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5.12.1 Description
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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.
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5.12.2 Pre-Conditions
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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.
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5.12.3 Service Flows
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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.
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5.12.4 Post-Conditions
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The UAV A successfully delivers package to Tom and UAV B successfully delivers package to Jerry and return safely.
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5.12.5 Existing features partly or fully covering the use case functionality
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None.
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5.12.6 Potential New Requirements needed to support the use case
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[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
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5.13.1 Description
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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)
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5.13.2 Pre-conditions
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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.
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5.13.3 Service Flows
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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.
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5.13.4 Post-conditions
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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.
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5.13.5 Existing features partly or fully covering the use case functionality
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None.
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5.13.6 Potential New Requirements needed to support the use case
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[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
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5.14.1 Description
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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.
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5.14.2 Pre-conditions
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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.
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5.14.3 Service Flows
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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.
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5.14.4 Post-conditions
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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.
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5.14.5 Existing features partly or fully covering the use case functionality
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None.
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5.14.6 Potential New Requirements needed to support the use case
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[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.
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5.15 Use case on contactless sleep monitoring service
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5.15.1 Description
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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.
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5.15.2 Pre-conditions
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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.
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5.15.3 Service Flows
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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.
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5.15.4 Post-conditions
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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.
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5.15.5 Existing feature partly or fully covering use case functionality
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None.
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5.15.6 Potential New Requirements needed to support the use case
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[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.
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5.16 Use case on Protection of Sensing Information
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5.16.1 Description
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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.
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5.16.2 Pre-conditions
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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.
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5.16.3 Service Flows
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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.
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5.16.4 Post-conditions
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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.
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5.16.5 Existing features partly or fully covering the use case functionality
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None
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5.16.6 Potential New Requirements needed to support the use case
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[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.
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5.17 Use case on health monitoring at home
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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).
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5.17.2 Pre-conditions
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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.
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5.17.3 Service Flows
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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.
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5.17.4 Post-conditions
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The sensing service/application receives accurate 3GPP sensing data about Tom and can generate alerts if an adverse event happens to Tom.
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5.17.5 Existing features partly or fully covering the use case functionality
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None.
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5.17.6 Potential New Requirements needed to support the use case
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[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.
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5.18 Use case on service continuity of unobtrusive health monitoring.
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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.
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5.18.2 Pre-conditions
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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.
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5.18.3 Service Flows
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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.
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5.18.4 Post-conditions
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Robert’s vital signs are monitored without interruption independently of his location.
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5.18.5 Existing features partly or fully covering the use case functionality
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None.
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5.18.6 Potential New Requirements needed to support the use case
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[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.
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5.19 Use case on Sensor Groups
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5.19.1 Description
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Sensing has been considered in this technical report in terms of interaction between a UE and a base station. This information however is only partial, as it extends along a limited UE-base station axis. This information however can be considered a component of a scene that, when gathered with other available sensor data, can be synthesized into more comprehensive information.
Where the sensor is video, LiDAR, sonar, etc., (that is, it operates in some other way than 3GPP defined radio access technology,) it is still valuable to gather simultaneous sensor data and combine it. Only this way can sensor data capturing a scene (such as the front and back and sides of an object of interest, etc.) be obtained.
In the Localized Mobile Metaverse Services use case 5.1 in [11], includes the following text "His mobile device begins to collect information about his surroundings. The collected information can include information that is obtained by interacting with nearby devices (e.g. sensors and other mobile devices)."
This use case explores the implications of this function. Specifically, how can a UE identify sensors that are present that can provide information sought by the UE?
In this particular use case, on a construction site, a crane is lifting a large object near a tower. Construction worker safety, efficient pursuit of tasks and other situational awareness to prevent disasters are important tasks. Instead of merely relying on the crane operator, this use case allows the 5G system to model and track the tower, crane and payload as it is in motion.
Figure 5.19.1-1: Group Sensing, to provide sensing services
In Figure 5.19.1-1, the UE is on a construction site. It seeks to identify sensors available at that site to provide sensing data potentially relevant to obtaining information for the user. These sensors - in the UE's proximity and available to provide sensor data (that is, this service is authorized,) comprise a sensor group.
Correspondence between Sensor Groups and other groups defined in stage 2 are neither implied by this use case nor excluded. There is no correspondence between Sensor Groups and other groups defined in stage 1.
The use case assumes that sensors that can form a sensor group are either UEs or communicate by means of a UE (as a kind of 'split terminal equipment (TE)' UE.)
It is essential to capture a 'synchronous' group of sensors and their movements in 3 dimensions in order to optimally combine the sensor data for the purpose of localization computations. This is particularly important when the viewer is near a large object or any non-static object must be modeled on all sides. This is an active area of research, for example in 6DoF Tracking and sensing. [44] The techniques described in this paper concern how to determine the 3D position and orientation of drones with synchronization, but it is clear that this is a fundamental requirement of a group of sensors providing input on a single physical object in (absolute or relative) motion.
The synchronous group of sensors form a logical set of devices whose data acquisition is critical for a particular task. The handling of this group is unique to this problem domain because (i) the need to synchronize the uplink transmissions of sensor measurement data of members of the group, so they can be combined in a timely way to produce a meaningful sensor measurement result of an object in motion, (ii) the dynamic nature of this group as the set of sensors that are appropriate to use can change often: the set of sensors prepared to obtain sensor measurement data of moving objects will change over time.
In this use case, a user's UE identifies a sensor group, through interaction with an AS. Part of identification of the sensors in the group is obtaining sufficient information that the user can become authorized to obtain sensor data, and the relevant service access information is obtained. The goal of the use case is to enable the acquisition of sensor data in a UE's proximity. The communication of the sensing data itself is out of scope of this use case.
Discovery of the kind described here can potentially be accomplished by different radio technologies, e.g. NR ProSe, UWB, IEEE 802.11, etc.
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5.19.2 Pre-conditions
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Benoît inspects various construction sites. He has a UE equipped with a set of surveillance and appraisal applications.
On construction sites he visits, there are sensors deployed. Some are UEs, e.g. using NR-based sensing. Other sensors include video cameras, LiDAR equipment and passive infrared sensors. These are not, generally, installed directly in the terminal equipment, but rather use the terminal equipment to communicate, as shown in figure 5.19.2-1.
