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5.21.1 Description
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Museums are a popular choice for people to spend their leisure time. With so many exhibits in museums, it is difficult for all visitors to know about the artistic value of each exhibit. A qualified museum guide can assist visitors in better understanding the information behind the exhibits.
Hiring a docent and renting an explanation device are two common methods for museum guides today. A docent usually serves multiple visitors at once, and it is difficult to provide personalized guidance based on each visitor's preferences. Moreover, for foreign visitors, docents who can speak their language are not always available. If visitors choose to rent an explanation device, they will need to manually enter the exhibit number each time they use the device, and the device usually only provides audio explanations, which is not very convenient for the visitors. Recently, some museums also offers other solutions, such as attaching the QR codes on the exhibit cases to provide the introduction information. By scanning the QR codes, visitors can also get information related to the exhibits. But for visitors, they still need to manually open the camera on their mobile phone and scan the QR code for each exhibit, which may be repeated lots of times during the visit.
Ambient IoT devices are a promising solution for museum guide. An exhibition hall in a museum can be thousands of square meters in size and have thousands of exhibits. Ambient IoT devices can work with limited energy storage capability or without any battery for an extremely long time, so the Ambient IoT devices are maintenance-free, lightweight, and small-size. In the museum, the Ambient IoT devices can be attached to the glass of the exhibit case or placed in the exhibit case with the exhibit. The introduction information of the exhibits corresponding to each Ambient IoT device is uploaded to the application server in advance.
Abby enjoys going to museums, and her mobile phone supports Ambient IoT service and is able to send signals to Ambient IoT devices. She also downloads the museum guide application and subscribes to the guide services.
The exhibit hall in the museum that Abby intends to visit covers 6,000 square meters and has 3,000 exhibits. Abby learned that this museum has deployed a museum guide system using ambient IoT devices to provide the corresponding introduction information of the exhibit that will help the visitors to have a deep understanding of each exhibit.
Figure 5.21.1-1: Ambient IoT for Museum Guide
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5.21.2 Pre-conditions
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In museums, the Ambient IoT devices are attached to the glass of the exhibit case or placed in the exhibit case with the exhibit. The introduction information of the exhibits corresponding to each Ambient IoT device is uploaded to the application server in advance.
Abby’s mobile phone supports Ambient IoT service and is able to send signals to Ambient IoT devices. She also downloads the museum guide application and subscribes to the guide services.
The museum has public or private 5G network coverage to provide Ambient IoT services with support for a large number of Ambient-IoT devices.
The Ambient IoT services could have interactions with the 5G network with necessary information.
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5.21.3 Service Flows
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1. Abby arrives at the museum and walks into the exhibition hall. She opens the guide application on her mobile phone to get more information. She also authorizes her mobile phone for the Ambient IoT communication service and Ambient IoT positioning service, to obtain the relative positioning results of Ambient IoT devices.
2. Abby taps the button on the application to get more information about nearby exhibits, and her mobile phone sends the signal (continuously or intermittently) to wake up and trigger the Ambient IoT devices, and the Ambient IoT devices are attached to the glass of the exhibit case or placed in the exhibit case with the exhibit in advance.
3. The Ambient IoT devices close to Abby receive the signal and are activated. The Ambient IoT devices respond to Abby’s mobile phone with their Ambient IoT device IDs.
4. Abby’s mobile phone receives the response signals from the Ambient IoT devices with their IDs. Abby's mobile phone can also derive the relative positioning results of each Ambient IoT device using the response signals.
Figure 5.21.3-1: Ambient IoT for Museum Guide
5. Abby's mobile phone sends the acquired relative positioning resultss and Ambient IoT IDs to the application server with the help of 5G network.
6. The application server transmits the introduction information corresponding to the Ambient IoT IDs to Abby's phone. With the relative positioning results derived in step 4, Abby's phone can give different priorities to the introduction information based on the relative positioning results. The information about the exhibit closest to her is displayed at the top of the screen.
7. As Abby moves, other Ambient IoT devices will be activated by the signal and respond with their Ambient IoT device IDs to Abby's mobile phone. With these new response signals, Abby’s mobile phone can derive a new list of relative positioning results, and the exhibit information on her mobile phone can be automatically updated.
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5.21.4 Post-conditions
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Thanks to the Ambient IoT service provided by the 5G system, Abby can better enjoy her museum trip.
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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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5.21.6 Potential New Requirements needed to support the use case
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[PR.5.21.6-001] The 5G system shall support to authorize a UE to perform Ambient IoT communication services with specific Ambient IoT devices.
[PR.5.21.6-002] The 5G system shall be able to support to authorize a UE to perform relative positioning operations with specific Ambient IoT devices.
[PR.5.21.6-003] The 5G system shall support to authorize a UE to obtain device identity information of an Ambient IoT device.
