing Service Provider (ECSP) based on PLMN operator service agreement. Alternatively, ECSP and the PLMN operator can be part of the same organization.
Eva is an AI engineer who needs to train some AI/ML models for her research work. Eva has collected all the needed data (e.g., the images of cats and dogs) during the weekdays. To train this model, the required dataset must be sent to a computing node, and the node will train the specified model (e.g., a dog/cat classifier) over this dataset. Eva needs to get the training result at the beginning of workday next week. Her compute tasks for AI/ML model training are offloaded to the system owned by the operator A for execution.
The operator A offers a “green compute and communication service” which can decide when and where the offloaded tasks are computed to reduce the overall GHG footprint of the system. This green compute and communication service requires tolerated deadline of compute task specified by the user, i.e., the quality of experience is not degraded as long as the compute task is finished within the given deadline. Eva loves our planet, so she is using this service for reducing the GHG footprint of her research work. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14.3 Service flows | 1. Eva subscribes the green compute and communication service to save our planet.
2. Eva indicates to the operator A that the compute task needs to be finished before the next workday (8:00 AM on Monday).
3. Eva offloads the compute task of AI/ML model training to the system owned by the operator A before she left the office (7:00 PM on Friday) in New York.
4. In the operator A’s system, the "computing node NY" (i.e., the computing farm located in New York) is the closest computing resource to the Eva’s workplace. Traditionally the "computing node NY" is selected to execute Eva’s task immediately; however, there is no solar power in New York at this moment (i.e., the ratio of renewable energy is low).
5. If Eva’s AI/ML model is trained by the "computing node NY", it will result in some GHG emissions to the air which is not friendly to the environment.
6. Fortunately, the "green compute and communication service" has two alternative options for the execution of Eva’s compute task based on the ratio of renewable energy reported by the "computing node NY" and another node "computing node LA" located in Los Angeles:
◦ [Option 1: Greener Location] The "computing node LA" located in Los Angeles (is on 4:00 PM) having abundant solar energy at that moment (i.e., the ratio of renewable energy is high). The dataset can be sent to "computing node LA" and the results are sent back to Eva after the completion. Since the execution will not last over one day, the system can adopt this option even if it requires more time for the communications.
◦ [Option 2: Greener Time] The "computing node NY" will have plentiful solar energy during the period of 9:00 AM – 4:00 PM every day. The training executed during the daytime of the weekend will not generate any GHG emissions. Since the task can be finished before the next workday, the system can adopt this option to schedule the training to be executed during the weekend.
In addition, by consuming the renewable energy immediately when it is produced, the operator can reduce the scale of its renewable energy storage system and reduce the overall cost.
7. By adopting the either option provided by "green compute and communication" service, the execution of AI model training requested by Eva can be nearly carbon-free and Eva still obtains the desired training result before the deadline. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14.4 Post-conditions | Eva’s AI/ML model training is finished before the targeted deadline while protecting our beautiful planet.
Operator A reduces the scale of its renewable energy storage system and reduce the overall cost. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14.5 Existing features partly or fully covering the use case functionality | None. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14.6 Potential new requirements needed to support the use case | [PR.5.14.6-1] Subject to operator’s policy and agreement between an application service provider and operator, the 5G system shall support a mechanism for the application service provider (including edge computing service provider) to provide to the 5G system the current or predicted ratio of renewable energy used for providing application services on periodic basis.
[PR.5.14.6-2] Subject to user consent and operator policy, the 5G system shall provide a mechanism to support the selection of an application server (including edge application server) based on the ratio of renewable energy for providing application services.
NOTE: An application server (including edge application server) can be a server node hosted by an Edge Computing Service Provider (ECSP) based on PLMN operator service agreement. Alternatively, ECSP and the PLMN operator can be part of the same organization. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15 Use case on supporting communication service with carbon-aware service requirements | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15.1 Description | Climate change caused by excessive emissions of GHG (Green House Gas, e.g., carbon dioxide) due to human activity (e.g., burning fossil fuels for electricity generation) is the main driver to climate change, which poses a significant threat to society and the environment. Toward the goal of carbon neutrality, it is important to reduce the GHG incl. carbon emissions in the first place rather than offset them later. Recent advancements in cellular technologies (e.g., 5GS) that enable a wide range of applications has led to an explosive growth of service demands in networks. ICT sector is expected to account for 20% of the global energy consumption by 2040. 3GPP plays a crucial role in the ICT sector to enable the deployment of these technologies on a global scale and therefore must also play a central role in enabling a sustainable future.
One key approach for telecom operators to reduce their carbon footprint is utilizing more renewable energy (e.g., solar, wind) that does not release carbon dioxide when producing electricity. The energy used by network can be from varied energy with different related levels of environmental impact incl. GHG emissions. Due to the highly variable and unpredictable nature of renewable energy sources, the supply of renewable energy varies substantially by time and location.
In the following use case, telecom operator provides communication service with carbon-aware requirements considering the ratio of renewable energy and the subscriber’s preferences. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15.2 Pre-conditions | Eva watches videos during the commute. She receives 5G service from the mobile network operator A.