Figure 5.19.2-1: Sensors available to become a sensing group
In the scenario above, (a) is a UE that serves various sensors that are themselves not UEs. The means by which these sensors communicate with the UE is out of scope of this use case. They could be e.g. connected by means of a physical cable. (b) is a UE that is capable of 3GPP defined sensing. (c) is a UE that can operate the UE camera for sensing purposes.
As the RF measurement data contains sensitive information (e.g. location of sensing transmitter/receiver, information about objects) from the 3GPP system it is processed in the 5G network to produce sensing results. 3GPP sensing data is not shared outside of 5G network. Application enabler layer combines these results with other data like non-3GPP sensing data to produce combined sensing results.
In this example (a) and (b) are authorized and ready to send mobile originated sensing data to an AS.
The non-3GPP sensing data from UEs and sensing results from 3GPP network acquired by the AS can be combined in software in a manner that is out of scope of the 5G standard. In this use case, the combination is performed by the AS.
Benoît's UE, (c), is authorized to access the media (the sensing result output of the AS produced by taking account of the non-3GPP sensing data from (a) and (b), sensing results from 3GPP network) provided by the AS.
Benoît, using UE (c), monitors the construction site for safety and efficiency.
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5.19.3 Service Flows
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Benoît's UE (c) uses functionality provided by the 5G system to seek to determine the existence of UEs (a) and (b), referring to Figure 5.19.2-1.
UE (c) has knowledge of the AS that accumulates sensor information that could be of interest.
UE (c) requests of the AS that accumulates sensor information for a sensor group: what sensors are in the proximity?
UE (c) is able to become authorized to receive information concerning the sensor group.
The Application Server (AS) requests the 5G system obtain a sensing group.
The 5G system will identify the set of sensing group members that provide the AS with sensor information that are in the proximity of UE(c). The 5G system will strive to synchronously locate 4 or more devices, to be localized within 10cm of accuracy, with accuracy of measurement within 5 ms of synchronization.
NOTE: It is impractical for the AS to continuously track the location of each of these UEs because their location can change and this information is needed only on demand. The group needs to be captured together, at the same time, since the sensor data of the group needs to be interpreted by UE (c) together.
The AS provides UE (c) with sufficient information to identify the sensing group that are ready to provide non-3GPP sensing data and sensing results as well as how to get sensing data from the sensing group from the AS.
UE (c) requests to obtain combined sensing results from the AS/sensing group. The sensors must be within proximity and their locations are known with great accuracy (within 10cm in 3D), with accuracy of measurement within 5 ms of synchronization.
UE (c) is authorized to obtain combined sensing results from the AS/sensing group.
UE (a), UE (b) provide non-3GPP sensing data and the network provides sensing results. These are received by the AS and combined. This combined sensing result is provided to UE (c) by the AS.
UE (b) is mobile and its position varies. UE (c) must identify its position with sufficient accuracy to interpret the sensing result meaningfully. Since UE (b) is mobile, its position and movements must be tracked to provide accuracy up to 10 cm, with accuracy of measurement within 5 ms of synchronization.
UE (b) leaves the proximity of UE (c). UE (c) identifies that UE (b) has left the sensing group.
Later, UE (b) returns to proximity of UE (c). UE (c) identifies that UE (b) has joined the sensing group, including its position within 10 cm, with accuracy of measurement within 5 ms of synchronization.
The crane operations are monitored by sensors (a) and (b), providing different perspectives by means of non-3GPP sensing data from non-3GPP sensors and sensing results from the 3GPP network to the AS.
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5.19.4 Post-conditions
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Benoît, making use of UE (c), is able to ascertain with very high accuracy the location and movement of the entire group of UEs that can form a sensor group. The ability of UE (c) to identify the position and membership of the group continues over time, so that the current membership of the group is known, and that membership can change.
The AS is able to combine the non-3GPP sensing data acquired by non-3GPP sensors and sensing results acquired by 3GPP network from different perspectives and produce a useful 3D representation of the site to the site supervisor, who receives the combined sensing result by means of media delivered from the AS to the Benoît's UE (c).
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5.19.5 Existing feature partly or fully covering use case functionality
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There are requirements specified in 22.261, 6.37.2 to support ranging services that are relevant to this use case. These were developed in the FS_Ranging study. [43]
- The 5G system shall be able to support for a UE to discover other UEs supporting ranging.
- The 5G system shall be able to start ranging and stop ranging according to the application layer’s demand.
- The 5G system shall be able to provide mechanisms for a MNO, or authorized third-party, to provision and manage ranging operation and configurations.
- The 5G system shall be able to support ranging enabled UEs to determine the ranging capabilities (e.g. capabilities to perform distance and/or angle measurement) of other ranging enabled UEs.
- The 5G system shall be able to allow a ranging enable UE to determine if another ranging enabled UE is stationary or mobile, before and/or during ranging.
- The 5G system shall allow ranging service between 2 UEs triggered by and exposed to the application server.
Differences between this use case and the above ranging requirements, and ranging in general include:
- Sensing data is not acquired 'between UEs' but by means of different sensing technologies.
- It is not sufficient to discover other UEs that support sensing: these must be in the discovering UE's proximity and the discovered UE's precise location must be ascertained.
- In this use case, a 'sensing group' is formed, where in Ranging, all range information was acquired through interactions directly (or indirectly if relayed) between UEs.
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5.19.6 Potential New Requirements needed to support the use case
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[PR 5.19.6-1] Based on third-party request, the 5G system shall be able to discover a suitable sensing group where sensing transmitters and receivers are within 100m range to be localized within 10cm of accuracy, with accuracy of sensing measurement process within 5 ms of synchronization.
[PR 5.19.6-2] Based on third-party request, the 5G system shall be able to discover a sensing group in the proximity of the UE that is requesting the service from the AS.
NOTE: This requirement assumes that a UE requests an AS to discover a set of sensing group members that have sensing functions that can provide sensing service.
