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e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.4.1 Description | In general, a UE senses using either or combination of the non-3GPP sensors such as camera, Lidar, 3GPP-based sensing. In 3GPP 5G wireless sensing, the Sensing transmitters and Sensing receivers sense for stationary and moving Objects around them – using time-difference-of-arrival (TDoA), angle-of-arrival (AoA), angle-of-departure (AoD) measurements, RSSI etc. as shown in Figure 5.4.1-1 [14]. Transparent sensing is a use case in which 3GPP sensing data is captured by Sensing transmitter and/or Sensing receiver and communicated so that the 5GS is aware of the 3GPP sensing data, while the non-3GPP sensing data is the result of non-3GPP sensors and is transparent to 5GS. From this information, service enablers can be defined. One example of such information is location data, whose corresponding service enabler is Location Based Services.
Figure 5.4.1-1: BS and UE sensing Objects
In this use case, non-3GPP sensing data is made available to the 5GS, and the requirements for this exposure are considered. The data so obtained can be used for diverse purposes. One such purpose is Localization (identifying both a three- dimensional position and orientation.) Transparent Sensing data used for Localization is described in TR 22.856 [11].
Figure 5.4.1-2: Opaque and Transparent Sensing Data
The distinguishing characteristic of this use case is that the non-3GPP sensing data is provided to the 5GS itself.
The application server receiving 'transparent non-3GPP sensing data' as shown in figure 5.4.1-2 can be operated by the MNO. This enables the MNO to provide specific processing to produce 'combined sensing results as a service,' where the sensing data is supplied by non-3GPP sensors owned and operated by third parties, subscribers, etc.
In this use case it is the 5GS that receives 3GPP and non-3GPP sensing data, not a third party. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.4.2 Pre-conditions | A UE has access to one or more sensors. In this use case. the UE has access to four sensors: NR-based sensing, 3D LiDAR, an RGB Camera and a Smart Phone Camera. The sensors' physical configuration is known (e.g. the cameras are 10 cm apart). The NR-based sensing capabilities of the UE and its connected BS are used to capture information about the nearby environment by the UE.
A mobile network MN supports the acquisition of non-3GPP sensing data. We term this support by the network a 'non-3GPP sensing data consuming service'. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.4.3 Service Flows | The user U activates a mechanism to enable Non-3GPP sensing data acquisition that can be collected at U's UE.
The user U provides this non-3GPP sensing data via the 5GS. This process is analogous to activating or enabling a location tracking service.
MN acquires sensing data provided by U's UE, for a period of time.
MN can also acquire 3GPP sensing data. 3GPP-RF sensing data can be processed only in 5GS to derive sensing results. The sensing results and the Non-3GPP sensing data can be combined to produce a combined sensing result.
The user U deactivates the mechanism to provide non-3GPP sensing data to the 5GS. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.4.4 Post-conditions | The non-3GPP sensing data acquired by the 5GS is processed in order to enable other services. The processed information can for example provide 'Spatial Localization' information that can be exposed to authorized third parties, as discussed in 22.856 [11]. "Spatial Localization Use Case". |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.4.5 Existing feature partly or fully covering use case functionality | Positioning in 5G Networks been proposed in 3GPP release-16, it specifies positioning signals and measurements for the 5G NR. In release-16, 5G Positioning architecture extends 4G positioning architecture by adding Location Management Function (LMF) and Transmission reception points (TRP). 5GS provides new positioning methods based on multi-cell round-trip time measurements, multiple antenna beam measurements, to enable downlink angle of departure (DL-AoD) and uplink angle of arrival (UL-AoA) [15][16]. The Rel-17 5G system supports positioning of the device-based but not device-free – objects that do not radiate EM signals [14][15][16].
The 5GS already supports transport of non-3GPP sensor data. The table below provides indicative performance requirements for media used for sensor information communication.
Sensor Type
Uplink KPI
Remarks
3D Lidar
30 Mbps
An example 3D LiDAR: 16 channel, 0.3M data points, dual return mode
2 bytes distance, 1byte [13]
Industrial RGB Camera
16 ~ 800 Mbps
2,592 x 2,048 x 10bits x 2.5 Hz x 6 EA, compression ratio 2%
Smart Phone Camera
4 ~ 200 Mbps
2,160 x 2,880 x 8bits x 1 Hz x 4 EA, compression ratio 2%
Table 5.4.5-1: Performance Requirements (already possible to fulfill with the 5GS) |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.4.6 Potential New Requirements needed to support the use case | [PR 5.4.6-1] Subject to user consent and national or regional regulatory requirements, based on operator policy, the 5GS shall support a mechanism to receive uplink non-3GPP sensing data from authorized non-3GPP sensors.
NOTE 1: This requirement assumes there is some functionality in the 5GS to discern and interpret the acquired 3GPP and non-3GPP sensing data.
[PR 5.4.6-2] Subject to user consent and national or regional regulatory requirements, based on operator policy, the 5GS shall support a mechanism to expose sensing results to trusted third parties.
[PR 5.4.6-3] Subject to user consent and national or regional regulatory requirements, based on operator policy, the 5GS shall support a mechanism to expose combined results to trusted third-parties.
[PR 5.4.6-4] Subject to user consent, network operator policy and national or regional regulatory requirements, the 5GS shall support a mechanism to enable Sensing transmitters and Sensing receivers to acquire 3GPP sensing data to capture information about the nearby environment and for this to be combined with Non-3GPP sensing data to produce a combined sensing result.
NOTE 2: This requirement does not imply or allow 3GPP sensing data to be exposed to third parites. This data is considered confidential. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.5 Use case on sensing for flooding in smart cities | |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.5.1 Description | Due to the climate change in recent years, a larger amount of rain sometimes falls within a short duration of time inside a small area. This result, in particular in urban areas, in inundation and flooding even in areas where these did not happen in the past. When flooding is about to happen on roads, people might enter areas getting in danger without knowing it. Once flooding really happens there, this might result in loss of human life. At places where flooding is expected to occur, monitoring of flooding is performed using cameras and other sensors. However, due to the recent climate change, it can be difficult to recognize places where flooding is expected to occur. Using radio waves, it is possible to recognize places where flooding occurs in an efficient way.
NOTE: There has been a related trend, although a mobile communication is not directly involved so far and it's monitoring of the river, not of the road as this use case deals with. In Japan, MLIT (Ministry of Land, Infrastructure, Transport and Tourism) takes care of the river administration and supervises water level observation of rivers to prevent and predict flooding. In the past, water-level gauges were only sparsely deployed along the river. Water levels at places where those gauges were not placed were estimated based on water levels observed some distance away where such gauges were placed. Detailed degree of possibility of flooding at each place was not directly understood. To improve this situation, MLIT has encouraged to develop a low-cost water-level gauge and has started placing such gauges e.g., at places that are relatively prone to flooding or show a specific water behavior due to the form of the river, or that are close to hospitals or important facilities. Disaster Information for River is now available at https://www.river.go.jp/e/ for public. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.5.2 Pre-conditions | Good partnership and cooperation are established between Mobile Operator #A and administrators of roads such as a local government in City #B. Mobile Operator #A constantly senses the surface of the road and informs results of sensing to the administrator of the road. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.5.3 Service Flows | Figure 5.5.3-1: Sensing for flooding in smart cities
1. Base stations owned by Mobile Operator #A are deployed around the road. Mobile Operator #A carries out sensing of the surface of the road in City #B. This sensing is performed using radio wave. Results of sensing information, incl. whether flooding occurs on the road, are informed to the administrator of the road in City #B.
2. The administrator of the road usually monitors the state of flooding on the road using information from sensors including information from Mobile Operator #A. In addition, in the case of heavy rain, the administrator can request Mobile Operator #A to increase frequency of monitoring of situation of roads and Mobile Operator #A monitors the situation more frequently responding to this request.
3. If there is information received that flooding occurs, the administrator advises people in the areas concerned to evacuate the areas. The administrator advises via mobile networks.
4. People who received the advice evacuate the areas or do not enter such areas.
5. Now City #B trusts Mobile Operator #A and allows it to advise people about evacuation without City #B's intervention in case of flooding. Next time a similar flooding occurs, Mobile Operator #A sends advice for evacuation directly to people. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.5.4 Post-conditions | Damage of the flooding has been kept at minimum. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.5.5 Existing features partly or fully covering the use case functionality | None. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.5.6 Potential New Requirements needed to support the use case | [PR 5.5.6-1] Subject to operator policy, the 5G system shall be able to provide sensing result indicating disasters or other emergencies (e.g., flooding) in a given geographic area to authorized third parties in a timely manner.
[PR 5.5.6-2] Subject to regional or national regulatory requirements and operator policy, the 5G system shall be able to provide its public warning system with a warning notification based on sensing result indicating disasters or other emergencies (e.g., flooding) in a given geographic area in a timely manner.
[PR 5.5.6-3] Subject to operator policy, it shall be possible for an authorized third party to configure the 5G system to initiate sensing for disasters or other emergencies (e.g., flooding) in a given geographic area.
[PR 5.5.6-4] The 5G system shall be able to support the following KPIs:
Table 5.5.6-1 Performance requirements of sensing for flooding in smart cities
Scenario
Sensing service area
Confidence level [%]
Accuracy of positioning estimate by sensing (for a target confidence level)
Accuracy of velocity estimate by sensing (for a target confidence level)
Sensing resolution
Max sensing service latency[ms]
Refreshing rate [s]
Missed detection [%]
False alarm [%]
Horizontal
[m]
Vertical
[m]
Horizontal
[m/s]
Vertical
[m/s]
Range resolution
[m]
Velocity resolution (horizontal/ vertical)
[m/s x m/s]
sensing for flooding in smart cities
Outdoor
95
≤10
[≤0.2]
NOTE 2
N/A
N/A
N/A
N/A
≤ 1min
NOTE 3
< 1min
NOTE 3
< 0.1
< 3
NOTE 1: The terms in Table 5.5.6-1 are found in Section 3.1.
NOTE 2: This value is for the water level. Description related to NOTE in clause 5.5.1 suggests 0.01 m. [≤0.2] is derived from the water level where people feel difficulty in walking.