The 5G system operated by operator A is powered by both of renewable energy (e.g., solar energy) and non-renewable energy (e.g., coal). The ratio of renewable energy measures the ratio of the power that is used from renewable energy sources as a percentage of total power usage in a given time unit. Calculation of ratio of renewable energy is done by means of averaging or applying a statistical model.
The operator A offers a “green communication service option”, in which the service has adaptable QoS levels considering the ratio of renewable energy and the subscriber’s preferences, e.g., the operator A can provide a communication service with bit rate of 30Mbps and low ratio of renewable energy, which can be adapted to the service with bit rate is 10Mbps when high ratio of renewable energy is more desirable to the subscriber.
The operator A monitors the supply of renewables for its 5G system and adjust the operation of communication services. Following the pre-agreed QoS requirements with a subscriber, the operator A adjusts the communication services based on the supply of renewable energy.
Eva loves our planet, so she subscribes the optional green communication service. Therefore, the operator can determine to use a higher latency but greener network function entities (e.g., located in a faraway but powered by 80%+ renewable energy large scale computing/communication center) to provide services to Eva.
NOTE: This green service ensures that QoS level criteria continues to be met (i.e., there is no trade-off between energy efficiency and service quality) since all the adapted QoS levels are satisfied by the subscriber based on the pre-agreement. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15.3 Service flows | 1. During the commute between the home and the workplace, Eva watches videos via 5GS operated by operator A.
2. Eva subscribes the green communication service option provided by operator A. Following the pre-agreed QoS requirements with Eva, the operator A adjusts the communication services based on the supply of renewable energy. That is, Eva is satisfied with all the adapted QoS levels based on this agreement when watching videos.
3. The operator A monitors the supply of renewables for its 5GS, i.e., the ratio of renewable energy (i.e., the ratio of the power that is used from renewable energy sources as a percentage of total power usage).
4. During the daytime, since solar power of a remote computing/communication center is plentiful, Eva gets video streaming with bit rate of 10Mbps, and the service provided by operator A has 40% for the ratio of renewable energy.
5. During the busy evening time, since the supply of solar power is decreasing, Eva gets video streaming with bit rate of 25Mbps, and the service provided by operator A has 10% for the ratio of renewable energy.
6. By "green communication service option” provided by operator A, the service requested by Eva use renewable as much as possible and Eva is still satisfied with the video content. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15.4 Post-conditions | Eva can enjoy communication service with the satisfied quality of service while protecting our beautiful planet. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15.5 Existing features partly or fully covering the use case functionality | None. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15.6 Potential new requirements needed to support the use case | [PR.5.15.6-1] Subject to user consent and operator policy, the 5G system shall be able to provide means to adapt a communication service to fulfil the subscriber’s preference concerning the ratio of renewable energy used for providing the service.
NOTE: Calculation of ratio of renewable energy as described in the preceding requirement is done by means of averaging or applying a statistical model. The requirement does not imply that some form of 'real time' monitoring is required. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 6 Consolidated potential requirements | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 6.1 Energy consumption as service criteria | This subclause contains the requirements related to energy consumption as service criteria and supporting energy credit limit for specific service.
Table 6.1-1 – Consolidated requirements on energy consumption as service criteria
CPR #
Consolidated Potential Requirement
Original PR #
Comment
CPR 6.1-1
Subject to operator’s policy, the 5G system shall support subscription policies that define a maximum energy credit limit for services for services without QoS criteria.
NOTE 1: The definition of subscription is in TS 21.905.
P.R 5.5.6-1
Definition of subscription is in TS 21905
maximum energy credit limit: a policy establishing an upper bound on the quantity of energy used by the 5G system to provide services provided to a specific subscriber.(clause 3.1)
CPR 6.1-2
Subject to operator’s policy, the 5G system shall support a means to associate energy consumption with charging information based on subscription policies for services without QoS criteria.
P.R 5.5.6-2
Charging aspect
CPR 6.1-3
Subject to operator’s policy, the 5G system shall support a mechanism to perform energy credit limit control for services without QoS criteria.
NOTE 2: The result of the credit control is not specified by this requirement.
NOTE 3: Credit control [18] compares against a credit control limit. It is assumed charging events are assigned a corresponding energy consumption and this is compared against a policy of energy credit limit. It is assumed there can be a new policy to limit energy consumption allowed.
P.R 5.5.6-4
CPR 6.1-4
Subject to operator’s policy, the 5G system shall support a means to define and enforce subscription policies that define a maximum energy consumption for services without QoS criteria.
NOTE 4: The granularity of the subscription policies can either apply to the subscriber (all services), or to particular services.
PR 5.1.6-1,
PR 5.1.6-2
CPR 6.1-6
The 5G system shall provide a mechanism to include the ratio of renewable energy as part of charging information.
NOTE 5: Calculation of ratio of renewable energy as described in the preceding requirement is done by means of averaging or applying a statistical model. The requirements do not imply that some form of 'real time' monitoring is required.