[PR.5.21.6-004] The 5G system shall be able to expose the identities and relative positioning results of Ambient IoT devices to a trusted third party.
[PR. 5.21.6-005] The 5G system shall be able to support suitable security mechanisms for Ambient IoT devices, including encryption and data integrity.
[PR.5.21.6-006] The 5G system shall be able to provide Ambient IoT service with the following KPIs:
Table 5.21.6-1: Ambient IoT service KPI for museum guide
Scenario
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Museum guide (indoor)
2 s
99.9%
NA
< 1 kbit/s UL (NOTE 1)
96 bits
<10,000 /km²
30m
20,000m² (NOTE 2)
3 km/h
NA
NA
90%
3 m
NOTE 1: The payload includes Ambient IoT device information, e.g., Ambient IoT device ID.
NOTE 2: For a relatively large-sized museum, the typical size is about 20,000 m².
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5.22 Use case on smart grazing dairy farming enabled by Ambient IoT
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5.22.1 Description
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The global sensor market is predicted to grow from $193.9 billion in 2020 to $332.8 billion in 2025 at a CAGR of 11.4% [40]. Globally, for tracking and monitoring the IoT market size is forecast to grow from US$ 8,575 million in 2021 to US$ 18,525.0 million at a CAGR of 8.01% in 2031 [41].
It is certainly not new that connected sensors and IoT can play a role in animal husbandry. Precision livestock farming (PLF) as a trendier term adopts an innovative production system approach [42] playing a key role in Industry 4.0 [43]. More efficient production of quality food at lower cost will be an important tool to improve sustainability and respond to the imminent energy crisis and food shortage we are facing today. Physical vitals of livestock such as temperature are monitored for farmers to take early actions before potential diseases cause severe economic loss. The body temperature of livestock is a precise health indicator and changes in body temperature are often the first sign of an acute illness. For these purposes, the target data acquisition process of animal body temperatures is not latency-sensitive. Also, the needed network coverage is usually local (e.g. outdoor dairy cow paddocks), which is different from existing NB-IoT/(e)MTC targeting at providing long-range communication while achieving long battery life time.
As the adoption of PLF continues, feedback is often received from livestock farmers at industry conferences. In EU the EU-PLF conference was held as early as 2016. Feedback includes that dairy cow farmers in countries like the Netherlands (one of the global top 5 dairy exports) have been considering replacement of active monitoring IoT devices (with battery-powered transponders) with cheaper ear tags. This is partly because of economical drawbacks with increasing herd sizes. More importantly, the thick and heavy neck- or leg-mounted devices can cause discomfort to livestock, so that they are often scraped off against walls (of the pen) or damaged by animals involuntarily.
A more recent GSMA publication [10] explicates disadvantages as battery drain rendering the loss of asset visibility in only a few months. For these technologies the frequency of data transmission would impact the battery life time. For smart livestock farming, animal’s physical vitals need to be monitored several times a day, and it is preferred to have the IoT device serve livestock’s lifespan. This additionally implies the energy storage component in the IoT device should operate autonomously over a long period comparable to the lifespan of the IoT device excluding this component. In the same GSMA paper, another drawback of high CAPEX in dense deployment of the “tag readers” is highlighted, primarily due to the poor communication range supported by these alternative technologies.
These above aspects in smart livestock farming can be better addressed by Ambient IoT, particularly in smart dairy farming. A publication in Dairy Science Journal explains pasturing benefit for milk yield and dairy cow udder health [44], compared with primary intake of silage or concentrate associated with keeping animals indoors. Figure 5.22.1-1 illustrates dairy cows grazing on pasture.
Figure 5.22.1-1: Dairy cows grazing on pasture
In fact, because of the per-country variations in pasture quantity and quality different dairy farms can achieve different grazing percentage [45]. Table 5.22.1-1 shows data related to percentage of grazing dairy cows in major dairy producing European counties (year 2015). Countries like the Netherlands have explicit ambition to further increase the percentage of dairy cow grazing [45].
Table 5.22.1-1: Grazing and automated milking in Europe, from members of European Grassland Federation (2015) [45]
As grazing is important for dairy production, various grazing methods are possible (e.g. continuous grazing, strip grazing, rotational grazing, etc.) [46]. For strip or rotational grazing, a large pasture is subdivided into a number of smaller paddocks, so that grazing is managed in a planned sequence. The dimension of paddocks could be calculated by multiplying the number of cows by their total daily intake by days in the paddock and then divided by the ideal pre-grazing yield (PGY). There is a physical limitation of the paddock dimension. For instance, for 80 cows assuming regular values for parameters previously mentioned, the paddock size comes to 1.54 hectares (around 124m by 124m) [47].