NOTE 3: Description related to NOTE in clause 5.5.1 suggests 2 minute-interval monitoring when the water level of the river rises quickly. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.6 Use case on intruder detection in surroundings of smart home | |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.6.1 Description | Detection of an intruder including a person or a harmful animal into a private property is an important piece to ensure residents at home in the private property feel comfortable and secure. For the surroundings monitoring, various technologies, such as cameras, infrared cameras, and microwave radars are being used. However, these technologies require line-of-sight, and therefore locations which can be monitored may be limited.
Wireless signals make it possible to monitor locations without line-of-sight and to monitor wider areas [17]. Sensing by wireless signals can complement the afore-mentioned technologies and can improve accuracy of the detection. Sensing by wireless signals gives residents time to prepare against intruders or to drive them away. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.6.2 Pre-conditions | UEs such as smart phones and consumer premise equipment are installed inside a house, in particular, near a wall or a window. Residents have a contract with a mobile operator for the UEs. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.6.3 Service Flows | Figure 5.6.3-1: Intruder detection in surroundings of smart home
1. The UEs such as smart phones and CPE communicate with base stations in the outdoor or in the indoor and monitor 3GPP signals which are influenced by outdoor objects such as humans and animals. In addition, the UEs communicate with base stations of the mobile operator and monitor the radio wave state between the UEs and the base stations.
2. When an intruder enters the site, the radio signals are changed. The core network processes the data and yields sensing result indicating detection of the intruder.
NOTE: Cases that such an intruder or an animal is already indoor are addressed in the use case in clause 5.1.
3. The residents are informed of detection of the intruder. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.6.4 Post-conditions | The residents report to the police or the security service and request them to take an appropriate action. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.6.5 Existing features partly or fully covering the use case functionality | None. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.6.6 Potential New Requirements needed to support the use case | [PR 5.6.6-1] Subject to operator policy, the 5G system shall be able to collect 3GPP sensing data and yield sensing result from the data for detection of outdoor objects.
[PR 5.6.6-2] The 5G system shall be able to support the following KPIs:
Table 5.6.6-1 Performance requirements of intruder detection in surroundings of smart home
Scenario
Sensing service area
Confidence level [%]
Accuracy of positioning estimate by sensing (for a target confidence level)
Accuracy of velocity estimate by sensing (for a target confidence level)
Sensing resolution
Max sensing service latency[ms]
Refreshing rate [s]
Missed detection [%]
False alarm [%]
Horizontal
[m]
Vertical
[m]
Horizontal
[m/s]
Vertical
[m/s]
Range resolution
[m]
Velocity resolution (horizontal/ vertical)
[m/s x m/s]
intruder detection in surroundings of smart home
Outdoor
95
≤2
N/A
N/A
N/A
N/A
N/A
≤1000
< 1
< 0.1
< 5
NOTE: The terms in Table 5.6.6-1 are found in Section 3.1. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.7 Use case on sensing for railway intrusion detection | |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.7.1 Description | Extensive railway deployment and the changing wildlife habitat area due to the changing global environment has led to increase of crash of wildlife to trains. Once a crash happens, its recovery costs, takes time, and impairs convenience [18], [19]. Such a crash should be avoided, but it appears difficult to proactively predict wildlife's intrusion onto railway track. It's different from e.g., weather forecast. Passively detecting wildlife's intrusion onto railway track appears an option to take. Monitoring with cameras serves the same purpose. However, this requires LOS (i.e., line of sight) and a dense deployment of cameras, which is not necessarily efficient. Another traditional mechanism using fibre optic sensing techniques is costly and requires manual intervention, making it very difficult to meet the increasing demand for railway monitoring. Thanks to the 5G NR based sensing, the base station as transmitter and receiver along the railway can constantly sense the railway situation such as railway intrusion.
The assumption of this use case is the following:
- There is at least 300km train line as depicted in the figure 5.7.1-1[19] owned by railway operator. The safe place is a place where a person and their equipment cannot be struck by rail traffic, which is used for minimizing damage caused by possible railway accident or crash and for ensuring safe operation of railway. The danger zone is anywhere within 3m horizontally from the nearest track.
- The typical size and velocity of intruder and train in this use case are described in the Table 5.7.1-1.
Table 5.7.1-1
Size
(Length x Width x Height)
Velocity
Intruder
Pedestrian(Adult):
0.5m x 0.5m x 1.75m
5km/h
Animal(Sheep/deer):
1.5m x 0.5m x 1 m
5km/h
Trains
24m x 3.5m x 3 m
100km/h - 350km/h
When the intruder standing at the outermost side of safe place starts walking on the danger zone, it means the intrusion happens. The distance that intruder move perpendicular to the railway track is more sensitive for road safety, compared to the distance parallel to the railway track.
Figure 5.7.1-1 |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.7.2 Pre-conditions | Base stations are deployed near and along a railway track which enable the mobile operator to constantly sense the railway including intruder (e.g., pedestrians and animal). For sensing, signaling transmitted by a base station is influenced or bounced by objects around the railway and then monitored by the base station and other base stations. Sensing result is being notified to a railway operator by the mobile operator. The railway operator knows locations of trains. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.7.3 Service Flows | Figure 5.7.3-1 Railway intrusion detection
1. Base stations are deployed near and along a railway track. In order to acquire the sensing information of railway, railway operator requests sensing service from mobile operator. The mobile operator configures the base stations along the train line to perform sensing. Suddenly, an intruder (e.g. pedestrian or animal) is walking on the danger zone.
2. The 3GPP sensing data is reported from base stations and further processed into the sensing results by the core network. The mobile operator exposes the sensing results to the railway operator. Based on the sensing results, the location of the intruder can be estimated.
3. Trains running on the railway track measure their own location and velocity. These trains inform that information to a controller of the railway operator.
4. The controller identifies a train that is affected by an intruder based on the sensing results from mobile operator and train's location and velocity.
5. The controller orders the train to slow down or stop. In addition, the staff working for railway operator immediately responds to the emergency. The intruder leaves the danger zone safely. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.7.4 Post-conditions | The controller judges the intruder is gone and safety can be ensured. The controller permits the train to start again or speed up. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.7.5 Existing feature partly or fully covering use case functionality | TBD. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.7.6 Potential New Requirements needed to support the use case | [PR 5.7.6-1] Subject to operator policy, the 5G system shall enable the core network to collect and aggregate 3GPP sensing data data from RAN.
[PR 5.7.6-2] Subject to operator policy, the 5G system shall enable the core network to expose a suitable API to provide the information regarding sensing results to authorized third parties.
[PR 5.7.6-3] The 5G system shall be able to support the following KPIs:
Table 5.7.6-1 Performance requirements of sensing results for railway intrusion detection
Scenario
Sensing service area
Confidence level [%]
Accuracy of positioning estimate by sensing (for a target confidence level)
Accuracy of velocity estimate by sensing (for a target confidence level)
Sensing resolution
Max sensing service latency[ms]
Refreshing rate [s]
Missed detection [%]
False alarm [%]
Horizontal
[m]
Vertical
[m]
Horizontal
[m/s]
Vertical
[m/s]
Range resolution
[m]
Velocity resolution (horizontal/ vertical)
[m/s x m/s]
Intrusion detection on a railway
Outdoor (Along railway)
95
≤1.5
N/A
N/A
N/A
N/A
N/A
˂1500
≤ 0.1
2
2
NOTE: The terms in Table 5.7.6-1 are found in Section 3.1.
NOTE: In this use case base station and UE is acting as sensing transmitter and/or sensing receiver. This is an example and other options can also be valid. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.8 Use Case on Sensing Assisted Automotive Maneuvering and Navigation | |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.8.1 Description | To support smart transportation and autonomous driving, more vehicle and devices are equipped with sensing technologies. For example, cameras, Radar, and Lidar systems are the most used sensors by the automotive industry to maintain the perception for autonomous vehicles at various levels of autonomy. Accurate sensing results are crucial to enable the safe and reliable control of the vehicles.
Due to the mounting position of the sensors (e.g., 3GPP based sensors) information collected from a single vehicle's sensors can not be sufficient or accurate enough to satisfy the advanced automotive use cases, e.g., autonomous driving, coordinated maneuver, etc. Therefore, the 5G system could coordinate sensing to get sensing data from various sources and generate sensing results which could be consumed at the vehicle and used for the vehicular control and driver assistance, e.g., feed into the Automated Driving System (ADS) in the car [21]. The 3GPP sensing data collected by the UE can be sent alongside relevant sensing information to other sensing entities (including other vehicles, roadside units, and network) for further processing (if required) before sharing with a third-party application as shown in Figure 5.8.1-1.
The network facilitated NR based sensing described above could significantly improve the sensing reliability and quality, enabling new and advanced automotive use cases.
Figure 5.8.1-1: 5G System Assisted Automotive maneuvering and navigation |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.8.2 Pre-conditions | In this use case, Joe and Bob’s vehicles are equipped with 3GPP-based sensing technology. Non-3GPP sensors like radar, camera and Lidar sensors could also be available in the vehicles. Additionally, the vehicles are capable of 5G communications, including direct communication with other vehicles, communication with 5G system via RAN entities. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.8.3 Service Flows | 5G system assisted coordination of sensing service
Step 1 (Network provides configurations and policies): When Bob’s car registers for 3GPP sensing service, the network provides policies and configurations to enable UEs take appropriate actions during sensing e.g., obtaining 3GPP sensing data from another UEs/RAN entities. For example, the policies provided by network could provide guidance for the discovery UEs/RAN entities with appropriate NR RF sensing capabilities, when to trigger requests, when to stop sending requests, messaging formats, the communication configurations (such as which 5G communication mode to use and under which conditions), the sensing configurations (such as which role i.e. transmitter/receiver, to use by a particular node for a particular sensing task, etc.. These polices and configurations could be updated frequently by the network based on e.g., network conditions, mobility pattern, etc.
Step 2 (Bob determines his sensors are blocked): Bob's sensor(s) is(are) blocked by Joe's vehicle, and cannot adequately detect its surroundings (e.g., detect if there is another vehicle in front). This could result in the vehicle miscalculating the needed distance to stop before a traffic light. In other cases, Joe's vehicle could also reduce the valid sensing region and result in misdetection of incoming vehicles size or shape, especially near intersections. The sensing results cannot fully satisfy the autonomous driving needs and requirement.
Step 3 (Bob recognizes need for sensing inputs): Due to unsatisfactory autonomous driving needs and requirements, the UE in Bob's vehicle is notified that its sensors are blocked and needs 5G System assistance for coordination of the sensing service.