PR.5.12.6-1,
PR.5.12.6-2
CPR 6.1-7
Subject to operator policy and agreement with 3rd party, the 5G system shall provide a mechanism to support the selection of an application server based on energy consumption information associated with a set of application servers.
NOTE 6: Energy consumption information can include ratio of renewable energy and carbon emission information when available. Calculation of ratio of renewable energy as described in the preceding requirement is done by means of averaging or applying a statistical model. The requirements do not imply that some form of 'real time' monitoring is required.
PR.5.14.6-2
CPR 6.1-8
Subject to user consent and operator policy, 5G system shall be able to provide means to modify a communication service based on energy related information criteria based on subscription policies.
NOTE 7: Energy consumption information can include ratio of renewable energy and carbon emission information when available. Calculation of ratio of renewable energy as described in the preceding requirement is done by means of averaging or applying a statistical model. The requirements do not imply that some form of 'real time' monitoring is required.
PR.5.15.6-1
CPR 6.1-9
Subject to user consent, operator policy and regulatory requirements, the 5G system shall be able to provide means to operate part or the whole network according to energy consumption requirements, which may be based on subscription policies or requested by an authorized 3rd party.
PR.5.9.6-1,
PR.5.13.6.1,
PR.5.13.6.2 |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 6.2 Different energy states of network elements and network functions | This subclause contains the requirements related to different energy states of network elements and network functions and dynamic changes.
Table 6.2-1 – Consolidated Requirements on different energy states of network elements and network functions
CPR #
Consolidated Potential Requirement
Original PR #
Comment
CPR 6.2-1
The 5G system shall support different energy states of network elements and network functions.
PR 5.2.6-1
CPR 6.2-2
5G system shall support dynamic changes of energy states of network elements and network functions.
NOTE 1: This requirement also include the condition when providing network elements or functions to an authorised 3rd party, the dynamic changes can be based on pre-configured policy (the time of changing energy states, which energy state map to which level of load, etc.)
PR 5.2.6-2
CPR 6.2-3
The 5G system shall support different charging mechanisms based on the different energy states of network elements and network functions.
PR 5.2.6-3
Charging aspect
NOTE 2: These requirements assume it is possible that there is new energy states of network elements and network functions. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 6.3 Monitoring and measurement related to energy consumption and efficiency | This subclause contains the requirements of monitoring and measurement related to energy consumption and efficiency.
Table 6.3-1 –Consolidated Requirements on monitoring and measurement related to energy efficiency
CPR #
Consolidated Potential Requirement
Original PR #
Comment
CPR 6.3-1
Subject to operator's policy, the 5G network shall support energy consumption monitoring at per network slice and per subscriber granularity.
NOTE 1: Energy consumption monitoring as described in the preceding requirement is done by means of averaging or applying a statistical model. The requirement does not imply that some form of 'real time' monitoring is required. The granularity of the subscription policies can either apply to the subscriber (all services), or to particular services.
PR 5.1.6-4
CPR 6.3-2
Subject to operator’s policy and agreement with 3rd party, the 5G system shall be able to monitor energy consumption for serving this 3rd party, independently from NG-RAN deployment scenarios.
NOTE2: The granularity of energy consumption measurement could vary according to different situations, for example, when several services share a same network slice, etc.
NOTE 3: The energy consumption information can be related to the network resources of network slice, NPNs, etc.
PR.5.3.6-1
PR.5.4.6-1
PR.5.6.6-1
CPR 6.3-4
Subject to operator policy and regulatory requirements, the 5G system shall be able to monitor the energy consumption for serving the 3rd party, together with the network performance statistic information for the services provided by that network, through same update rate e.g. hourly or daily,
NOTE 4: The network performance statistic information could be the data rate, packet delay and packet loss, etc.
PR.5.7.6-1 |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 6.4 Information exposure related to energy consumption and efficiency | This subclause contains the requirements related to information exposure related to energy consumption and efficiency.
Table 6.4-1 – Consolidated Requirements on information exposure related to Energy Consumption
CPR #
Consolidated Potential Requirement
Original PR #
Comment
CPR 6.4-1
Subject to operator’s policy and agreement with 3rd party, the 5G system shall be able to expose information on energy consumption forserving this 3rd party.
NOTE 1: Energy consumption information can include ratio of renewable energy and carbon emission information when available. The reporting period could be set, e.g., on monthly or yearly basis and can vary based on location.
NOTE 2: The energy consumption information can be related to the network resources of network slice, NPNs, etc.
PR.5.3.6-1
PR.5.4.6-1
PR.5.9.6-2
PR 5.10.6-1
CPR 6.4-2
Subject to operator’s policy, the 5G system shall support a means to expose energy consumption to authorized third parties for services, including energy consumption information related to the condition of energy credit limit (e.g. when the energy consumption is reaching the energy credit limit).