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5.20 Use case of Sensing for Parking Space Determination
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5.20.1 Description
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Sensing technology can improve the user experience in parking garage via enabling the vehicle and parking garage to get more information, e.g. information whether a parking space is available or not. The indoor/underground parking garage can install multiple Sensing receivers and Sensing transmitters throughout the concrete structure for detecting the availability of the parking space. The outdoor parking garage can also exploit multiple Sensing receivers and Sensing transmitters for detecting the availability of the parking space.
Another related use case is automated parking e.g. AVP (Automated Valet Parking) and AFP (Automatic Factory Parking) [45] where cars are provided with drive-path information to do automated parking in a given parking lot facility. Connectivity is an important component in automatic parking, and the 3GPP sensing technology can serve as the way to determine available parking spaces and the best route for a car to reach it.
The coverage could be either a public network or a private network specifically for the parking garage. For the Sensing receiver(s) and Sensing transmitter(s) indoor, see figure 5.20.1-1, one deployment scenario is that Sensing receiver(s) and Sensing transmitter(s) can be ceiling-mounted and located in such a way as to provide sensor coverage for the parking bays within the structure, where the Sensing transmitter and Sensing receiver can be co-located. Another deployment method is that some Sensing receiver(s) and Sensing transmitter(s) can be ceiling-mounted and some can be mounted on the floor or wall, where the Sensing transmitter and Sensing receiver can be separately located. For the Sensing receiver(s) and Sensing transmitter(s) outdoor, see figure 5.20.1-2, Sensing receiver(s) and Sensing transmitter(s) can be deployed at a relative high place to guarantee the coverage of the parking garage.
Figure 5.20.1-1: Parking space determination (indoor deployment)
Figure 5.20.1-2: Parking space determination (outdoor deployment)
Multiple methods can be used via using the sensing signals emitted from the Sensing transmitter to detect the target object/area and the sensing signals bounced/reflected. For example, the Sensing receiver can measure the reflected signal power of the target area [8]. Since the cars are usually made of metal materials and the ground is, on the contrary, covered by cement or plastic cement, these objects can vary significantly on the reflected signal power, thus the Sensing receiver can distinguish whether a parking space is taken by simply measuring the reflected signal power difference. Another example method is that the Sensing receiver(s) and Sensing transmitter(s) can identify a parking space availability by monitoring the target movements. Comparing with the stationary objects such as ground and poles, the Sensing receiver(s) and Sensing transmitter(s) can easily distinguish a car when a car is parking or leaving, thus by measuring the distance/angle/velocity, the Sensing receiver(s) and Sensing transmitter(s) can record that a parking space is occupied when a car is parking, and that a parking space is free when a car is leaving. Or the Sensing receiver(s) and Sensing transmitter(s) can also detect a parking space availability by generating a 3-D point cloud [9], then both the stationary and moving target can be easily detected in a 3-D point cloud especially with some backend data processing skills such as machine learning/deep learning.
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5.20.2 Pre-conditions
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This use case is about a public multi-storey parking garage who has installed Sensing receiver(s) and Sensing transmitter(s) throughout the concrete structure to detect the positions of people, objects, and vehicles within the garage. The concrete structure can make coverage difficult and, especially in underground levels, coverage provided by external transmitters can be very poor. This parking garage can provide the information to the entering vehicles about the availability of the parking space.
Consider an example scenario shown in Fig. 5.20.2-1. A typical parking space is with length 5 m and width 2.5 m. So, from the horizontal dimension, the resolution requires to distinguish different parking spaces. The results can be aggregated by the parking garage operator and the parking state can be updated in seconds even when the coverage of the parking garage is poor, which helps avoid a wasting of time for the entering vehicles.
Figure 5.20.2-1: Example of sensing scenario
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5.20.3 Service Flows
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1. James wants to park his car at the public parking garage in floor #B2. His vehicle, on entering the public parking garage, queries the parking garage service for availability of a parking bay in floor #B2.
2. The parking garage operator can activate the sensing devices in floor #B2 for sensing. Sensing receiver(s) and Sensing transmitter(s) sense the parking spaces without interfering each other or with bearable interference. The sensing results can be aggregated by the parking garage operator.
3. With the aggregated sensing results, the parking garage operator can send sensing results back with an addition to the dynamic map corresponding to the floor #B2 which shows the current status of parking bays in the structure.
4. James can see the available parking bays on his in-car display and choose a suitable one.
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5.20.4 Post-conditions
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Thanks to sensing, James has found a parking space on the correct floor without issue, making his life easier during daily travel.
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5.20.5 Existing features partly or fully covering the use case functionality
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None.
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5.20.6 Potential New Requirements needed to support the use case
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[PR 5.20.6-1] The 5G system shall be able to provide sensing services in licensed and unlicensed spectrum.
[PR 5.20.6-2] The 5G system shall be able to authorize Sensing receiver(s) and Sensing transmitter(s) to participate in a sensing service.
[PR 5.20.6-3] Based on operator’s policy, the 5G system shall enable a trusted third-party to request the activation of the sensing service with specific KPI requirement, as well as deactivation of the same service.
[PR 5.20.6-4] The 5G system shall be able to support charging for the sensing services (e.g. considering service type, sensing accuracy, target area, duration).
[PR 5.20.6-5] The 5G system shall be able to provide a sensing service considering the interference to the Sensing service caused by the sensing operations between multiple Sensing transmitter(s) and Sensing receiver(s).
[PR 5.20.6-6] The 5G system shall be able to provide sensing with following KPIs.
Table 5.20.6-1 Performance requirements of sensing results for parking space determination
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]
Parking space determination
Indoor/ outdoor
95
0.5
0.5
0.1
N/A
2.5m perpendicular to the parking space
5m parallel to the parking space
N/A
1000
1
1
5
NOTE: The terms in Table 5.20.6-1 are found in Section 3.1.
5.21. Use case of Seamless XR streaming
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5.21.1 Description
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Extended Reality (XR) is an important 5G use case. Split-rendering architectures, where the heavy XR video rendering computation is done at the application server based on control information received from the UE, poses strict Quality-of-Service (QoS) requirements in terms of round-trip latency and throughput for delivering the video and control info.