Step 4 (Bob’s vehicle discovers Joe’s vehicle): With the policies and configurations provided by the 5G system, Bob’s vehicle can search for neighbouring UEs/RAN entities or ask the network to provide recommendations for UEs/RAN entities (e.g. considering the current network conditions in the target sensing area) and their 3GPP NR RF sensing capabilities (e.g., if UE/RAN entity supports sensing service). This information would be used to discover other vehicles and RAN entities with 3GPP NR RF sensors that can support sensing in the area. In this example, Bob's vehicle discovered Joe's vehicle could be useful in providing sensing inputs.
Step 5 (Bob’s vehicle connects to Joe’s vehicle): Bob's vehicle then establishes 5G communication connection with Joe's vehicle and/or RAN entities as shown in Figure 5.8.3-1. The most suitable 5G communication mode (e.g., broadcast, unicast, etc) is determined by the Bob’s vehicle based on 5G system configuration and policies.
Step 6 (Bob's vehicle requests sensing info from Joe’s vehicle). The request could indicate the information needed to perform sensing, e.g., the additional region to be covered, additional sensing target, synchronization info, etc.
Step 7 (Joe sends sensing results/3GPP sensing data to Bob’s vehicle) Based on the information provided by Bob’s vehicle; Joe sends Bob 3GPP sensing data identifying objects in its surroundings. It is important to note that when 3GPP sensing data is shared between Joe and Bob, it is expected to be performed in compliance with operator policy on the use of the operator resources (e.g., licensed/unlicensed spectrum).
Step 8a (Bob processes 3GPP sensing data locally) Based on the fact that Bob’s has non-3GPP sensors (e.g., camera, Lidar), Bob’s car can combine the 3GPP sensing data from Joe’s vehicle with other sensors.
Step 8b (The 5G System expose sensing results to third-party application) Additionally or alternatively Bob can share sensing results and non-3GPP sensing data from the camera and Lidar within the 5G System and then it is exposed by the 5G System to a third-party application server for combination by the third-party. It is important to note that contextual information is information forwarded alongside the sensing results which provide context to the conditions under which the sensing results were derived. This contextual information can be used in scenarios where the sensing result is to be combined with data from other sources. It should also be noted that in case contextual information is required, this information should be shared with the appropriate consent, permissions and subject to operator policy.
Figure 5.8.3-1: 5G system assisted automotive maneuvering and navigation
With the sensing information provided by Joe’s vehicle and the network, Bob’s vehicle obtains a full map of the region. The autonomous driving algorithm can make corresponding decisions reliably. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.8.4 Post-conditions | Using 5G system assistance, Bob’s vehicle would be able to achieve highly reliable navigation capacity, by coordinating the operation with other vehicles to collaborate with other sensing devices to improve quality. With high-quality sensing results, advanced smart transportation use cases and autonomous driving could be achieved. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.8.5 Existing features partly or fully covering the use case functionality | V2X communication supports the information exchange among the vehicles, between vehicle and infrastructure or network. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.8.6 Potential New Requirements needed to support the use case | [PR 5.8.6-1] The 5G system shall be able to support mechanisms to control UEs and RAN entities for a sensing service.
NOTE 1: In the requirement above, control can include configuration such as sensing specific policies and settings (e.g., conditions for triggering sensing requests, location, etc.) coordinated amongst UE and RAN entities.
[PR 5.8.6-2] For a sensing service, the 5G system shall be able to support mechanisms for the UEs and RAN entities to provide 3GPP sensing data.
NOTE 2: This requirement can cover scenarios making use of information already available in the EPC and E-UTRA (assuming no new functionalities are required in the EPC and E-UTRA).
[PR 5.8.6-3] The 5G system shall be able to support an authorized UE in the discovery of UEs and selection of RAN entities with the required 3GPP NR RF sensing capabilities for the sensing service.
[PR 5.8.6-4] Subject to user consent and regulations, based on operator policy, the 5G system shall be able to provide means to authorize and configure a UE for sensing operation (e.g., based on location, time, etc) and for establishing the communication connection needed to assist the sensing service.
NOTE 3: The above requirement assumes that the communication connection used for assisting sensing service (e.g. for transferring 3GPP sensing data or sensing results) can include existing communication connection modes such as direct network communication, direct device connection under network coverage and indirect network connection [33].
[PR 5.8.6-5] Subject to user consent and regulations, based on operator policy, the 5G system shall be able to support exposure of sensing results and sensing contextual information (e.g. UE location), to a trusted third-party application.
[PR 5.8.6-6] The 5G system shall be able to provide means for the 5G network to activate and/or deactivate sensing service in the target sensing area based on network conditions (e.g., network-load). |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.9 Use case on AGV detection and tracking in factories | |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.9.1 Description | Improving safety and work conditions in factories and industrial environments is a critical component for industry 4.0. Replacing communication cables with wireless connections has already positively changed the factory environment, by providing reliable ethernet-like communications, and enabling time-sensitive networking over the air. Nevertheless, despite automation and improvement, accidents in factories still occur, leaving room for improvement. Indeed, 5250 fatal work injuries were recorded in the US only in 2018, according to the Bureau of Labour Statistics [22], a 2% increase from 2017.
Automated Guided Vehicles (AGVs) are key components of the new smart factories, used for a variety of tasks such as heavy or hazardous materials transportation and distribution. Simultaneous presence of AGVs and human workers at the industrial side creates safety challenges and calls for stringent safety requirements [23]. For example, the driverless, automated guided industrial vehicles ANSI/ITSDF B56.5 [24] safety standard requires that “the AGV shall detect and avoid both static and dynamic obstacles appearing in the path of travel direction”. Reliable detection of AGV/human presence or proximity is therefore an important safety criterion.
5G system can be deployed in a factory which uses RAN entities and/or UEs to measure 3GPP sensing data, that are made available to sensing management entities in order to derive sensing results such as the detection of the presence or proximity of AGVs and humans. This use case assumes support of NR-based RF sensing. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.9.2 Pre-conditions | Company #A operates multiple AGV in its factory. Each AGV is programmed to perform certain tasks, such as transporting large containers from point #B to point #C following a programmed route. AGVs can be of various sizes and operate at different speeds and locations. In a factory, workers are dispersed throughout the area, performing different tasks. Workers-AGVs interactions are a source of potential injuries, and extra care needs to be taken to avoid any harm.
The factory deploys 5G based integrated communication and sensing system with RAN entities and UEs throughout the factory floor. The RAN entities deployment is done to optimize communication, positioning, and sensing.
The RAN entities and/or UEs perform sensing operations over certain target areas throughout the factory. The deployed RAN entities (or a subset of the RAN entities) transmit sensing reference signals, which are received by a subset of RAN entities and/or selected UEs. Some UEs are authorized and configured to monitor the sensing reference signals and report 3GPP sensing data to a sensing entity in the 5G system. The sensing entity can be deployed either locally in the factory or in the cloud/edge.
In this use case it is important to note that AGVs do not actively participate in the sensing signals transmission or reception, and hence it is more applicable to AGVs which are not equipped with UEs, e.g., legacy AGVs. For those AGVs with UEs, the UEs can be helpful in sensing and tracking humans on the factory floor.
5.9.3 Service Flows
Figure 5.9.3-1: AGV presence and proximity detection
1. Alex is working in his section of the factory (shown in the lower left area in Figure 5.9.3-1), performing regular maintenance work around a conveyor belt.
2. An AGV, AGV#1, is approaching the area where Alex is working, carrying a heavy load to be placed at a designated location next to the conveyor belt.
3. Using the 3GPP sensing data from the RAN entities and the UE carried by Alex, the sensing entity processes the data to obtain sensing results and detects the proximity of the AGV1 to Alex. The sensing results are shared with a safety monitoring application of the factory, and a notification is sent to Alex to warn him of the approaching AGV.
4. Another AGV, AGV#2, enters an area (lower right area in Figure 5.9.3-1) with increased risk for workers due to higher workers presence and higher equipment and machines density. Based on the 3GPP sensing data from RAN entities, the sensing entity processes the data to obtain sensing results and detects the presence of AGV#2 and exposes the detection event to the factory safety monitoring application. The safety monitoring application triggers a warning sound to warn the workers (e.g., John and Emma) in that area of the approaching AGV.
Note that, in this scenario, none of the UEs was involved in the sensing session. However, the sensing entity can use 3GPP sensing data from UEs in the area (e.g., UE carried by Emma) in its sensing processing if available.
5. In another scenario, John (lower right area in Figure 5.9.3-1), working on his section, not having a UE, is being tracked using 3GPP sensing data from RAN entities and/or UEs. When John comes in proximity with an AGV, which has or does not have a UE, a warning message is sounded to alert John. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.9.4 Post-conditions | Thanks to the warning messages, workers are safe and potential accidents caused by workers-AGVs interactions are avoided. By leveraging the sensing capability of the 5G based integrated communication and sensing system, the factory safety supervision is upgraded, and workers safety is enhanced. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.9.5 Existing features partly or fully covering the use case functionality | None. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.9.6 Potential New Requirements needed to support the use case | NOTE 1: The following requirements apply to networks managed by PLMN or NPN.
[PR 5.9.6-1] The 5G system shall be able to provide means to support NR-based sensing in a certain area or location.
[PR 5.9.6-2] Based on operator policy and location area, the 5G system shall be able to provide means to support per-UE authorization for NR-based sensing.
[PR 5.9.6-3] The 5G system shall be able to support means to enable RAN entities and UEs to transfer 3GPP sensing data to sensing processing entities in the 5G system responsible for processing and aggregation of the 3GPP sensing data.
NOTE 2: The “Sensing processing entities” in the above requirement refer to one or more entities in the 5G system responsible for aggregating and processing of 3GPP sensing data (e.g., core network).
[PR 5.9.6-4] Based on operator’s policy, the 5G system shall be able to support means to expose sensing results to a trusted third-party application. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.10 Use case on UAV flight trajectory tracing | |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.10.1 Description | With the development of UAV technologies and the increase of demands on rapid logistics, aerial photographing, environmental monitoring and public security, a variety of commercial UAV services gradually become reality.
Normally the commercial UAVs fly based on predetermined flight routes, following regulated positions, heights, speeds, and directions. E.g., a package-delivery UAV flies from the package sender to the package recipient; a task-execution (such as environmental monitoring) UAV flies from the UAV airport to the target area.