P.R 5.5.6-3
CPR 6.4-3
Subject to operator policy, the 5G system shall provide means for the trusted 3rd party, to configure which network performance statistic information (e.g. the data rate, packet delay and packet loss) for the communication service provided to the 3rd party, needs to be exposed along with the information on energy consumption for serving this 3rd party.
PR.5.7.6-2
CPR 6.4-4
Based on operator policy and agreement with 3rd party, the 5G system shall be able to expose energy consumption information and prediction on energy consumption of the 5G network per application service to the 3rd party.
PR.5.8.6-1
PR.5.8.6-2
CPR 6.4-5
Subject to operator’s policy and agreement with 3rd party, the 5G system shall support a mechanism for the 3rd party to provide current or predicted energy consumption information over a specific period of time.
NOTE 1: Energy consumption information can include ratio of renewable energy used for providing application services on periodic basis.
PR.5.14.6-1 |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 6.6 Temporary communication service pooling over a geographical area for energy saving | This subclause contains the requirements related to the temporary communication service pooling over a geographical area for energy saving.
Table 6.6-1 – Consolidated requirements on temporary communication service pooling over a geographical area for energy saving
CPR #
Consolidated Potential Requirement
Original PR #
Comment
CPR 6.6-1
Subject to regulatory requirements and operators’ policies, the 5G system shall enable an operator to temporarily serve UEs of other operators within a geographical area for the purpose of saving energy of the other operators.
NOTE 1: the other operators are assumed to stop providing communication service over their own network infrastructure within the same geographical area to save energy during that time.
NOTE 2: policies may include predefined times/locations, energy consumption/efficiency thresholds, etc.
NOTE 3: it is assumed that the 5G system can collect charging information associated with serving UEs of other operators
PR.5.11.6-1, PR.5.11.6-2,
PR.5.11.6-4 |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 7 Conclusion and recommendations | This document analyzes a number of use cases to support energy efficiency as service criteria. The resulting potential consolidated requirements have been captured in clauses 6. It is recommended to proceed with normative work based on the identified consolidated requirements. Annex A: Existing energy efficiency standardisation A.1 Overview of existing energy efficiency standardisation In ETSI, GSMA and 3GPP, there were many reports, studies, specifications related to energy efficiency. And now there are also ongoing 3GPP R18 studies on energy efficiency in both SA5 and RAN. In ETSI, existing specifications cover several aspects of energy efficiency, which include energy efficiency metrics and measurement methods for mobile core equipment, metrics and methods to measure energy performance of Mobile Radio Access Networks, measurement and monitoring of power, energy and environmental parameters for ICT equipment in telecommunications. [2] [3] GSMA has done lots of work in assessing energy consumption in different fields within a communication system. In "Going green: benchmarking the energy efficiency of mobile", GSMA states that 73% of the energy of the participating operators is consumed in the radio access network (RAN). The network core (13%), owned data centres (9%) and other operations (5%) account for the rest. [4] The statistics show that energy efficiency is an end-to-end issue. In 3GPP, energy efficiency has been studied in SA, SA5 and RAN. SA have studied system requirements and principles and provided an Energy Efficiency Control Framework. [5] SA5 has specified concepts, use cases, requirements and solutions for energy efficiency assessment and optimization for energy saving, as well as Energy Efficiency (EE) KPIs. [6] [7] RAN EE study has concentrated on the definition of network energy consumption models, evaluation methodology and KPIs, also studied and identified techniques on the gNB and UE sides to improve network energy savings in terms of both BS transmission and reception. [8] A.2 Energy efficiency KPIs 3GPP Energy Efficiency KPI definitions are under SA5 (Telecom Management) responsibility. They are based on measurements collected on RAN or CN network elements / network functions via OA&M. The KPI calculation is a generalisation of the work in ETSI TC EE. Figure A.2-1 below shows the KPI derivation with notes to the source specifications. Figure A.2-1: KPI derivation and sources A.3 Summary of existing energy efficiency standards Table A.2-1 below shows the standards relevant to the present document with a synopsis taken from the Scope clause of the standard. Table A.3-2: List of EE specifications SDO Group Standard Summary 3GPP SA TR 21.866: "Study on Energy Efficiency Aspects of 3GPP Standards" [5] Identifies and studies the key issues and the potential solutions in defining Energy Efficiency Key Performance Indicators and the Energy Efficiency optimization operations in existing and future 3GPP networks. 3GPP SA5 TS28.310: "Management and orchestration; Energy efficiency of 5G" [6] Specifies concepts, use cases, requirements and solutions for the energy efficiency assessment and optimization for energy saving of 5G networks. 