This use case primarily proposes to support data acquisition process of dairy cows’ physical vitals on grazing dairy farms. In terms of the total size of pasture on grazing dairy farms, data from the Netherlands by University of Wageningen [48] reveals the pasture area for grazing in practice. Table 5.1 in [48] demonstrates among the various Dutch dairy farms the pasture surface area for grazing ranges from 4.9 hectares (49000 m2) to 34.3 hectares (343000 m2).
Another publication summarizing Wisconsin dairy grazing practice [49] shows the farm count distribution versus herd size and distribution of average acres per cow versus herd size. Based on these statistics, it shows majority of Wisconsin farms have herd size ranging from 50 to 150, and respectively the average acres per cow ranges from 1.2 to 0.7. Therefore, the total pasture surface of the majority of farms ranges from 60 acres (around 250000 m2) to 105 acres (around 430000 m2).
Australian data additionally shows for grazing dairy farming, the total pasture size can be influenced by bay length. Publication by Rural Water Commission of Victoria [50] explains practice on designing paddocks for irrigated dairy farms. Per requirement on bay length for economic reasons (i.e. short bay lengths leading to more spending on crossings, outlets, and drains, and overly long bays resulting in cow access problems), the ideal length of bay is between 300m and 500m [50]. The resulted pasture size is within an area of 600m by 600m.
To efficiently connect dairy cows, attached to each of them is a small, thin and light-weight tag (a type of Ambient IoT device) that has limited power source and includes a basic temperature sensor. These Ambient IoT devices power themselves by harvesting energy from the environment (e.g. solar, movement). The dairy cow health management system collects cows’ temperature several times a day, usually once every 15 minutes.
The base stations provide to the tags random access and data transmission over the radio interface. The tags are capable of storing tags’ identifiers and small sized data captured by sensors. The 5G system provides base station capability (e.g., “tag reading” functionality), tag operation and management. The monitored data is collected remotely according to the health-analyzing applications.
In this use case, grazing dairy farm BIO-DuurzameBeweiding is modernizing their dairy cow health management process to improve efficiency and productivity. They attach to dairy cows are wireless temperature sensors (tags), a form of Ambient IoT device, for the remote livestock health management application to retrieve dairy cow temperature to detect early signs of ailment that could take days or weeks to develop. The remote livestock health management application analyses the collected sensor values to identify potential illness of certain animals prior to symptoms appearing.
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5.22.2 Pre-conditions
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BIO-DuurzameBeweiding has a service level agreement with GroenTEL to deploy Ambient IoT service within 5G network coverage to enable the communication of Ambient IoT devices with the network. The communication service availability is achieved by providing seamless 5G network coverage. As part of the service level agreement, GroenTEL provides 5G coverage of the entire grazing pasture and efficient communication of Ambient IoT devices with the network. This includes:
• Interfacing with BIO-DuurzameBeweiding remote livestock health management system;
• Providing energy-efficient mechanisms for Ambient IoT devices’ network access
• Providing efficient communication between the network and Ambient IoT with the required communication performance
• Providing energy efficient security mechanisms for the communication between Ambient IoT devices and the network.
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5.22.3 Service Flows
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1. Upon the request from the livestock health management application, the 5G network starts inventory process via the selected gNB(s) This operation is associated with a certain area (e.g. grazing pasture of the dairy farm). Triggered by the 5G network, tags detect the signals from the gNB and respond to the command.
2. These Ambient IoT devices send the identification information to the 5G network and 5G core network complete the authentication procedure.
3. The Ambient IoT devices (wireless sensors) measure dairy cow physical vitals (i.e. body temperature). These temperature sensors are very simple, typical sampling rate is less than 10 Hz with sample size of 32 bits [39], thus the sensor data rate generated per tag is less than 320 bit/s. Assuming tag ID length is 96 bits, and it is transmitted together with sensor data, then the total throughput is < 500 bit/s.
4. The 5G network, based on the requests issued by the application function, performs operations (i.e. "inventory", "read", etc.) on tags correspondingly. "Inventory" operation is to read the tag identifier. "Read" operation is to read temperature sensor data.
5. The 5G core network then sends the results of the operations to the livestock health management application. The application function includes analytics functions that detect the anomaly and notifies the farmers of BIO-DuurzameBeweiding when necessary.
6. This data acquisition by the livestock health management application takes place once every 15 minutes.
7. In some additional situations, BIO-DuurzameBeweiding livestock management application requests the 5G network to perform sensor data read-out operation on specific tags attached to particular individual livestock (e.g. pregnant sows, lactating cows). The corresponding tags respond to the operation and report the temperature data.
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5.22.4 Post-conditions
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The 5G network enables efficient communication for Ambient IoT devices, the livestock management application is enabled by the 5G system to retrieve temperature sensor data from Ambient IoT devices. Depending on the needs, the livestock management application is enabled by 5G system to obtain the sensor data from an entire herd, a subset of herd, or an individual dairy cow.