On-route flying is important for these commercial UAVs. Their flight routes are optimized and permitted by UAV service operators, UAV management department, or USS (Uncrewed Aerial System Service Supplier)/UTM (Uncrewed Aerial System Traffic Management). Usually, they have the shortest flight distance, avoid no-fly zone, and keep safe distance from obstacles (e.g., building, trees, hills) and other commercial UAVs.
Although a UAV is equipped with sensors to keep itself along the flight route, the external UAV flight trajectory tracing function is still necessary because these sensors sometimes are restricted. E.g., the camera is impacted by light situation; the UAV-borne radar is impacted by rainfall or snowfall, etc. If these events occur, UAV cannot correctly decide its own position, height or speed, and thus cannot follow the traced route.
Although there exist dedicated UAV surveillance equipment and radar, their large-scale deployment has great challenges due to lack of available sites and high installation and maintenance cost.
In comparison, using the 5G system can provide a cost-effective way to trace these UAVs, e.g., 5G network infrastructures with ubiquitous coverage can better trace the flight trajectory of each UAV.
Specifically, 5G RAN entities can rely on radio sensing to obtain the information on UAV position and motion (e.g., distance, angle) and send 3GPP sensing data to a sensing processing entity located in the 5G system.
As shown in Figure 5.10.1-1, the UEs that are connected to the 5G RAN entities can be configured to assist in the sensing operations, which can increase the sensing coverage, provide more positioning reference points, and improve sensing result accuracy and robustness. This improvement is a result of higher density of UEs compared to the base stations, which increases the probability that some UEs are located in positions that have shorter distance away from UAV than 5G RAN entities (e.g., UAV located in the middle of two 5G RAN entities while UE locates under UAV), or some UEs are located in the reflection directions that have larger radar cross section (RCS) than 5G RAN entities considering the UAV RCS variation in different reflection directions.
The 5G sensing processing entity can collect the sensing data from one or multiple network infrastructures.
The 5G network operator can provide the UAV flight trajectory tracing service to a trusted third-party application (e.g., UAV service operator, UAV management department, USS/UTM) as requested.
Figure 5.10.1-1: UAV flight trajectory tracing by 5G system |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.10.2 Pre-conditions | A UAV operator/UTM provides package delivery service in an area which is covered by 5G network. The UAV operator/UTM subscribes to the UAV flight trajectory tracing service from the 5G network operator.
The UAV operator/UTM provides the 5G network operator the characteristics of the UAV to be sensed, time and space (covering the regulated UAV flight routes and possible off-route locations) of the UAV flight trajectory tracing service. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.10.3 Service Flows | When the appointed time starts, 5G network operator activates the UAV flight trajectory tracing function at the appointed space until the appointed time ends.
The UAV operator controls UAV#1 to take off from package delivery source and fly toward package delivery destination along a regulated flight route.
By radio sensing, a set of 5G base stations and UEs detect UAV#1, and then estimate the position and motion related metrics (e.g., distance, angle) as well as the target object is in coverage, resulting in 3GPP sensing data. The 5G RAN and UEs then send the 3GPP sensing data to the 5G sensing processing entity.
In certain cases, during the flying course, based on sensing and location information, if it is detected that UAV#1 has left the coverage of an old base station and entered the coverage of a new base station, the old base station could stop radio sensing and operate in a power saving mode. The new base station starts and keeps on sensing UAV#1 until it is out of coverage. Note that the determination that the UAV#1 has left the coverage of a base station or not could be determined based on the UAV positions and velocities estimated at the 5G sensing processing entity. Therefore, the network could then decide to activate and deactivate sensing in certain base stations based on this information. In other cases, the network could configure a start and stop of sensing operations for a base station based on a specified time period. In some other cases, during the flying course of the UAVs, based on location information, flying trajectory, sensing requirements, network conditions (e.g. network load) etc., if it is detected that the sensing coverage of the current base station monitoring UAV#1 has weakened and/or a new base station is available that can provide better sensing coverage to monitor UAV#1, a proactive sensing handover can be triggered. This would be useful for the sensing service continuity.
The 5G sensing processing entity collects the UAV 3GPP sensing data from one or multiple RANs and UEs, and estimates the positions and velocities, and sends in real time the sensing results (e.g., UAV positions, velocities) to the UAV operator and/or UTM.
Based on the received sensing results, the UAV operator and/or UTM traces the flight trajectory of UAV#1. Once the UAV operator and/or UTM detects an off-route event, it further steers UAV#1. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.10.4 Post-conditions | UAV#1 delivers package to the destination along the traced flight route or its off-route behavior is sensed. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.10.5 Existing features partly or fully covering the use case functionality | None. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.10.6 Potential New Requirements needed to support the use case | [PR 5.10.6-1] Based on operator policy, request from UTM and sensing configuration (e.g. sensing area), the 5G system shall be able to support RAN entities and UEs in sensing the characteristics of an airborne object of interest (e.g., UAV), including generating 3GPP sensing data related to the object’s location and motion metrics (see examples in Table 5.10.6-1).
[PR 5.10.6-2] The 5G system shall be able to support means to authorize RAN entities and UEs in certain location area generating and reporting 3GPP sensing data (e.g., related to a UAV position, velocity) to a 5G sensing processing entity.
NOTE 1: The requirement above assumes that the 3GPP sensing data is post-processed in 5G sensing processing entity which is located within the 5G system.
[PR 5.10.6-3] The 5G system shall be able to support means to process the 3GPP sensing data and expose in real time the sensing results (e.g., related to a UAV position, velocity) from a 5G sensing processing entity to a trusted third-party application.
[PR 5.10.6-4] The 5G system shall support energy efficient sensing operations.
NOTE 2: Examples of energy efficient sensing operations can include temporarily disabling sensing transmitters and receivers that are not involved in sensing and communication operations or adjusting the sensing operation parameters (e.g. sensing frequency).
[PR 5.10.6-5] Subject to operator’s policy, the 5G network may provide secure means for the operator to expose information on sensing service availability (e.g., if sensing service is available and the supported KPIs) in a desired sensing service area location to a trusted third-party.
[PR 5.10.6-6] The 5G system shall be able to provide the means for supporting sensing service continuity.
[PR 5.10.6-7] The 5G system shall support sensing services with KPIs as given in Table 5.10.6-1.
Table 5.10.6-1 Performance requirements of sensing results for UAV flight trajectory tracing
Scenario
Sensing service area
Confidence level [%]
Accuracy of positioning estimate by sensing (for a target confidence level)
Accuracy of velocity estimate by sensing (for a target confidence level)
Sensing resolution
Max sensing service latency[ms]
Refreshing rate [s]
Missed detection [%]
False alarm [%]
Horizontal
[m]
Vertical
[m]
Horizontal
[m/s]
Vertical
[m/s]
Range resolution (horizontal/vertical)
[mxm]
Velocity resolution (horizontal/ vertical)
[m/s x m/s]
UAV flight trajectory tracing
Outdoor
N/A
1-2
1-2
1-2
1-2
1m x 1m ~10m x 10m NOTE 2
1m/s x 1m/s ~ 10m/s x 10m/s NOTE 3
100~1000 NOTE 4
1Hz
NOTE 5
5
5
NOTE 1: The terms in Table 5.10.6-1 are found in Section 3.1.
NOTE 2: To detect the UAV existence (e.g., for intrusion detection), the sensing resolution of distance is 10m [25]. To track the UAV flying (e.g., for collision detection and warning), the sensing resolution of distance is 1m [25].
NOTE 3: To detect the UAV existence, the sensing resolution of velocity is 10m/s [25]. To track the UAV flying, the sensing resolution of velocity is 1m/s [25].
NOTE 4: To realize 1m granularity tracking, when the velocity resolution is 1~10m/s, the maximum corresponding sensing service latency is 0.1~1s.
NOTE 5: Echodyne MESA-DAATM has approximate 1Hz scan rate [40]. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.11 Use case on sensing at crossroads with/without obstacle | |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.11.1 Description | The various ways of transportation (e.g. vehicles, walking people, motor vehicle, non-motor vehicle) and the dense buildings make the traffic condition complicated. Typically, traffic accidents often happen at the crossroads for example the pedestrians suddenly rush to the road from the invisible place (e.g., behind the high buildings, behind the tall trees), which cause an urgent need to monitor the real-time road status for all days, thus with the collaboration of trusted third-party e.g. map service provider or ITS management platform, driving warning or assistant driving information can be provide timely to vehicles.
The road status includes vehicle moving information, VRU (Vulnerable Road User) information (e.g. VRU location, VRU moving direction, VRU moving speed, etc.), abnormal vehicle behaviour, road obstacles and road condition.
The road status information can be sensed by the cameras and radars on RSU (Road Side Unit). But considering the crossroad condition is very complicated, there are always some blind points. 5G based sensing can provide sensing information to fill these gaps.
For example, it is expected that the base station can sense the surrounding environment e.g. the road, and send the 3GPP sensing data to the core network. The core network can carry out systematic calculation and analysis of the 3GPP sensing data for outputting the sensing result. Such sensing result can be sent to a trusted third-party e.g. map service provider for combination with navigation map data, so as to make the driver aware of the congestion and traffic accidents in advance, and effectively increase the comfort and safety of driving. The base station sensing operations could improve the real-time map service with high reliability and quality.
But in some cases of above, the obstacles (e.g., high buildings or trees) block the transmission of radio signals. The availability and accuracy of the sensing service for the target objects which are located in the area will be greatly impacted.
To guarantee sensing service in this area, multiple 5G system sensing entities can work together. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.11.2 Pre-conditions | Network operator “VV” has released a sensing service for road status sensing and has deployed base stations especially at multiple crossroads to continuously sense the road status.
Due to the high buildings (e.g. Building A) near the crossroads, there are some areas with obstacles for 5G base stations. Some 5G system sensing entities are further deployed by the network operator ‘VV’ to help radio signal transmission and collect 3GPP sensing data.
Network operator “VV” has a collaboration with the ITS management department that the user who has registered the Network operator “VV”’s “road status sensing service” can receive real-time road status information, driving warning or assistant driving information from ITS management platform.
Bob has registered the road status sensing service from Network operator “VV”.
Network operator “VV” can also deliver the real-time road information and the real time location/ trajectory of vehicles to a map service provider. The map service provider can provide “assisted driving service” based on this information.