It is therefore crucial to always maintain a high-quality wireless link for XR. Thus, it is critical to predict and adapt fast to wireless channel changes. This is especially true in Millimeter wave bands in which the channel and propagation characteristics are very sensitive to user and environment changes such as blockages, user motion or rotation.
To adapt fast to the wireless channel changes, an understanding of the wireless channel dynamics is required. The channel dynamics depend on understanding the surrounding environment such as the transmitter and receiver locations, geometry of the buildings, moving scatterers, location and material of blockers, etc.
Interestingly, most of the XR streaming devices (e.g., 5G phones, AR/VR headsets) and third-party entities that support 5G (i.e., 3GPP sensors) also support non-3GPP sensors, such as RF sensors, Inertial Measurement Units (IMU) sensors, RGB cameras, position sensors, and others.
In light of the availability of 3GPP and non-3GPP sensors and the need of environment understanding, it is therefore natural to utilize the overall sensing information to acquire an understanding of the surrounding environment.
To this end, a “Sensing RF Map Service” can be envisioned that enables the collection of sensing information from 3GPP and non-3GPP sensors, process and provide that information to a sensing service.
• The input to this “Sensing RF Map” service could be 3GPP sensing data and non-3GPP sensing data from multiple sensors, e.g., RF sensing data, XR user position, camera images, depth maps, hand tracking, motion type, etc. Such input could be produced by a 5GS entity (e.g,, UE or RAN entities) or by a third-party (e.g., surveillance camera). It is essential to note that the collection of this sensing should be done with appropriate user consent and adherence to regional and national regulations.
• The processing of 3GPP and non-3GPP sensing data can be performed within the 5G system or outside the 5GS (for example on an application server). In this use case, we are focus on processing in the 5G system.
• The output of this service (i.e., sensing result) is some understanding of the environment and/or impact to communication performance of a service consumer, e.g., RF environment mapping, etc. When sensing result is shared outside of the 5GS, the appropriate consent and permissions for sharing this information is required.
• The consumer of this service could be a third-party application or other entities in the 5GS.
It is important to note that while this service is provided by 5GSor edge server, business model for the monetization of this service would need to consider factors such as the entities involved in sensing, the transfer of the non-3GPP sensing data and the value of sensing RF Map information produced by these entities as well as the value to the consumer of the service. These considerations are also required for scenarios involving 3GPP only sensing operations but additional considerations are indeed required for non-3GPP sensing data which is generated outside the 5G system.
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5.21.2 Pre-conditions
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Jose is playing a game inside a gaming arena using a VR headset that is connected to a RAN entity. The VR headset, RAN entity and third-party surveillance system are configured to provide “3GPP sensing data and non-3GPP sensing data” to the “Sensing RF Map Service”.
The VR headset is equipped with 3GPP sensors and non-3GPP sensors such as, IMU sensors and cameras, and it can provide sensing inputs e.g., 3GPP sensing data, headset pose and location, velocity, images of the environment and processed images (such as motion pattern and maps). Also, the VR headset can provide communication reference signal measurements or reports to the Sensing RF Map Service.
RAN entity has 3GPP NR RF capabilities and can provide 3GPP sensing data to the 5GS, which processes and provides sensing results to the sensing RF Map service.
The gaming arena also has cameras deployed by a trusted third-party surveillance camera company and can provide images of the environment and processed images (such as motion pattern and maps) to the 5GS.
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5.21.3 Service Flows
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1. Jose is playing a game using a VR headset in an arena with some obstacles and other gamers in the environment. Jose moves through the arena and approaches a communication blocker which could potentially impact the performance of the wireless communication between VR headset and the RAN entity.
2. Jose’s VR headset, RAN entity and the third-party surveillance system provide 3GPP sensing data, and non-3GPP sensing data to the Sensing RF Map Service. The Sensing RF Map Service combines the 3GPP and non-3GPP sensing data to produce a sensing result which is a comprehensive RF map of the environment surrounding the headset (e.g. information such as the location of RAN entities, reflectors, static blockers, etc. and an indication of wireless link blockage event, e.g., people walking by blocking the 5G link).
NOTE: An RF map is a spatial/geographical representation of environmental characteristics (e.g., wireless propagation and objects such as RF signal reflectors, blockers in the environment). This map enables improvements in areas such as radio resource management, beam management, mobility and user applications.
3. 5GS uses the RF map to predict that Jose’s communication link is about to be blocked if he comes close to the blocker and such prediction is sent to communication and/or the application layers of the game. For example, the application layer adjusts the content of rendered video frames accordingly (e.g., lowers the frame rate, adds a virtual obstacle in the rendered video to prevent Jose from coming close to the blocker.)
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5.21.4 Post-conditions
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Jose enjoys seamless XR gaming application without video frame drops, i.e., no video glitches. This is because Sensing RF map Information was leveraged to assist both the communication service as well as the application.
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22.837
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5.21.5 Existing features partly or fully covering the use case functionality
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None.
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22.837
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5.21.6 Potential New Requirements needed to support the use case
|
[PR 5.21.6-1] Subject to user consent and regulatory requirements, based on operator policy, the 5G system shall be able to support secure means for RAN entities and authorized UEs to provide 3GPP sensing data to a 5G network for processing.
[PR 5.21.6-2] Subject to user consent and regulatory requirements, based on operator policy, the 5G system shall be able to collect non-3GPP sensing data from trusted parties.
[PR 5.21.6-3] Subject to user consent and regulatory requirements, based on operator policy, the 5G system should be able to support the combination of the 3GPP sensing data and non-3GPP sensing data to derive combined sensing result.
[PR 5.21.6-4] Subject to user consent and regulatory requirements, based on operator policy, the 5G system shall be able to expose the combined sensing results to a trusted third-party service provider.
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5.22 Use case of UAVs/vehicles/pedestrians detection near Smart Grid equipment
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5.22.1 Description
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In the future, there will be more and more autonomous driving devices, such as drones and self-driving cars. These devices have a strong ability to affect the surrounding environment, which may have an impact on the operating equipment in Smart Grid.
For example, vehicles, such as UAVs and engineering vehicles, may affect the operation safety of multiple links such as power generation, power transmission, and power transformation.