3GPP SA5 TS28.552: "Management and orchestration; 5G performance measurements" [11] Specifies the performance measurements for 5G networks including network slicing. Performance measurements for NG-RAN are defined in this document, and some L2 measurement definitions are inherited from TS 38.314. The performance measurements for 5GC are all defined in this document. Related KPIs associated with those measurements are defined in TS 28.554 [12]. 3GPP SA5 TS28.554: "Management and orchestration; 5G end to end Key Performance Indicators (KPI)" [12] Specifies end-to-end Key Performance Indicators (KPIs) for the 5G network and network slicing 3GPP SA5 TS28.622: "Telecommunication management; Generic Network Resource Model (NRM) Integration Reference Point (IRP); Information Service (IS)" [13] Specifies the Generic network resource information that can be communicated for telecommunication network management purposes, including management data about energy efficiency 3GPP SA5 TR28.813: "Management and orchestration; Study on new aspects of Energy Efficiency (EE) for 5G" [7] Investigates the opportunities for defining new Energy Efficiency (EE) KPIs and new Energy Saving (ES) solutions. 3GPP RAN1 TR 38.864: "Study on network energy savings for NR" [8] Investigates network energy consumption modelling, techniques for network energy saving, evaluation of gains and impact. ETSI TC EE ETSI ES 203 228: "Environmental Engineering (EE); Assessment of mobile network energy efficiency" [3] Defines the topology and level of analysis to assess the energy efficiency of mobile networks (excluding terminal) ETSI TC EE ETSI ES 202 336-1: "Environmental Engineering (EE); Monitoring and Control Interface for Infrastructure Equipment (Power, Cooling and Building Environment Systems used in Telecommunication Networks) Part 1: Generic Interface" [9] Defines monitoring and control of Infrastructure Environment i.e. power, cooling and building environment systems for telecommunication centres and access network locations. ETSI TC EE ETSI ES 202 336-12: "Environmental Engineering (EE); Monitoring and control interface for infrastructure equipment (power, cooling and building environment systems used in telecommunication networks); Part 12: ICT equipment power, energy and environmental parameters monitoring information model" [10] Defines measurement and monitoring of power, energy and environmental parameters for ICT equipment in telecommunications or datacenter or customer premises Annex B: Change history Change history Date Meeting TDoc CR Rev Cat Subject/Comment New version 2022-08 SA1#99-e S1-222412 TR skeleton 0.0.0 2022-08 SA1#99-e Inclusion of approved pCRs from SA1 #99e: S1-222413: S1-222414: S1-222415: S1-222416 0.1.0 2022-11 SA1#100 Inclusion of approved pCRs from SA1 #100: S1-223431: S1-223654: S1-223656: S1-223657: S1-223658 0.2.0 2023-02 SA1#101 Inclusion of approved pCRs from SA1 #101: S1-230061: S1-230418: S1-230445: S1-230589: S1-230680: S1-230685: S1-230790: S1-230791: S1-230792: S1-230793 0.3.0 2023-03 SA#99 SP-230226 MCC clean-up presentation to SA#99 1.0.0 2023-05 SA1#102 Inclusion of approved pCRs from SA1 #102: S1-231179: S1-231180: S1-231277: S1-231531: S1-231532: S1-231533: S1-231540: S1-231543: S1-231550: S1-231552: S1-231553: S1-231770: S1-231771: S1-231772 1.1.0 2023-06 SA#100 SP-230519 MCC clean-up for approval by SA#100 2.0.0 2023-06 SA#100 SP-230519 Raised to v.19.0.0 by MCC following approval by SA#100 19.0.0 2023-09 SA#101 SP-231029 0007 D Quality improvements 19.1.0 2023-09 SA#101 SP-231029 0005 1 F Addressing EN 5.11 on pooling 19.1.0 2023-09 SA#101 SP-231029 0004 1 B Adding conclusion in TR 22.882 19.1.0 2023-09 SA#101 SP-231029 0006 2 F Consolidation of 5.11 PRs on pooling 19.1.0 2023-09 SA#101 SP-231029 0002 3 F Updating existing CPR in TR 22.882 19.1.0 2023-09 SA#101 SP-231029 0001 3 F Addition of terminolgy for energy consumption as a service criteria 19.1.0 2023-09 SA#101 SP-231029 0003 4 B Updating CPR with newly agreed PRs 19.1.0 2023-09 SA#101 SP-231029 0008 3 B Updating CPR with newly agreed PRs 19.1.0 2023-12 SA#102 SP-231414 0009 2 B Consolidation requirements update with leftover PRs 19.2.0 2024-03 SA#103 SP-240202 0011 1 D Editorial corrections in FS_EnergyServ 19.3.0 |
5eaf1b94c89939407995fc52470817be | 22.890 | 1 Scope | The present document analyses use cases of smart railway station such as station operation monitoring and control, passenger supporting services and evolution use cases of business and performance applications currently included in TR22.989 in order to derive potential requirements. |
5eaf1b94c89939407995fc52470817be | 22.890 | 2 References | The following documents contain provisions, which through reference in this text, constitute provisions of the present document.
- References are either specific (identified by date of publication, edition number, version number, etc.) or non‑specific.
- For a specific reference, subsequent revisions do not apply.
- For a non-specific reference, the latest version applies. In the case of a reference to a 3GPP document (including a GSM document), a non-specific reference implicitly refers to the latest version of that document in the same Release as the present document.
[1] 3GPP TR 21.905: "Vocabulary for 3GPP Specifications".
[2] UIC MG-7900v2.0.0, Future Railway Mobile Communication System – Use cases, Feb. 2020.