Bob has a vehicle with the “assisted driving service” provided by the map service provider.
Bob drives the vehicle from home to the company in the morning of a working day. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.11.3 Service Flows | Figure 5.11.3-1. Sensing at crossroads with/without obstacle
1. The 5G base station continuously collects 3GPP sensing data of the road status and the sensing result is continuously reported to the trusted third-party (e.g. the map service provider or ITS management platform) by 5G network according to the preconfigured refresh rate (e.g. in the midnight, it uses slow refresh rate with 0.2Hz, and in the working day morning, it uses fast refresh rate with 10Hz). The refresh rate can be adjusted according to the trusted third-party demand and network operator’s policy.
2. In the working day morning, Bob has started his road status sensing service when he begins driving his vehicle to his office.
3. Bob drives his vehicle from home to his office and started assisted driving service. The map service provider sends the road sensing request to the 3GPP core network.
4. In the crossroad, there are some higher buildings. It is difficult for Bob to timely detect other vehicles and VRUs in the area. As example in figure 5.11.3-1, Bob is driving his vehicle and crossing the crossroad toward the southeast of the crossroad. Linda is driving her motorcycle on a side road toward the main road which is also the southeast of the crossroad. The line of sight between Bob and Linda is blocked by the high building A which is at a corner of the intersection.
5. Linda’s motorcycle activity is continuously sensed by the base station under the help of other 5G system sensing entities.
6. The 5G system collects and associates the multiple 3GPP sensing data from multiple base stations with the crossroad location. Considering the obstacles (e.g., high buildings or trees) in this area, it impacts the sensing quality and availability of the 3GPP sensing data from the blocked base stations. So, the 5G system needs to select suitable 3GPP sensing data to derive the sensing result to guarantee the availability of the sensing service.
7. The motorcycle sensing result which includes the motorcycles moving speed, moving direction, position etc. is periodically reported to the the map service provider and ITS management platform.
8. The other vehicles in the crossroad have been sensed and related sensing result are also reported to the map service provider and ITS management platform.
9. The map service provider fuses the sensing result with the map and then sends to the Tom’s vehicle.
10. According to the continuously received motorcycle sensing results, the ITS management platform can analyze and identify that there will be a potential collision risk between Bob and Linda. The collision warning then is sent to Bob. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.11.4 Post Conditions | Bob’s vehicle receives the real-time map information which warns Bob that there is another cross-direction motorcycle driving towards his vehicle. Bob stops his vehicle before the crossroad to avoid a potential collision. With the assistance of RAN sensing, Bob arrives in the company safely and easily. Bob starts the daily work in the office.
Bob receives the warning and drives safely through the crossroads.
Linda can also ride safely to the crossroad. The potential risk of collision is avoided. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.11.5 Existing features partly or fully covering the use case functionality | None. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.11.6 Potential New Requirements needed to support the use case | [PR 5.11.6-1] The 5G system shall be able to support a mechanism to provide available sensing service in a target sensing service area.
[PR 5.11.6-2] The 5G RAN shall be able to collect 3GPP sensing data from requested target sensing service area according to the operator’s policy.
NOTE 1: The operator policy means to configure the target sensing service area, real time 3GPP sensing data collection or periodic collection etc.
[PR 5.11.6-3] The 5G system shall be able to report the sensing result to the trusted third-party with refresh rate which is requested by the trusted third-party e.g. a map service provider, and controllable by the operator, according to a business agreement.
NOTE 2: The sensing result can be the target object’s size, shape, position, moving direction, moving speed, etc.
[PR 5.11.6-4] The 5G system shall support means for a trusted third-party application, e.g. a map service provider to configure sensing per location.
[PR. 5.11.6-5] The 5G system shall be able to support the sensing service with given KPIs in Table 5.11.6-1.
Table 5.11.6-1 Performance requirements of sensing results for sensing at crossroads with/without obstacle
Scenario
Sensing service area
Confidence level [%]
Accuracy of positioning estimate by sensing (for a target confidence level)
Accuracy of velocity estimate by sensing (for a target confidence level)
Sensing resolution
Max sensing service latency[ms]
Refreshing rate [s]
Missed detection [%]
False alarm [%]
Horizontal
[m]
Vertical
[m]
Horizontal
[m/s]
Vertical
[m/s]
Range resolution
[m]
Velocity resolution (horizontal/ vertical)
[m/s x m/s]
Sensing at crossroads with/without obstacle
Outdoor
95
≤1
N/A
N/A
N/A
N/A
N/A
≤100
NOTE 2
≤ 0.1
≤5
≤5
NOTE 1: The terms in Table 5.11.6-1 are found in Section 3.1.
NOTE 2: The value is sourced from [28].
NOTE: In this use case base station is acting as sensing transmitter and/or sensing receiver. This is an example and other options can also be valid. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.12 Use case on Network assisted sensing to avoid UAV collision | |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.12.1 Description | With the help of current 5G networks, the commercialization of low-altitude UAVs has entered a new stage. UAV can perform surveillance, early warning for many scenarios, and other tasks in low altitude airspace below commercial flights such as delivery. In the logistics industry, UAV delivery is developed very quickly and is estimated to become a nearly 10-billion-euro market. UAV delivery can be widely used in food distribution, retail commodity delivery, postal delivery, provision of medical aids, precision agriculture delivery, industrial delivery, etc.
While the UAV is applied in so many industries, how to avoid collision and effectively manage the UAV traffic are key challenges. In general, the UAV can provide its moving information and surrounding dynamic environment sensed by its own sensors to UTM (Uncrewed Aerial System Traffic Management), then the UTM controls the flight trajectory of the UAV accordingly. But the sensing range of a single UAV is limited and during a UAV flying, the UAV surrounding environment status will not be detected in time which will cause the UAV deviation or collision.
Using the wide coverage of 5G network, a UE on boarding UAV can be a subscriber of the 5G network and connect with UTM via the 5G network.
As shown in figure 5.12.1-1, through the communication connection between the 5G base station and the UE on boarding UAV, the UE can provide its positioning information and UE ID to 5G network. The 5G network and UTM can corelate the UE positioning information, UE ID with UAV ID. Based on it, on one hand, the 5G RAN nodes can work together to send sensing signal toward specific direction, angle, area to track the flight of the UAV. On the other hand, the UE can collect the reflection signals from its environments and send the 3GPP sensing data associated with the UE ID to 5G network via the communication connection. Some sensing information of the UAV flying environment, e.g. higher building, obstacles and other UAVs nearby, which will impact its safe flying can be collected by UE onboarding a UAV and then reported to 5G core network to be exposed to the UTM. Furthermore, continuous sensing service can be provided during UAV flight.
The UTM is using different inputs like classic radar, via systems currently used in general aviation like FLARM or ADS-B. In this sense, UTM already combines different sources of location information and could further use 5G sensing as additional source for the specific UAV to avoid it deviating from course and collision. When multiple UAVs appear in the same area, the base station also can sense them at the same time.
Figure 5.12.1-1 Network assisted collision avoidance for the UAVs
The following service flow gives an example of UAV delivery in retail goods delivery. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.12.2 Pre-Conditions | Network Operator ‘MM’ provides a new 5G service named ‘5G Sensing Service’.
The UAV City Express ‘SS’ uses a specific UTM to assist its retail goods UAV delivery.
This UTM uses ‘5G Sensing Service’ provided by 5G network Operator ‘MM’ as additional source of information and navigate the UAVs.
Tom has ordered online daily necessities from a supermarket. Tom is living in downtown.
Jerry has also ordered online some food from a supermarket. Jerry is living in countryside.
The supermarket prepares the goods in packages and asks City Express ‘SS’ to deliver them to Tom and Jerry.
City Express ‘SS’ dispatches UAV A for Tom, and UAV B for Jerry.
UE A is on board UAV A and UE B is on board UAV B. Both UE A and UE B are subscribed to the 5G network of Operator ‘MM’.
Through the communication connections between the 5G RAN and the UE A/ UE B, the UE provides its positioning information and UE ID. The 5G network and UTM corelate the UE positioning information, UE ID with associated UAV ID. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.12.3 Service Flows | The UAV A and UAV B are flying to their destinations under the guidance of UTM with the assistance of the ‘5G Sensing Service’ provided by network Operator ‘MM’.
Considering that UAV A will fly to downtown, the UTM asks network Operator ‘MM’’s ‘5G Sensing Service’ to provide sensing service for UAV A, and the required sensing result includes the flying environment along its trajectory, e.g. altitude of the buildings, obstacles and other UAVs nearby.
Considering UAV B will fly to the countryside, the UTM asks network Operator ‘MM’’s ‘5G Sensing Service’ to provide sensing service for UAV B, and the required sensing result includes the flying environment along its trajectory e.g. obstacles, and other UAVs nearby.
The UTM requests the report period about UAV A and UAV B.
Each base station continuously sends sensing signaling along the UAV A’s trajectory, and the UE A on board of the UAV A can send the 3GPP sensing data which it collects for its surrounding environment back to the RAN using the 5G communication connection. Then, the 5G network can obtain a comprehensive UAV A’s flying environment sensing result e.g. building position, altitude, other nearby moving objects e.g. other UAV’s relative position, altitude, degree of moving angle, moving speed etc. to UTM.
Same sensing operation is also for UAV B.
The 5G network reports the sensing result periodically according to UTM’s request.
The UTM adjusts and guides the UAV flying trajectories considering the received sensing result and input from other sources (e.g. FLARM, ADS-B).
Considering UAV A is flying toward downtown, both the flying environment (e.g. many buildings) and wireless environment are complex compared with UAV B and its environment in countryside, the 5G network needs to configure different sensing operation for UAV A and UAV B to guarantee required sensing service quality, for example to operate sensing with shorter period, sensing KPI, and report sensing result with higher refresh rate for UAV A. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.12.4 Post-Conditions | The UAV A successfully delivers package to Tom and UAV B successfully delivers package to Jerry and return safely. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.12.5 Existing features partly or fully covering the use case functionality | None. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.12.6 Potential New Requirements needed to support the use case | [PR 5.12.6-1] The 5G system shall be able to provide a sensing service to track one specific target object and the environment around the target object with the sensing assistance information provided by the UE on board the specific target object or authorized third-party.
[PR 5.12.6-2] The base stations shall be able to sense multiple specific target objects and their environments at the same time.