At present, multiple scenarios of power transmission and transformation in the Smart Grid industry have potential combination with integrated sensing and communication technology. Among them, there are related accidents caused by hooking or damaging transmission lines by vehicles in the power transmission process. Thus, the transmission stations need to identify and warn vehicles. In the process of power transformation, there are security risks such as candid photography and attack by drones, getting electric shock when approaching, etc. In a word, there are requirements for perimeter intrusion detection and UAV detection in substations.
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22.837
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5.22.2 Pre-conditions
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There are existing 5G base stations deployed near the transmission stations and substations, which can provide constant remote sensing of the location of intruders in the coverage area including UAVs, engineering vehicles and pedestrians. Network operator A can use these 5G base stations to provide 5G sensing service for the Smart Grid operator X, including sensing the motion trail of the UAVs, vehicles and pedestrians in their working area.
The Smart Grid Operator X uses the 5G sensing service provided by 5G network Operator A to detect potential intrusion/approaching of UAVs, vehicles and pedestrians near the transmission stations and substations.
The Smart Grid operator sets the border of restricted area for the transmission stations/lines and substations in which no UAVs, vehicles or pedestrians can be access, and define a warning distance value. Once a UAV, traffic vehicle, or pedestrian is detected that its distance from the border is less than the warning distance value, the 5G system will report the event to the Smart Grid operator to send the alerting message.
The 5G base stations can sense the location of the UAV/traffic vehicle/pedestrian constantly and send these data to the 5G core network. Then the sensing node and computing node can analyse and predict the path of the UAV or pedestrian according to a large amount of data and give early warning of potential security risks.
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22.837
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5.22.3 Service Flows
|
1. The Smart Grid Operator X requests sensing service from network operator A to collect sensing data in the defined area (i.e., the park covering transmission stations and substations). The network operator A configures the base stations located in the defined area to perform sensing.
2. The 5G RAN constantly collects 3GPP sensing data of the location of UAVs/vehicles/pedestrians in the defined area and send the sensing data to the 5G core network with a defined frequency to obtain the sensing result (i.e., the distance between the UAV/traffic vehicle/pedestrian and the border or motion trail).
3. The 5G system will send notification to UAVs/vehicles/pedestrians with UE that they are near a restricted area. 5G system will also report the sensing results to the Smart Grid operator. The Smart Grid operator determines to send the alerting message to the intruding/approaching UAVs/vehicles/pedestrians based on the sensing results. In addition, the staffs working in the park respond to the emergency and prepare to intercept the intruding/approaching if the UAVs/vehicles/pedestrians are not away.
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5.22.4 Post-conditions
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The UAVs/vehicles/pedestrians are away from the defined area. Potential security risks are avoided. Thanks to the wide-area and constant sensing capability of the 5G base station, and the precise data processing and prediction by the 5G core network, the safety supervision of the Smart Grid is improved.
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22.837
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5.22.5 Existing features partly or fully covering the use case functionality
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In TS22.261, there are existing requirements on information exposure:
In clause 6.10:
The 5G system shall be able to:
- provide a third-party with secure access to APIs (e.g. triggered by an application that is visible to the 5G system), by authenticating and authorizing both the third-party and the UE using the third-party's service.
- provide a UE with secure access to APIs (e.g. triggered by an application that is not visible to the 5G system), by authenticating and authorizing the UE.
- allow the UE to provide/revoke consent for information (e.g., location, presence) to be shared with the third-party.
- preserve the confidentiality of the UE's external identity (e.g. MSISDN) against the third-party.
- provide a third-party with information to identify networks and APIs on those networks.
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5.22.6 Potential New Requirements needed to support the use case
|
[PR 5.22.6-1] Subject to operator policy, the 5G system shall enable the network to expose a suitable API to a authorized third party to provide the information regarding sensing results.
[PR 5.22.6-2] Based on operator policy, the 5G system may be able to utilize sensing assistance information exposed by a trusted third-party to derive the sensing result.
[PR 5.22.6-3] The 5G system shall be able to support the following KPIs:
Table 5.22.6-1 Performance requirements of sensing results for UAVs/vehicles/pedestrians’ detection near Smart Grid equipment
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 the use case in Smart Grid NOTE 2
Outdoor
95
≤0.7
N/A
UAV: ≤25
Pedestrian: ≤1.5
Vehicle: ≤15
N/A
N/A
N/A
≤5s
≥10Hz
[≤5]
[≤5]
NOTE 1: The terms in Table 5.22.6-1 are found in Section 3.1.
NOTE 2: The typical size (Length x Width x Height) of UAV is 1.6m x 1.5m x 0.7m, the typical size of pedestrian is 0.5m x 0.5m x 1.75m, and the typical size of engineering vehicle is 7.5m x 2.5m x 3.5 m. The size of the park of Smart Grid depends on the real environment.
NOTE 3: The safe distance between pedestrian/vehicle and transmission station/line is 0.7m/0.95m [46].
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5.23 Use case on AMR collision avoidance in smart factories
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5.23.1 Description
|
Autonomous mobile robots (AMR) are currently being introduced in many logistics operations, e.g. manufacturing, warehousing, cross-docks, terminals, and hospitals. Compared to an automated guided vehicle (AGV) system in which a central unit takes control of scheduling, routing, and dispatching decisions for all AGVs, AMRs are robots built with intelligence to autonomously move and perform tasks. AGVs is expected to further be evolved into intelligent AMR to meet the demand of intelligent factory.
Compared to AGVs which move on transport paths guided by rails, magnetic markers etc. AMRs can travel automatically without derivatives or guides. AMRs don’t rely on predetermined paths, they can easily adjust routes as user demands change, so AMRs have wider mobile range and more flexibility. AMRs can not only stop on time to avoid humans and other obstacles, but also adjust its route for its destination. However, during the AMR working process, the sensing range of a single AMR is limited and the AMR surrounding environment status may be not detected in time. For example, People or other machines that suddenly appear from behind the large factory equipment can affect the driving safety of the AMR. So, it is very challenge for AMR to get accurate and continuous sensing information along its route.