[3] UIC FU-7100v5.0.0, Future Railway Mobile Communication System – User Requirements Specification, Feb. 2020.
[4] TTA TTAK.KO-06.0507/R1, Requirements for Smart Railway Device - Information Model, Dec. 2020.
[5] TTA TTAK.KO-06.0508/R1, Requirements for Smart Railway Platform - Information Model, Dec. 2020.
[6] 3GPP TR 22.990. “Study on off-network for rail”.
[7] 3GPP TS 22.280: " Mission Critical Services Common Requirements (MCCoRe)"
[8] 3GPP TS 22.282: “Mission Critical (MC) data”.
[9] 3GPP TS 22.289: “Mobile communication system for railways”. |
5eaf1b94c89939407995fc52470817be | 22.890 | 3 Definitions and abbreviations | |
5eaf1b94c89939407995fc52470817be | 22.890 | 3.1 Definitions | For the purposes of the present document, the terms and definitions given in 3GPP TR 21.905 [1] and the following apply. A term defined in the present document takes precedence over the definition of the same term, if any, in 3GPP TR 21.905 [1].
Mobile Intelligent Assistant: 5G enabled robot with autonomous movements and artificial intelligence to support passengers in the Railway Smart Station.
Railway Smart Station: a train station where the 5G and other ICT technologies such as IoT and AI, are used for providing assisting railway services.
Zone: A 2-dimensional region of a pre-determined size.
Zone resolution: The pre-determined size of the given zone. |
5eaf1b94c89939407995fc52470817be | 22.890 | 3.2 Abbreviations | For the purposes of the present document, the abbreviations given in 3GPP TR 21.905 [1] and the following apply. An abbreviation defined in the present document takes precedence over the definition of the same abbreviation, if any, in 3GPP TR 21.905 [1].
AI Artificial Intelligence
FRMCS Future Railway Mobile Communication System
ITS Intelligent Transport System
IoT Internet of Things
MCX Mission Critical X, with X = PTT or X= Video or X= Data |
5eaf1b94c89939407995fc52470817be | 22.890 | 4 Overviews | The railway station is a major touchpoint to customers including passengers. The railway community is considering the Railway Smart Station services for the railway station operations and customers. Many railway companies are planning to adopt the Railway Smart Station services and some companies have already launched their own projects to provide such services over Mission Critical Services (MCPTT, MCVideo, MCData Services).
TR 22.889/989 provides basic requirements and focuses on the railway communication system having three categories critical, performance and business communications. While the critical and performance communications address the safe movement of trains, business communications provide value-added services for passengers. The Railway Smart Station services provide assistance of station operation and value-added services for passengers, e.g., subway station evacuation guidance via the passenger's UE.
The objectives of this technical report are as follows:
• Study use cases related to Railway Smart Station Services and deduce requirements from those. For example:
• Use cases of station operation monitoring and control
• Use cases of passenger supporting services
• Evolution use cases of business and performance applications currently included in TR22.889/989
• Analysis gaps between the requirements identified and the functionality already provided by 3GPP (e.g., 22.261, 22.228, or MCX specifications) |
5eaf1b94c89939407995fc52470817be | 22.890 | 5 Performance communication applications related use cases | |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.1 Emergency use case of smart station – fire in station | |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.1.1 Description | The fire in station use case is to describe an emergency situation and managing the situation in context of railway smart station. Through this use case work, technical keywords are deduced and numbers of potential requirements are come from the keywords. |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.1.2 Pre-conditions | Fire detectors are 3GPP UEs. The passengers have their own 3GPP UEs as their smart phone.
There is a fire situation in somewhere of a railway smart station. A fire detector senses the situation and report to railway smart station system via 3GPP network.
Some passengers also recognize and register the situation to the station system via railway smart station app in their 3GPP UEs and some of them notify it to the fire fighting force and/or police. |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.1.3 Service Flows | 1. The Railway Smart Station System indicates the fire situation from the fire detector. While the fire is getting bigger and bigger, the number of fire detectors providing sensing information is also increasing. The system indicates the location and directions of the fire spreading by analysing the information from the detectors.
2. The Railway Smart Station System starts a fire emergency protocol. It declares the situation to the near firehouses and police stations, and provides the station information via a specific interface that is not in scope of 3GPP, e.g. the station map. It finds available devices in the station and controls the devices to handle the situation. For example, the system controls fire sprinklers to start supress the fire efficiently. An evacuation warning and emergency exit information are announced to people in the station via the audio broadcasting devices. Emergency messages are sent to the people as well. The system controls emergency lamps and direction lights to give guidance information for evacuating the people.
3. The system notices the situation to the neighbour stations and the incoming trains. The trains make emergency stop at a safe place and evacuate their passengers. The system sends emergency protocol information to the railway workers in the station depends on their group roles in the protocol.
4. The system video-streams the fire site using a camera near the fire place. The people in the station could watch the streaming and get the information of the fire site, e.g. location and range of the site.