[PR 5.12.6-3] The 5G system shall be able to provide a mechanism controllable by the operator, according to a business agreement, for a trusted third-party to request the sensing service related with a certain target object or multiple target objects of a certain location area.
[PR 5.12.6-4] Based on operator policy, the 5G system shall be able to provide a mechanism for a trusted third-party to request per location area different sensing services configuration (e.g. sensing KPI, report refresh rate etc.).
[PR 5.12.6-5] The 5G system shall be able to report sensing result of the environment around a specific target object to a trusted third-party.
NOTE 1: The sensing result of the environment for example can be its position, the size of obstacles around, and other moving objects nearby.
[PR 5.12.6-6] The 5G system shall be able to provide sensing service with follow KPIs:
Table 5.12.6-1 Performance requirements of sensing results for network assisted sensing to avoid UAV collision
Scenario
Sensing service area
Confidence level [%]
Accuracy of positioning estimate by sensing (for a target confidence level)
Accuracy of velocity estimate by sensing (for a target confidence level)
Sensing resolution
Max sensing service latency
[ms]
Refreshing rate
[s]
Missed detection
[%]
False alarm
[%]
Horizontal
[m]
Vertical
[m]
Horizontal
[m/s]
Vertical
[m/s]
Range resolution
[m]
Velocity resolution (horizontal/ vertical)
[m/s x m/s]
Network assisted sensing to avoid UAV collision
Outdoor
95
1
1
1
NOTE 2
1 NOTE 2
<1
NOTE 2
1
500
0.5
N/A
N/A
NOTE 1: The terms in Table 5.12.6-1 are found in Section 3.1.
NOTE 2: The KPI values are sourced from [25] and [40].
NOTE 2: In this use case base station is acting as sensing transmitter and/or sensing receiver. This is an example and other options can also be valid.
5.13. Use case on sensing for UAV intrusion detection |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.13.1 Description | UAV industry is developing quickly around the world with the widely usages in various scenarios such as aerial photography, police force, urban management, agriculture, geology, meteorology, electric power, emergency rescue and disaster relief, etc. Especially for the smart city in future, a large number of UAVs will be used to improve the quality of our daily life including industrial inspection, public security patrol, cargo transportation, live broadcast and so on. However, this also brings big challenges on UAV supervision due to the following reasons:
1) Low-altitude UAVs have characteristics as large number, small size, wide flying zone, widely used to execute complex and diverse tasks, which makes UAV supervision very difficult if only using the traditional radar system.
2) Non-cooperative UAVs could intrude some no-fly zone (e.g. airport, military base) intentionally or unintentionally which would lead to serious consequences, e.g. exposing private information using the camera, blocking other UAV traffic on the flying route.
5G radio signals can be used to provide wireless access for communication, meanwhile the 5G radio signals can also be used to generate sensing data for object detection e.g. sense presence or proximity of UAVs illegal flying in a specific area. 5G System could provide sensing service by processing sensing data and output sensing information (e.g. relative position, altitude, distance, velocity, direction). In this case, 5G System could be used for sensing the UAV intrusion in the scenarios of UAV illegal flying in restricted area include light rail, airports, government facilities, research institutes, high-speed railway stations, temporary performance venue and other permanent or temporary restricted areas.
Furthermore, considering that the UAV entering the restricted area is illegal and the UAV itself even could be illegal, this kind of sensing operation doesn’t require the cooperation of the UAV. That means the UAV may be unaware of the sensing operation. When multiple UAVs appear in the same restricted area, the 5G system can sense presence or proximity of multiple UAVs illegal flying at the same time.
Figure 5.13.1-1 UAV collision risks at light rail (Level1)
Another example is flight route protection area intrusion detection. Compared to the wide no-fly zone (e.g. airport, military base), the flight route of a UAV is pre-allocated by UTM for given time period with restricted space vertically and horizontally, and it is generally much narrower and longer giving rise to more stringent requirements of positioning of an intruder. Such route in space shall be protected from illegal or uncollaborated UAVs for potential collision and unlawful usage. The characteristics of flight route can be virtualized in Figure 5.13.1-2 as a 3D tunnel with a 40 x 20 meter cross section which shall be monitored or sensed continuously in space and time by the 5G system to detect the presence of unauthorized usage. If illegal UAV is detected over given UAV route, 5GS will trigger intrusion alarm and UTM will take further action to warn the UAV which has been assigned for that route for potential re-routing or other necessary actions.
Figure 5.13.1-2 UAV collision over flight routes (Level 2) |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.13.2 Pre-conditions | The UAVs owned by the logistics operator ‘YY’ will take off and fly. The logistics operator ‘YY’ requests UTM to manage potential illegal intrusion into the UAV flight routes protection area. The logistics operator ‘YY’ has provided the information of flight routes protection area to the UTM.
Network operator ‘MM’ provides 5G sensing service for the park, flight routes protection area of the logistics UAV and the light rail area with its 5G network covering the park, flight routes protection area of the logistics UAV and the light rail track. ‘MM’ can make use of base stations to sense the airspace within their coverage area and report the sensing information to the USS/UTM as defined in TS 23.256 clause 3.1.
The Light rail operator ‘XX’ uses a UTM to management potential UAV illegal intrusion along the light rail tracks. ‘XX’ has provided its restricted area information to the UTM.
There is a need to hold a ceremony with high security requirement in the park temporarily, turning the park in a restricted area where UAVs are not allowed to enter. The administrator has a subscription for UAV prevention service from the USS/UTM.
The UTM uses ‘5G Sensing Service’ provided by 5G network Operator ‘MM’ to detect potential UAV illegal intrusion for above scenarios.
The UTM requests that once a UAV is detected that its distance from the border of the restricted area is less than 10m, the 5G system should report the event to the UTM.
The Network operator ‘MM’ can configure energy consumption sensing mode with different sensing period, e.g. operate sensing one time per 50 seconds, per 10 seconds, per second etc. And in emergency condition, the 5G system can provide continuously sensing service according to the UTM’s request.
The light rail works from 5:30 am to 23:00 pm every day. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.13.3 Service Flows | Figure 5.13.3-1: Sensing for UAV intrusion detection
The 5G system periodically senses the restricted area whether there are UAVs flying into the restricted area border for both the Park, flight routes protection area of the logistics UAV and the light rail area.
There are three UAVs (A, B, C) flying around the restricted areas.
When UAV A flying near the Park is detected and closely tracked with required accuracy in the sensing area, the 5G system reports the sensing results to the UTM in real time and begins continuously sensing. Then, the UAV A flying into the flight routes protection area of the logistics UAV is detected, and closely tracked with required accuracy in the sensing area, the 5G system reports the sensing results to the UTM in real time and continuously senses.
When UAV B and UAV C flying near the light rail are detected, and closely tracked with required accuracy in the sensing area, the 5G system reports the sensing results to the UTM in real time and continuously senses.
To reduce energy consumption, the 5G system will notify the UTM that the 5G system cannot detect any UAVs illegal flying after a time period which is requested by the UTM. After that, the 5G system stops continuously sensing and begins periodically sensing operation according to the Network Operator’s policy.
The USS/UTM could trigger to send warning messages/notices to UAV controller based on analytical results based on the sensing information from the mobile network. Alternatively, the USS/UTM will trigger UAV countermeasures to prevent the UAV from flying in the no-fly area or flight routes protection area of the logistics UAV.
When the ceremony has been finished or the logistics UAV lands, the 5G system would stop sensing operation based on the request from UTM. And when the light rail stops operation between 23:00 pm to 5:00am next morning, the 5G system stops sensing operation to save energy. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.13.4 Post-conditions | The mobile network can provide sensing service for UAV intrusion detection with high quality and continuity, to improve the accuracy and efficiency of public safety supervision and management.
USS/UTM interacts with the mobile network for sensing service and perform UAV intrusion detection based on the sensing information exposed by network. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.13.5 Existing features partly or fully covering the use case functionality | None. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.13.6 Potential New Requirements needed to support the use case | [PR 5.13.6-1] The 5G system shall be able to provide a sensing service by using RAN to collect 3GPP sensing data.
[PR 5.13.6-2] The RAN shall be able to sense a target object by obtaining 3GPP sensing data without active involvement of the target object.
[PR 5.13.6-3] The 5G system shall provide mechanisms for an operator to transport 3GPP sensing data from RAN towards the core network.
[PR 5.13.6-4] Based on operator’s policy and subject to regulatory requirements, the 5G system shall be able to provide a mechanism for a trusted third-party to request the sensing service and based on the request, the base station shall be able to operate sensing periodically or continuously in certain location area for a certain amount of time.
[PR 5.13.6-5] Based on operator’s policy and subject to regulatory requirements, the 5G system shall be able to periodically expose sensing results to a trusted third-party application.
[PR 5.13.6-6] The 5G system shall provide a mechanism controllable by the operator, according to a business agreement, to report sensing result to a trusted third-party about a target object and multiple target objects when specific conditions are met.
NOTE: These conditions could be the target object distance from the restricted area border less than 10m or entering restricted area.
[PR 5.13.6-7] The 5G system shall be able to support the activation and deactivation of the sensing service according to operator’s policy.
[PR 5.13.6-8] The 5G system shall be able to provide a mechanism for network operator to configure and adjust sensing operation (e.g. authorization, sensing area, sensing operation period and sensing operation time window etc.) based on request from a trusted third-party.
[PR 5.13.6-9] The 5G system shall be able to provide sensing with following KPIs:
Table 5.13.6-1 Performance requirements of sensing results for UAV intrusion detection
Scenario
Sensing service area
Confidence level [%]
Accuracy of positioning estimate by sensing (for a target confidence level)
Accuracy of velocity estimate by sensing (for a target confidence level)
Sensing resolution
Max sensing service latency
[ms]
Refreshing rate
[s]
Missed detection
[%]
False alarm
[%]
Horizontal
[m]
Vertical
[m]
Horizontal
[m/s]
Vertical
[m/s]
Range resolution
[m]
Velocity resolution (horizontal/ vertical)
[m/s x m/s]
UAV intrusion detection
NOTE 2
Level 1
Outdoor
95
≤10
≤10
N/A
N/A
10
[5]
[≤1000]
[≤1]
≤5
≤5
Levle2
Outdoor
95
≤5
≤5
N/A
N/A
10
[5]
[≤1000]
[≤1]
≤5
≤5
NOTE 1: The terms in Table 5.13.6-1 are found in Section 3.1.