5G base stations can be deployed in a factory not only to provide communication capabilities for equipments in the factory but also sense the surrounding environment e.g. obstacles or people in the trajectory of AMRs. Base stations transmit the sensing signals and receive the reflected signals to get sensing information, then reports the real-time 3GPP sensing data to the core network. The core network can process and analyze the 3GPP sensing data for outputting the sensing result. Such sensing result can be exposed to a trusted third-party e.g. automation platform of the factory to enables AMRs to know more information about the surrounding environment to improve efficiency and driving safety.
In addition, when there are obstacles (e.g., the large factory equipment) to block the transmission of radio signals or AMR trajectory is across indoor and outdoor, multiple base stations with sensing capability can work together to improve the sensing accuracy and sensing service continuity.
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5.23.2 Pre-Conditions
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5G Network operator ‘MM’ provides 5G sensing service in the factory of Company A. Its 5G system has been deployed covering the factory to provide continuous sensing service indoor and outdoor.
Company A has placed two AMRs (AMR 1 and AMR2) in its factory for moving goods from workshop A to workshop B. At the same time, there are people moving around in both workshops, and other goods or tools may be temporarily placed on the route of the AMRs. The people walking in the workshop and the goods may block the AMR route, jeopardizing production safety. In addition, the two AMRs may collide considering their flexible routes.
The AMRs of Company A uses ‘5G Sensing Service’ provided by 5G network Operator ‘MM’ during they are working. In order to ensure data security, the related sensing data is not permitted to be delivered outside Company A.
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5.23.3 Service Flows
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Figure 5.23.3-1 shows the route change of AMR1 in the process of carrying goods.
Figure 5.23.3-1: Sensing People or obstacles detection in smart factory
1. The AMR#1 is delivering the car parts from workshop A to Sam who is near the assembly line in workshop B.
2. The 3GPP sensing data collected by Base station #1/RAN, the 5G network processes the 3GPP sensing data to obtain sensing results and detects the proximity of obstacles along the trajectory of AMR#1. 5G system provides the sensing result to the AMR#1, and AMR#1 then re-route and bypass the obstacles based on the sensing result.
3. AMR#1 is leaving the Workshop A and across from indoor to outdoor.
4. The 3GPP sensing data is collected by Base station #2/RAN, the 5G network processes the 3GPP sensing data to obtain sensing results and detects the proximity of Daming who is walking across the trajectory of AMR#1. 5G system provides the sensing result to the AMR#1, then AMR#1 stops to wait for Daming to leave.
5. AMR#1 enters the Workshop B.
6. The 3GPP sensing data is collected by Base station #3/RAN, the 5G network processes the 3GPP sensing data to obtain sensing results and detects the AMR#2 near AMR#1. 5G system provides the sensing result to AMR#1, then AMR#1 re-routes and bypasses the obstacles based on the sensing result.
7. When AMR#1 enters the coverage of Base Station #4, using the 3GPP sensing data from Base station #4/RAN, the 5G network processes the data to obtain sensing results and detects the proximity of John who is behind a large machine. 5G system provides the sensing result to AMR#1, then AMR#1 stops and waits for John to leave.
AMR#1 successfully delivers the car parts to Sam in workshop B.
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5.23.4 Post-Conditions
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Based on the communication and sensing services provided by the 5G network, the AMRs in the factory operate normally and reduce safety incidents.
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22.837
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5.23.5 Existing features partly or fully covering the use case functionality
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None.
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22.837
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5.23.6 Potential New Requirements needed to support the use case
|
[PR 5.23.6-1] The 5G system shall be able to provide the continuity of sensing service for a specific target object, across indoor and outdoor.
[PR 5.23.6-2] The 5G system shall be able to provide a secure mechanism to ensure sensing result data privacy within the sensing service area.
[PR 5.23.6-3] The 5G system shall be able to support the following sensing related KPIs:
Table 5.23.6-1 Performance requirements of sensing results for AMR collision avoidance in smart factories
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]
AMR collision avoidance in smart factories
indoor/outdoor
99
≤1
N/A
1
N/A
1
1.5
˂500
0.05
N/A
5
NOTE 1: The terms in Table 5.23.6-1 are found in Section 3.1.
NOTE 2: The KPI values are sourced from [47].
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5.24 Use case on roaming for sensing service of sports monitoring
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5.24.1 Description
|
Sports monitoring application describes the case of a human being monitored when doing exercise via utilizing wireless signals instead of cameras, or wearable devices. With enhanced privacy preservation, wireless signals that propagated in the 5G system (e.g. between 5G UE and 5G UE, and between the radio access network and device) can be further reused and processed to retrieve the target sensing object’s characteristics [48]. In a sports monitoring situation, the target object is human and the target object’s characteristic is human body gesture. By comparing the detected body gesture with the correct body gesture when people are doing exercises like sit-ups, and push-ups, this sport monitoring application will give feedback, for example, it can count the number of the exercise e.g. sit-ups, and calculate calories.
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5.24.2 Pre-conditions
|
The sports monitoring application provider has a service agreement with mobile operator A in country X and mobile operator B in country Y.
Mobile operator A in country X and Mobile operator B in country Y has roaming agreements.
Bob installs a sports monitoring application on his mobile phone and subscribes to the sensing service with mobile operator A.
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5.24.3 Service Flows
|
1. Bob is a sports fan and does exercise every day. He travels to country Y and gets accommodation in hotel M, where mobile operator B’s sensing service is available. Bob triggers the application and selects his favorite sport, sit-up.
2. The sensing request is received by Mobile operator B and Mobile operator B then authorize whether the sensing request can be satisfied or allowed, e.g. by verifying the sensing system availability (infrastructure, sensing modalities), the location of the sensing service, local privacy restrictions, the roaming agreement with Bob’s home mobile operator A in country X, the identity of Bob and etc.
3. If the authorization succeeds, mobile operator B authorizes and provides such 5G sensing service to Bob with required performance targets and requirements and Bob pays for the sensing service to mobile operator B.
• Mobile operator executes sensing measurement process (e.g. micro doppler shift) with the sensing entities (e.g. RAN entities and the roaming UE, or CPE and the roaming UE) to obtain 3GPP sensing data;
• Mobile operator processes the 3GPP sensing data to derive sensing result and expose it to the application server.