5. The system gets UEs information and sets up roles to UEs of the workers, firefighters and police officers, and downloads information on the UEs to support the role via interfacing the systems of the fire department and the police. The role is changed dynamically depends on the status of duty of the workers, firefighters and officers.
6. The system and the UEs of the people get cooperation to count the number of people in the station. The people is included in the rescue group autonomously. |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.1.4 Post-conditions | The devices in the station are monitored and controlled by the Railway Smart Station System.
The railway workers, firefighters, police officers are on their duty using their UEs.
The people in the station and the incoming train, escape the station and move to the safe place by using their UEs which are interfaced by the system. |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.1.5 Existing features partly or fully covering the use case functionality | The role and group management are fully covered by 3GPP system and MCX framework. |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.1.6 Potential New Requirements needed to support the use case | [PR-5.1.6-1] The 5G system shall support to access various networks which are used to monitor and control features for the devices in the station.
[PR-5.1.6-2] The 5G system shall support to connect massive number of devices in a specific area in the station, which is defined to monitor and/or control.
[PR-5.1.6-3] The 5G system should support to interface external system to control the UEs that belongs to the external system.
[PR-5.1.6-4] The 5G system should support counting number of UEs in a specific area in the station under the condition of category of UE and status of UE.
[Editor's note: The requirements are FFS.] |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.2 Multiple trains' stops at the same platform | |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.2.1 Description | It is needed to reduce train intervals to increase the track capacity. If the train intervals are less than some threshold, multiple trains should stop at the same platform. This is because we can reduce the interval between trains, but for safety reasons, reducing the time for passengers to get on and off and increasing the speed of trains entering the station is limited. In general, it takes more than 1 minute for the train to enter and exit the platform, including the time for passengers to get on and off, so if the train interval becomes shorter than 1 minute, there could be two trains on the platform.
The scenario when two trains stop at the same platform is as follows:
- The passenger information system (PIS) of a smart station displays that Train 1 will stop in front of the platform, and Train 2 will stop at the back of the platform. Train 1 & 2 may have different routes.
- Step 1: A previous train is departing the platform, and Train 1 enters the platform while a part of the previous train is still at the platform. According to the previous train's location, Train 1 slows down its speed and goes in front of the platform.
- Step 2: After the previous train left the platform, Train 1 stops in front of the platform.
- Step 3: While Train 1 is stopping for passengers to get on and off, Train 2 enters the platform
- Step 4: Train 2 stops behind Train 1 and opens its doors. While the passengers of Train 2 are getting on and off, Train 1 start to depart the platform.
Figure 6.2.1-1 Two trains' stops at the same platform |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.2.2 Pre-conditions | - Each train has at least one onboard UE (i.e., FRMCS UE), supporting both on-network and off-network communications.
- There is an edge server per station and the edge server can determine which platform trains stop and transmit/receive data to onboard UEs of Trains 1&2 through the 3GPP network.
- Each edge server can transmit/receive information to the PIS.
- Onboard UEs know the identities of the edge server on the train route. |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.2.3 Service Flows | 1. Train 1 is stopping at Platform A of the smart station, and Train 2 is approaching. Trains 1 & 2 are connected and authorized to transmit/receive information to the server at the smart station.
2. The server determines that Train 2 stops at Platform A. The server informs Train 2 of the platform where Train 2 will stop, the stop location within the platform, and the existence of Train 1 at the platform. Also, the server informs Train 1 that Train 2 will stop behind Train 1.
3. Train 2 establishes a connection with Train 1 through on-network and then notifies the server of the connection establishment with Train 1. Trains 1&2 can share information such as acceleration/deceleration, braking, location, etc., through the connection to stop at the same platform.
4. The server allows Train 2 to enter the platform.
5. For redundancy, Train 2 can add a connection with Train 1 through off-network before entering the platform.
6. Train 2 stops behind Train 1 at Platform A and opens its doors for passengers to get on and off. Train 1 starts to depart. |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.2.4 Post-conditions | - Train 1 establishes a connection with the server at the next station while Train 1 has a connection with the server at the current station.
- When the distance between Trains 1 and 2 becomes longer, Trains 1 and 2 stop sharing the information and disconnect from each other. |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.2.5 Existing features partly or fully covering the use case functionality | TR 22.990[6] covers utilizing off-network and on-network communications at the same time and the traffic characteristic of off-network communications. |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.2.6 Potential New Requirements needed to support the use case | |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.2.6.1 Requirements related to the Service layer | [PR 5.2.6-1] A single mobile FRMCS UE shall be able to connect to multiple edge servers simultaneously which are located along rail tracks.
Note: The above requirement is intended to be included in Section 5.5 of TS22.282[8].
[Editor's note: The potential requirements for FRMCS UEs to identify the edge servers are FFS]
[Editor's note: The potential requirements for edge servers to authorize the FRMCS UEs are FFS] |
5eaf1b94c89939407995fc52470817be | 22.890 | 5.2.6.2 Requirements related to the Transport layer | [PR 5.2.6-2] The FRMCS System shall support the following traffic characteristics of data transfer:
Note: This table is intended to be included in Section 6.2 of TS 22.289[9].