NOTE 2: Level 1 and level 2 depend on the size of the restriction area to be sensed.
NOTE: In this use case base station is acting as sensing transmitter and/or sensing receiver. This is an example and other options can also be valid.
5.14. Use case on sensing for tourist spot traffic management |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.14.1 Description | In order to ensure the sustainable development of tourist spots, the traffic flow management of tourist attractions should fully consider the space-carrying capacity, facility-carrying capacity, ecological-carrying capacity and other factors that may induce disasters within the area.
The scenic area controls the traffic flow through real-time monitoring, diversion of traffic and early warning and reporting. The flow control of tourist spots includes two aspects: passenger-flow management and vehicle-flow management.
Traffic data collection is an important part of traffic management. Base stations in tourist area can provide 5G communication service and also can sense the passenger and the vehicle in its coverage at gates or per unit area that are set with a finer granularity. For tourist spots with a large area, it will be convenient to use base station to have the traffic sensing data sources when it's difficult to deploy equipment like camera and other sensors. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.14.2 Pre-conditions | Network Operator A provides 5G services for a famous tourist spot.
The management department of the tourist spot has subscribed the sensing service provided by 5G network Operator A, and the base stations in the tourist area can be used to sense the traffic flow and the crowd density (for both including the vehicles and passengers) constantly.
Jim is the worker of the tourist spot and responsible for traffic management. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.14.3 Service Flows | Figure 5.14.3-1: Sensing for tourist spot traffic management
1. When the scenic area begins to open, Jim will operate the scenic area traffic monitoring system to start real-time traffic control.
2. The traffic management system of the scenic spot will send a service request to the operator network to start sensing the people and vehicles in the scenic spot.
3. The base stations at the entrance and exit of the scenic spot can sense the people and vehicles that enter or leave the place, and the base stations in the scenic spot can sense the people and vehicles for certain area (e.g. walkway, parking area).
4. Operator A reports the traffic sensing information from the base stations in the scenic spot to the traffic monitoring system. Based on the sensing information, the traffic management system could analyse the traffic status and decide whether the traffic in the area is congested.
5. If the congestion exceeds the threshold, the management system would notice Jim about the detail, and Jim would trigger to limit traffic to avoid traffic overload in the scenic spot. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.14.4 Post-conditions | With 5GS support to the traffic management system, the vehicles and tourists are controlled within a reasonable range, and the spot can operate normally during business hours. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.14.5 Existing features partly or fully covering the use case functionality | None. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.14.6 Potential New Requirements needed to support the use case | [PR 5.14.6-1] The 5G system shall be able to provide means to use base station(s) to perform sensing in certain area.
[PR 5.14.6-2] Subject to regulatory requirements and operator policy, the 5G system shall be able to expose sensing results to a trusted third-party application.
[PR 5.14.6-3] Subject to regulatory requirements and operator policy, the 5G system shall be able to support the activation and deactivation of the sensing service based on location.
[PR 5.14.6-4] The 5G system shall be able to provide sensing service with KPIs given in Table 5.14.6-1.
Table 5.14.6-1 Performance requirements of sensing results for tourist spot traffic management
Scenario
Sensing service area
Confidence level [%]
Accuracy of positioning estimate by sensing (for a target confidence level)
Accuracy of velocity estimate by sensing (for a target confidence level)
Sensing resolution
Max sensing service latency
[ms]
Refreshing rate
[s]
Missed detection
[%]
False alarm
[%]
Horizontal
[m]
Vertical
[m]
Horizontal
[m/s]
Vertical
[m/s]
Range resolution
[m]
Velocity resolution (horizontal/ vertical)
[m/s x m/s]
Tourist spot traffic management
Outdoor
95
[≤2]
N/A
[1]
N/A
[1]
[1]
[≤5000]
[≤0.2]
≤5
NOTE 2
≤5
NOTE 2
NOTE 1: The terms in Table 5.14.6-1 are found in Section 3.1.
NOTE 2: Missed detection or false alarm describes missing to acquire a sensing result or acquiring a wrong sensing result which referring to a target object (a person or a vehicle), in this use case will be missing detect a person or a vehicle, not referring to the number of a crowd of people or vehicles.
NOTE: In this use case base station is acting as sensing transmitter and/or sensing receiver. This is an example and other options can also be valid. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.15 Use case on contactless sleep monitoring service | |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.15.1 Description | Compared with wearable devices, contactless sensing technologies have more advantages in health status detection. 3GPP system are designed for catering people’s communication purpose, whose wireless signals are very rich and can be accessible ubiquitously. With additional processing, 3GPP system will breed new opportunities with contactless sensing technologies applied, such as smart health, smart home, smart city and even smart space.
Sleep Monitoring application describes the case that a human’s sleep situation is monitored without any wearable device [31]. Instead of utilizing capacitors as propagation medium, Sleep Monitoring application effectively reuses the current ubiquitously accessible medium, that is wireless signals to realize the sensing purpose. People’s presence, movement and even respiration will affect the wireless signal propagation, which on the receiving side will be presented as the fluctuation of waveform’s intensity, phase shift and etc.
Figure 5.15.1-1 describes how the wireless signals that are propagated via the established direct network connection (i.e. between the radio access network and 5G UE) will be affected and distorted by the target sensing object. Generally, when people are sleeping, regular chest rise and fall will cause additional vibration of the target object when detecting the doppler [37], this is defined as the micro doppler effect in radar [32]. By observing the micro doppler effect, people’s respiration rate per minute can be counted.
Figure 5.15.1-1: People’s respiration affected 3GPP wireless signal propagation in an indoor environment
NOTE 1: The transmitter as shown in Figure 5.15.1-1 is an indoor small base station as described in TS22.261 [33].
NOTE 2: The transmitter as shown in Figure 5.15.1-1 can also be a CPE that is used for this service.
This sleep monitoring application can help to diagnose early symptoms of some diseases, e.g. milder symptoms of sleep apnea before it develops worse [41]. Through monitoring people’s breathing, i.e. respiration rate, and the breathing stoppage duration, the application server can give instructions to the user on whether or not the user is experiencing sleep apnea, and the user in return can adjust lifestyles such as losing weight or quitting smoking to avoid worse cases.
- A person's respiratory rate is the number of breaths you take per minute. The normal respiration rate for an adult at rest is 12 to 20 breaths per minute. A respiration rate under 12 or over 25 breaths per minute while resting is considered abnormal [42].
- The breathing stoppage duration is the amount of time that a sleep apnea patient stops breathing, which can be from 10 seconds to two minutes or more [41]. We take breathing stoppage duration = 10 seconds for example as the trigger of the event reporting to the application server. When the user triggers this sensing service, the sensing system will monitor this special event and report it to the application server. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.15.2 Pre-conditions | The device installing this sleep monitoring application is 5G UE.
There is a service agreement between MNO and sleep monitoring operator. The MNO can also be the sleep monitoring application provider. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.15.3 Service Flows | 1. The application user Bob triggers the sleep monitoring application on the 5G UE. When the application server receives the request, the application server contacts the 5G system to trigger the sensing service to monitor Bob’s respiration rate.
2. 5G system discovers a base station (or CPE) to start the sleep monitoring sensing service.
3. The base station (or CPE) coordinates with Bob’s phone (5G UE) to perform the sensing measurement process. The base station and the 5G UE can be transmitter and receiver or vice versa. The receiver measures the 5G wireless signals (e.g., number of detected transmission paths, micro doppler shift, etc.) and collects them as the 3GPP sensing data.
4. 3GPP sensing data is processed to derive the sensing results (e.g. respiration rate) locally or is provided to the 5G network: 5G network processes the 3GPP sensing data to derive the sensing results and exposes the sensing results to the sleep monitoring application server.
5. The 5G UE receives the sleep monitoring feedback from the application server and shows it to the application user Bob. Bob can have sleep apnea and needs the application to further monitor his breathing stoppage duration. An event with “breathing stoppages duration = 10 seconds” is triggered by Bob and received by the application server, which then contacts the 5G system to trigger this event.
6. 5G system adjusts the sensing measurement process and executes Steps 3-5. When the event report criteria are satisfied, i.e. Bob is detected to have a 10-second breathing stoppages duration, the application server will receive the notification sent by 5G system. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.15.4 Post-conditions | The user experiences the sleep monitoring application enabled by the 5G network. Bob changes his lifestyle, he does more exercise, and tries to lose weight to avoid the sleep apnoea problem. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.15.5 Existing feature partly or fully covering use case functionality | None. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.15.6 Potential New Requirements needed to support the use case | [PR 5.15.6-1] The 5G system shall support mechanisms to discover and configure a UE and a base station to perform sensing measurement process in a certain sensing service location area.
[PR 5.15.6-2] The 5G system shall support mechanisms to derive and expose sensing results to a trusted third-party.
[PR 5.15.6-3] The 5G system shall be able to provide 5G wireless sensing service with the following KPIs:
Table 5.15.6-1 Performance requirements of sensing results for contactless sleep monitoring
Scenario
Sensing service area
Confidence level [%]
Human motion rate accuracy
[Hz]
Accuracy of positioning estimate by sensing (for a target confidence level)
Accuracy of velocity estimate by sensing (for a target confidence level)
Sensing resolution
Max sensing service latency[ms]
Refreshing rate [s]
Missed detection [%]
False alarm [%]
Horizontal
[m]
Vertical
[m]
Horizontal
[m/s]
Vertical
[m/s]
Range resolution
[m]
Velocity resolution (horizontal/ vertical)
[m/s x m/s]
Sleep monitoring
Outdoor (bedroom)
95
0.033
NOTE 2
N/A
N/A
N/A
N/A
N/A
N/A
60s
60
5 NOTE 3
5
NOTE 3
NOTE 1: The terms in Table 5.15.6-1 are found in Section 3.1.
NOTE 2: Respiration rate = 18 times/min as reference, any detected value in [16,20] satisfies accuracy requirements, 0.033Hz corresponds to 2 times/min.
NOTE 3: Detect event = “breathing stoppages duration >= 10 seconds” as reference.