4. If the authorization fails, mobile operator B does not provide such 5G sensing service to Bob and potentially, Bob or the sports monitoring application server will receive the reason of why mobile operator B cannot provide such sensing service.
5. Later, Bob left the hotel to run around the area near the hotel. When Bob runs near a restricted area where sensing service is not allowed, the Mobile operator B revokes the authorization and terminates the sensing service. Potentially, Bob or the sports monitoring application server will receive the reason of why mobile operator B cannot provide such sensing service.
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5.24.4 Post-conditions
|
Bob can enjoy the sports monitoring application even when he travels in another country.
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5.24.5 Existing features partly or fully covering the use case functionality
|
Roaming-related authentication and charging may refer to existing requirements as defined in Clause 9 in TS22.261:
The following set of requirements complement the requirements listed in 3GPP TS 22.115. The requirements apply for both home and roaming cases.
The 5G core network shall support collection of charging information for alternative authentication mechanisms
The 5G system shall be able to generate charging information regarding the used radio resources e.g. used frequency bands.
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5.24.6 Potential New Requirements needed to support the use case
|
[PR 5.24.6-1] Based on operator policy, the 5G System shall be able to provide the 5G wireless sensing services in case of roaming.
[PR 5.24.6-2] 5G network shall provide means for mobile operator to provide / revoke authorization for the operation(s) of a 5G wireless sensing service based on location, time, specific KPI level and the origin of the request.
[PR.5.24.6-3] The 5G system shall be able to provide 5G wireless sensing service with the following KPIs:
Table 5.24.6-1 Performance requirements of sensing results for sports 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]
Sports monitoring
Indoor (living room)
95
0.05
NOTE 2
0.07
NOTE 3
N/A
N/A
N/A
N/A
N/A
N/A
60s
1min
N/A
N/A
NOTE 1: The terms in Table 5.24.6-1 are found in Section 3.1.
NOTE 2: Sit-up rate = 30 times/min as reference, 0.05Hz corresponds to 3 times/min.
NOTE 3: Push-up rate = 40 times/min as reference, 0.07Hz corresponds to 4 times/min.
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5.25 Use Case on immersive experience based on sensing
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5.25.1 Description
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Sensing based on the 5G signals is a technology using the difference between wireless signals and its reflective signals including the Doppler frequency shift, time of flight (ToF), amplitude variation and so on, to sense the surroundings. The information collected during sensing cannot be directly understood by human beings, providing good privacy protection. Along with 5G stepping into the home, more interesting functions can be introduced based on the sensing using 5G signals.
It will be fantastic to have an immersive audio and light experience when watching movies and listening to music in the home. The speakers can provide this kind of audio experience if they can know the position of each other and also the user. Usually, to have immersive audio experience, several speakers are needed. Ranging technology can help the speakers to determine position relative to each other and this gives a chance for speakers to provide a fantastic experience together to a listener by adjusting the audio field at a place when the listener stays at that special place.
Different from ranging service where only the UE’s position can be identified, sensing can identify the relative position of the reflector even the reflector is not a UE. If the speakers can obtain the sensing results, this will give a chance to the speakers to follow the listener and provide an immersive audio experience, even when the listener is moving around. The speakers can follow the position of the human and adjust the audio field anytime anywhere. Similar to the audio case, if the smart light can obtain the sensing results, the light can also track the user anytime anywhere to provide an immersive experience.
For the immersive experience scenario, the audio field and light adjustment should be based on the user’s position. For example, the smart screen, lights and speakers can provide immersive sound and light experience for the user who sits at the sofa area (around 2~3m2 area) and at the same time lower the sound volume and turn down the light at other places of the home avoiding the interference on others. The sensing node (e.g., smart screen, i.e., a UE) can perform sensing operations to track the user’s movement using RF signals [29] and provide the information to the speakers and lights for adjustment. Then both the lights and speakers can provide a cosy zone around the user.
In home, there is usually a mixed deployment of smart screen, lights, and speakers. We take smart screen as the sensing node as an example. Assume that the smart screen, the smart lights, and the speakers are placed in the drawing-room, and the smart screen can sense the object in the room as shown in Fig. 5.25.1-1. The smart screen (i.e., UE) can receive the reflected sensing signals transmitted by UEs in the room, or by the gNB to perform sensing operation on the user in the room.
Figure 5.25.1-1: Example deployment of the smart screen, speakers and lights
The smart screen can track the user’s position via sensing operation. Each user is assumed to occupy an area 0.5m * 0.5m and move with a speed lower than 2m/s in horizontal dimension. Then the audio field and light can be adjusted based on the user position (e.g. an area 1.5m * 1.5m) to avoid the experience deterioration even when the user is walking around.
To identify multiple users in the room, in the horizontal dimension, the resolution requires to distinguish objects as large as 0.5m. With higher accuracy on distance, each user in the room can be identify with a more accurate location such as 0.2m, the light and audio can target the user better [30]. If the results are accurate but out of date due to the movement of the user, this will also degrade the experience as the cosy zone is lagging the movement of the user. Consider the audio field and lights are adjusted in an area with 1.5m * 1.5m, to avoid the experience deterioration, the service latency should smaller than 0.5m/2m/s, i.e., 250ms. To track the user’s movement, the results need to be refreshed in 250ms, i.e., 4 times per second (4 Hz).
Figure 5.25.1-2: Example of accuracy required for the use case
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5.25.2 Pre-conditions
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This use case is about Tom’s home theatre plan. Tom bought a set of speakers, and placed them in his home to create an immersive audio experience. Tom also bought a set of smart lights to create an immersive light experience. Together with a smart screen in home, these smart devices compose the home theatre. According to the instruction of the speakers, and also based on the availability of audio and power wiring Tom distributed the speakers in his living room. The smart lights are installed on the ceiling of the room. After detecting the position of each distributed speakers, the home theatre system can adjust the audio field in Tom’s home. After detecting the position of smart lights, the home theatre system can control the light variation in home. This detection mechanism of the speakers and smart lights is outside the scope of this document.