Scenario
(Note 5)
End-to-end latency
Reliability
(Note 1)
UE speed
UE Relative
Speed
User experienced data rate
Payload
size
(Note 2)
Area traffic density
Overall UE density
Service area dimension
(Note 3)
Multiple trains' stops at the same platform (Korea, urban railway)
≤10 ms
99.9999%
≤100 km/h
≤50km/h
≤1Mb/s
Small to large
≤ 1 Mb/s/km
≤ 5 (100m)
≤ 15 km
along rail tracks including bad weather conditions
(Note 4)
NOTE 1: Reliability as defined in TS 22.289 sub-clause 3.1.
NOTE 2: Small: payload ≤ 256 octets, Medium: payload ≤512 octets; Large: payload 513 -1500 octets.
NOTE 3: Estimates of maximum dimensions.
NOTE 4: Non-Line-of-Sight (NLOS) between UEs shall be supported
NOTE 5: Off-network traffic characteristics are not addressed in this table since it can be covered by TR22.990.
Table 5.2.6.2-1: Traffic characteristics for multiple trains' stops at the same platform |
5eaf1b94c89939407995fc52470817be | 22.890 | 6 Business communication applications related use cases | |
5eaf1b94c89939407995fc52470817be | 22.890 | 6.1 Transportation convenience service for the passengers for the reduced mobility | |
5eaf1b94c89939407995fc52470817be | 22.890 | 6.1.1 Description | In the Railway Smart Station, a transportation convenience service for the passengers with the reduced mobility can be feasible, such as a mobility service for the passengers to arrive at the desired destination.
Figure 6.1.1-1. Example of transport convenience service for passenger with reduced mobility |
5eaf1b94c89939407995fc52470817be | 22.890 | 6.1.2 Pre-conditions | 1. There exist feasible Mobile Intelligent Assistants in the Railway Smart Station, where the Mobile Intelligent Assistants support 3GPP system.
2. The Mobile Intelligent Assistants are operated under the central control system via 3GPP access.
3. There is at least one passenger with reduced mobility in the Railway Smart Station, where the weak passenger has difficulty moving toward the desired destination.
4. The passenger has an equipment supporting 3GPP access. |
5eaf1b94c89939407995fc52470817be | 22.890 | 6.1.3 Service Flows | 1. A passenger with reduced mobility is reserved in advance, where a Railway Smart Station already knows that the passenger needs help to get to the desired destination.
2. Once the passenger enters the Railway Smart Station, one Mobile Intelligent Assistant stands by for mobile support to the desired destination.
3. The Mobile Intelligent Assistant takes the passenger to the desired place. |
5eaf1b94c89939407995fc52470817be | 22.890 | 6.1.4 Post-conditions | 1. The Railway Smart Station traces and manages the route of movement of the passenger with reduced mobility. |
5eaf1b94c89939407995fc52470817be | 22.890 | 6.1.5 Existing features partly or fully covering the use case functionality | [R-5.11-001] The MCX Service shall support obtaining and conveying Location information describing the position of the MCX UE.
[R-5.11-002] The MCX Service should support obtaining and conveying high accuracy Location information describing the position of the MCX UE.
[R-5.11-002a] The MCX Service shall be able to provide a mechanism for obtaining high accuracy Location information by integrating position information from multiple external sources (e.g. magnetometers, orientation sensors, GNSS)
[R-5.11-003] The MCX Service shall provide for the flexibility to convey future formats of Location information.
[R-6.12-002] The MCX Service shall support conveyance of Location information provided by 3GPP location services.
Note: Please refer to TS 22.280 V17.6.0 [7]. |
5eaf1b94c89939407995fc52470817be | 22.890 | 6.1.6 Potential New Requirements needed to support the use case | [R-6.1.6-1] The MCX service shall be able to support obtaining and conveying location information as a scalable zone information describing the position of the MCX UE.
Editor's note: This requirement is FFS. |
5eaf1b94c89939407995fc52470817be | 22.890 | 6.2 Smart kiosk of Railway Smart Station | |
5eaf1b94c89939407995fc52470817be | 22.890 | 6.2.1 Description | A smart kiosk in the railway smart station provides various information to passengers, such as location information service with 3D or metaverse enabled station map, simple ticketing service, and other information providing services via interfacing smart station devices and systems, e.g. CCTV, sensors.
The kiosk co-operates with a Mobile Intelligent Assistant such as robot, to support passengers if the kiosk operating system decides that it is necessary. |
5eaf1b94c89939407995fc52470817be | 22.890 | 6.2.2 Pre-conditions | A passenger has ticketed of a train.
A passenger has a UE, which is a Railway Smart Station service enabled.
A kiosk has a UE, which is a Railway Smart Station service enabled.
A Mobile Intelligent Assistant has a UE, which is a Railway Smart Station service enabled.
A passenger has made a permission to handle his/her identification to FRMCS, such as the smart station system. |
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