NOTE: In this use case base station and UE is acting as sensing transmitter and/or sensing receiver. This is an example and other options can also be valid. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.16 Use case on Protection of Sensing Information | |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.16.1 Description | This use case re-uses the scenario where a UE performs sensing to detect intruders in the home, as per use case 5.1 (intruder detection in smart home). The additional aspect introduced in this use case is that there is an unauthorised user that is attempting to collect sensing information from Mary's home. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.16.2 Pre-conditions | Refer to use case 5.1 where 5G CPEs (i.e. UEs) are set up to detect intruders when Mary's home is vacant as her family is on holiday. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.16.3 Service Flows | An unauthorised user is in the vicinity of Mary's home.
In Mary's home, the 5G CPE transmits 5G signals, and the reflected signals are used by the unauthorised user's device to collect sensing information.
As the 5G signals from the CPEs in Mary's home are protected, the unauthorised user's device fails to derive any sensing information. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.16.4 Post-conditions | The privacy of sensing information in Mary's home is preserved.
The unauthorised user cannot use the 5G signals to detect that the family is not at home. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.16.5 Existing features partly or fully covering the use case functionality | None |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.16.6 Potential New Requirements needed to support the use case | [PR 5.16.6-1] The 5G system shall provide a mechanism to protect identifiable information that can be derived from the 3GPP sensing data from eavesdropping. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.17 Use case on health monitoring at home | 5.17.1 Description
Tom is an elderly person living in his house. Since he has become weaker, he has subscribed to a wireless sensing service of his MNO so that his health state (including e.g. lack of movement, detection of falls, breathing rate) can be monitored 24/7 when he is at his home. Wireless sensing is a promising technology for health monitoring [34] [35] [36] [37] that does not require a person to wear a health monitoring device on his/her body (which people may forget, requires recharging, and can be uncomfortable to wear over long periods of time).
A single base station is not capable of covering Tom’s home with good coverage. Thus, multiple base stations capable of acting as wireless transmitters and/or receivers cooperate to ensure excellent coverage. Furthermore, the received reflected radar signal is sometimes weak, and thus, the MNO offers the possibility of using a phone with wireless sensing receiving capabilities. The usage of the phone also allows more accurate measurements of certain vital signs (e.g. breathing rate) since the phone is close to Tom. The usage of the phone also allows the MNO to offload the workload from the base station to the phone. Also other UEs in vicinity of Tom could take part in the sensing.
Fig. 5.17.1.1 shows a schematic illustration of how such system could look like, whereby the blue arrow indicates transmitted wireless sensing signals from Base Station A, and the green dashed arrows indicate reflected wireless sensing signals received by Base Station B and Tom’s phone.
Figure 5.17.1-1: Example of a distributed sensing system (incl. two base stations, a UE and a Sensing function). |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.17.2 Pre-conditions | 1. Tom has subscribed to the sensing service offered by an MNO.
2. The MNO has deployed two RAN entities (e.g. base station A and base station B) that are capable of wireless communication and sensing. The base stations can act as wireless sensing transmitters and/or wireless sensing receivers. These two base stations are sufficiently close to Tom's house to provide good coverage in and around Tom's house in the frequency bands used for wireless sensing. Tom’s subscription includes a phone with wireless sensing capabilities for more accurate sensing.
3. Tom has a mobile phone that is capable of detecting wireless sensing signals. Tom can use it to directly and/or more accurately sense his health state.
4. The 3GPP sensing data from the RAN and UEs is collected and processed by a sensing function that can be deployed in the 5G network or provided by an external application or a combination thereof. The exact separation of functionalities between those entities is not explored further in this use case. The sensing function is assumed to be capable of extracting health state information, e.g. lack of movement, detection of falls, breathing rate from this 3GPP sensing data, determine the sensing requirements (e.g. accuracy), and determine the criteria/thresholds (e.g. lack of movement) on when to create an alert. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.17.3 Service Flows | 1. Based on Tom’s sensing subscription, information about a user (in this case Tom) is obtained including information about where he lives and sensing requirements that are needed (e.g. sensing of movements which can be used to detect falls or sufficient activity of Tom).
2. Base station A starts transmitting the wireless sensing signal.
3. Tom is currently located in the living room. If Tom is at this location, base station A can hardly receive the reflection of its transmitted sensing signal. However, base station B can receive a strong reflection of that sensing signal. Base station A and B coordinate with each other so that Base Station B is capable of processing the received reflected wireless sensing signal, generating 3GPP sensing data that is sent to a sensing function for further processing. In this manner, movements of Tom in and around the house can be monitored, and it can be detected if Tom falls.
4. Tom feels a bit weak today and decides to measure his health state in more detail. Tom was told that he needs to carry his phone to enable this. Tom picks up his phone and uses it as a wireless sensing receiver capable of picking up and processing the reflected wireless sensing signal transmitted by Base station A. This requires the phone to coordinate wireless sensing with Base station A, which includes for example exchanging of capabilities (since the sensing capabilities can differ per phone) and coordinating of timing/frequencies of sensing signals. Since Tom’s phone is very close to Tom, Tom can use his phone for more accurate sensing of certain vital signs, such as breathing rate and heart rate. The phone sends measurements to a sensing function for further processing. When Tom goes to sleep, he puts his phone next to him to monitor his vital signs also during the night.
5. When Tom’s health state is determined to be in danger, e.g., when Tom falls or stops moving, the family or emergency services gets alerted of such event. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.17.4 Post-conditions | The sensing service/application receives accurate 3GPP sensing data about Tom and can generate alerts if an adverse event happens to Tom. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.17.5 Existing features partly or fully covering the use case functionality | None. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.17.6 Potential New Requirements needed to support the use case | [PR 5.17.6-1] The 5G system shall be able to coordinate wireless sensing among a set of RAN entities and UEs.
[PR 5.17.6-2] The 5G system shall support a mechanism for the 5G network to retrieve the wireless sensing capabilities from UEs and RAN entities, and for the UEs and RAN entities to exchange capabilities amongst each other.
[PR 5.17.6-3] The 5G system shall support a mechanism for two or more authorized UEs and/or RAN entities to take part in the wireless sensing of a target, whereby the authorization may be provided based on location.
[PR 5.17.6-4] The 5G system shall support a mechanism to provide wireless sensing capable UEs and RAN entities with information of which network entity to send the 3GPP sensing data to. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.18 Use case on service continuity of unobtrusive health monitoring. | 5.18.1 Description
An elderly home has installed a new 5G system capable of providing communication and sensing capabilities through the facilities as illustrated in Figure 5.18.1-1. The deployed 5G system includes multiple sensing devices, e.g., base stations, providing connectivity and sensing capabilities. These sensing devices can perform wireless sensing of a target, in this case, health monitoring (e.g. fall/activity detection [34][35][36] or wireless sensing of vital signs such as heart rate [38] or breathing rate [37] of one or more persons). Since elderly people move through the facilities, it is important to provide health monitoring independently of the base station used for sensing. The staff of the elderly home really likes this new 5G wireless sensing feature because it is unobtrusive and offers various advantages over the old system that they use with body worn sensors. For example, they don’t need to recharge or replace the batteries of body worn sensors anymore and remind people or help people to wear them after they took them off (for example to take a shower). The elderly people themselves also like it more, since the body worn sensors often made them feel uncomfortable, especially during sleep or during hot days. Installing cameras was not seen as a good alternative because of the privacy concerns.
In the provided use case, base stations cooperate with each other to ensure service continuity for sensing of a ‘target’ user. In this particular scenario, a user, Robert, is considered who moves through the facilities. Robert's health is quite frail and requires continuous monitoring of his health state without interruption. Robert is currently sensed by means of (indoor) base station A located near his room and is moving out of the sensing area of base station A and approaching the sensing area of base station B covering the recreation/eating area and part of the hallway. Base station A and base station B cooperate in such a way that it is ensured that base station B has started wireless sensing of Robert before base station A stops its wireless sensing of Robert. When Robert is in range of both base station A and B, both base stations can cooperate to perform simultaneous wireless sensing. Similarly, when Robert decides to go for a walk to the garden that is covered by Base Station C, the sensing of Robert is seamlessly continued by Base Station C. The 3GPP sensing data is collected and processed by the 5G network (e.g. to detect certain movement patterns) and then sensing results are exposed to a sensing application that is automatically monitoring health anomalies. If a health anomaly is detected (e.g. Robert falls down), an alarm is triggered indicating the health condition as well as the location of the monitored user.
Figure 5.18.1-1: Example of service continuity between Base stations A, B and C. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.18.2 Pre-conditions | 1. MNO operates a 5GS providing wireless sensing capabilities through a set of base stations installed in the elderly home and its garden, as illustrated in Figure 5.18.1-1.
2. Robert has subscribed to the wireless sensing service offered by the 5GS in cooperation with an external application provider. Robert provided some identification information, e.g. which room he resides in, the identity of his mobile phone and/or some physical characteristics (e.g. length). The application provider has no knowledge of the RAN infrastructure operated by the MNO. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.18.3 Service Flows | 1. Robert is currently located in his room in the elderly home. The closest nearby base station, i.e. base station A infers, based on the identification information provided by Robert, that Robert is in his room. Base station A starts wireless sensing of Robert, whereby it sends the 3GPP sensing data to the 5GC for further processing, after which the sensing results are sent to a sensing application to detect health anomalies
2. Robert starts moving toward the garden.
3. When leaving his room and entering the hallway, the wireless sensing signal conditions of base station B become better than those of base station A.
4. The 5G system coordinates the responsibility of sensing Robert from base station A to base station B. During this time, both base station A and B might sense Robert.
5. Base station B is used for sensing Robert
6. Base station A can stop sensing Robert.
7. When leaving the elderly home and entering the garden, Base Station C continues the sensing of Robert. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.18.4 Post-conditions | Robert’s vital signs are monitored without interruption independently of his location. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.18.5 Existing features partly or fully covering the use case functionality | None. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.18.6 Potential New Requirements needed to support the use case | [PR 5.18.6.1] The 5G system shall support continuity of sensing of a target that may move across a sensing area that may be bigger than the coverage area of a single sensing transmitter.
[PR 5.18.6.2] The 5G system shall support simultaneous wireless sensing of a target by means of multiple sensing devices.
[PR 5.18.6-3] Subject to operator’s policy, the 5G network may provide secure means for the operator to expose information on sensing service availability (e.g., if sensing service is available and the supported KPIs) in a desired sensing service area location to a trusted third-party. |
e8cee4e428329a7668584ba76bf8de13 | 22.837 | 5.19 Use case on Sensor Groups |
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