There exists a sensing device in the home, which can sense Tom’s position without requiring Tom to take a UE with him. For example, the sensing node is the smart screen belonging to the home theatre system at Tom’s home. Based on the sensing results from the sensing node, the home theatre system can adjust the audio field and light based on the sensing results.
The home theatre system can be deployed by user where the smart screen, lights and speakers communicate with each other via direct device communication using unlicensed band. As an alternative, the home theatre system can be deployed with the help of operator using licensed band when the units of the home theatre system are in coverage. In this case, operator can control the performing of sensing operation based on the location of the deployment of the home theatre.
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5.25.3 Service Flows
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Tom activates his home theatre and the speaker begin to play music based on the audio on demand. The sensing device in the room (i.e., Smart screen) performs sensing operation and the sensing results begin helping adjust the audio field.
Figure 5.25.3-1 Immersive experience with tracking light and sound
Tom immerses himself in music and begins to dance. The sensing device (e.g., smart screen) tracks Tom’s position via the processing of the receiving sensing signals, the Sensing result is calculated, and the Sensing result is sent to the control unit of the home theatre system.
Based on the sensing results, the home theatre system can adjust the audio field and lights according to Tom’s movement.
Thanks for the sensing service provided by the sensing node (e.g. smart screen), no matter where Tom stands, he always experiences the best surround sound and tracking light.
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5.25.4 Post-conditions
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Thanks to the sensing service provided in the intelligent home, Tom can have an immersive experience via his home theatre.
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22.837
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5.25.5 Existing features partly or fully covering the use case functionality
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None.
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22.837
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5.25.6 Potential New Requirements needed to support the use case
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[PR 5.25.6-1] The 5G system shall be able to configure and authorize sensing for a Sensing device or a group of Sensing devices when using licensed spectrum based on the Sensing device’s location.
[PR 5.25.6-2] The 5G system shall be able to enable a Sensing device to perform sensing with licensed band under operator’s control based on the Sensing device’s location.
[PR 5.25.6-3] The 5G system shall be able to enable UEs without 5G coverage to use unlicensed spectrum to perform sensing.
[PR 5.25.6-4] Subject to user consent and national or regional regulation, based on operator policy, the 5G system shall be able to allow a Sensing device to provide sensing results to a trusted third party.
[PR 5.25.6-5] The 5G system shall be able to provide sensing with following KPIs:
Table 5.25.6-1 Performance requirements of sensing results for immersive experience
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]
Immersiveexperience
Indoor
95
0.5
0.5
0.1
N/A
0.5
N/A
250
(granularity of field is 1.5m x 1.5m)
0.25
5
5
NOTE: The terms in Table 5.25.6-1 are found in Section 3.1.
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5.26 Use case on accurate sensing for automotive manoeuvring and navigation service
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5.26.1 Description
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It is forecasted that there will be approximately 8 million autonomous or semi-autonomous vehicles on the road by 2025 [49]. NR wireless sensing will assist with automotive manoeuvring and navigation, especially in scenarios where single car-mounted sensors collecting information is not enough for making safe and reliable decisions, e.g. to avoid a collision, pedestrians, etc.
This scenario reuses the use case as defined in section 5.8, where NR wireless sensing is utilized to assist automotive manoeuvring, i.e. sensing results play an important role in making the manoeuvring decisions. However, the sensing environment when RAN entities and UEs execute the sensing measurement process may be subject to high interference (e.g. interference caused by adjacent RAN entities, radars, fake base stations) and cause the sensing information as collected to be wrong.
The sensing information provided to the Automated Driving System (ADS) server needs to be fully trustworthy: reliability, integrity, high confidence level and protection against tampering are key aspects. Users (and third parties) should not be able to fraud the ADS Server by tampering with the sensing information in order to influence the manoeuvring decision.
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5.26.2 Pre-conditions
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Refer to 5.8, where Bob’s vehicle is detected to be blocked by other vehicle and cannot do the decision for autonomous driving with sensors collected data (e.g. from lidar, radar, camera, etc). Bob recognizes the needs of 5G system assistance and requests 5G System for coordination of the sensing service.
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e8cee4e428329a7668584ba76bf8de13
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22.837
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5.26.3 Service Flows
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1. Bob drives in downtown, and is approaching a crossroad with regulatory signs, where the sensors on Bob’s vehicle are blocked by other vehicles. Bob’s vehicle cannot see the surroundings and Bob sends the sensing request to 5G system.
2. The 5G system gives instructions about how to proceed the sensing to Bob’s vehicle and Bob’s vehicle selects Joe’s vehicle to assist the sensing service. Joe’s vehicle transfers the sensing contextual information to Bob’s ADS server.
3. Bob’s ADS server utilizes the sensing contextual information to do the decision, Bob decelerates before the traffic light.
4. Bob continues the journey and drives in a tunnel (10km length), the sensors on Bob’s vehicle are detected to be blocked by a big truck. Bob sends the sensing request to 5G system.
5. The 5G system selects RAN entities (e.g. road side units) to assist the sensing service. The 5G system transfer the sensing information collected by RAN entities to Bob’s ADS server.
6. Bob’s ADS server utilizes the sensing information to do the decision, and Bob accelerates to overtake the big truck.
7. Bob continues the journey and drives in a desert area and some sensors on Bob’s vehicle are detected to be broken (e.g. because of heat). Bob’s vehicle sends the sensing request to 5G system.
8. The 5G system selects RAN entities (sparsely deployed in desert area) to assist the sensing service. With the feedback from RAN entities, the 5G system transfer the sensing information together with the indication of confidence level as 60% to the ADS server.
9. Bob’s ADS server utilizes the indication and sensing information, and decides to return to Level 0 driving for safety.
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22.837
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5.26.4 Post-conditions
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Bob’s vehicle is able to drive with high reliability by utilizing accurate 5G sensing service.
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22.837
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5.26.5 Existing features partly or fully covering the use case functionality
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None.
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22.837
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5.26.6 Potential New Requirements needed to support the use case
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[PR 5.26.6-1] The 5G system shall be able to determine the confidence level of the sensing results.
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e8cee4e428329a7668584ba76bf8de13
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22.837
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5.27 Use case public safety search and rescue or apprehend
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