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5.22.5 Existing features partly or fully covering the use case functionality
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SA1 has performed various studies on IoT in previous releases, where related normative stage 1 requirements are introduced in TS 22.011 [9], TS 22.278 [7], TS 22.368 [6], and TS 22.261 [8].
TS 22.011 introduces access control for MTC, examples of periodic network selection attempts are:
For UEs only supporting any of the following, or a combination of, NB-IoT, GERAN EC-GSM-IoT [18], and Category M1[13] of E-UTRAN enhanced-MTC, the UE shall interpret the interval value to be between 2 and 240 hours, with a step size of 2 hours between 2 and 80 hours and a step size of 4 hours between 80 and 240 hours.
In the absence of a permitted value in the SIM/USIM, or the SIM/USIM is phase 1 and therefore does not contain the datafield, then a default value of 60 minutes, shall be used by the UE except for those UEs only supporting any of the following, or a combination of: NB-IoT, GERAN EC-GSM-IoT [18], and Category M1 [17] of E-UTRAN enhanced-MTC. For those UEs a default value of 72 hours shall be used.
NOTE: Use of values less than 60 minutes may result in excessive UE battery drain.
TS 22.368 addresses features of MTC communication and service requirements related to MTC device triggering, addressing, identifiers, low mobility, small data transmission, infrequent MT communication, security, remote MTC device management, group-based MTC features including policing and addressing, etc. Example requirements are:
The system shall provide mechanisms to lower power consumption of MTC Devices.
The system shall provide mechanisms for the network operator to efficiently manage numbers and identifiers related to MTC Subscribers.
TS 22.261 captures some important service requirements for IoT, e.g.
The 5G system shall support a secure mechanism for a home operator to remotely provision the 3GPP credentials of a uniquely identifiable and verifiably secure IoT device.
The 5G system shall support a secure mechanism for the network operator of an NPN to remotely provision the non-3GPP identities and credentials of a uniquely identifiable and verifiably secure IoT device.
An IoT device which is able to access a 5G PLMN in direct network connection mode using a 3GPP RAT shall have a 3GPP subscription.
The 5G system shall allow the operator to identify a UE as an IoT device based on UE characteristics (e.g. identified by an equipment identifier or a range of equipment identifiers) or subscription or the combination of both.
An IoT device which is able to connect to a UE in direct device connection mode shall have a 3GPP subscription, if the IoT device needs to be identifiable by the core network (e.g. for IoT device management purposes or to use indirect network connection mode).
The 5G system shall support operator-controlled alternative authentication methods (i.e. alternative to AKA) with different types of credentials for network access for IoT devices in isolated deployment scenarios (e.g. for industrial automation).
In these specifications, albeit the service requirements addressing traits for IoT in terms of low device power consumption, small and infrequent data transmissions, long service lifetime, and resource efficiently, the IoT devices considered in 3GPP have been assumed to be powered by at least batteries up till now. To enable extremely small, light-weight, battery-less Ambient IoT devices that engage in basic IoT data transaction and appropriate level of operator management and charging suitable for the target scenarios, new challenges to the 5G system are foreseen and need to be addressed.
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5.22.6 Potential New Requirements needed to support the use case
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[PR 5.22.6-1] The 5G system shall support energy efficient communication mechanisms (i.e. minimizing the device communication power consumption) for Ambient IoT devices, while meeting the communication performance requirements.
[PR 5.22.6-2] The 5G system shall provide a mechanism for a 3rd party application to write user data to and to read user data from an Ambient IoT device.
[PR 5.22.6-3] The 5G system shall be able to collect charging information for a large group of closely located Ambient IoT devices in an efficient way.
NOTE: for example, the efficiency could be reduced total number of charging data related to a group of Ambient IoT devices, the reduction is compared with already specified 3GPP technologies.
[PR 5.22.6-4] The 5G system shall provide the network connection with the following KPIs for the use of Ambient IoT devices for smart dairy farms, see table 5.22.6-1.
Table 5.22.6-1: Potential key performance requirements for the use of Ambient IoT devices for smart grazing dairy farming
Scenario
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Smart dairy farm
>1 s
(note 1)
99%
NA
<500 bit/s
Typically,
[< 100 bytes]
(note 2)
<5200 devices / km2
(note 4)
[300 m - 500 m]
outdoor
(note 6)
430000 m2
(note 5)
Up to 3 km/h outdoor
15 min
(note 3)
NA
NA
NA
NOTE 1: Latency is not critical.
NOTE 2: Electronic Product Code standard [5], this size is the payload size.
NOTE 3: The livestock health management application monitors dairy cow body temperature many times daily, typically two consecutive transfers of the application data have an interval of 15 minutes.
NOTE 4: Calculated from 80 dairy cows assuming regular values for parameters (e.g. daily intake, pre-grazing
yield) previously mentioned, the paddock size comes to 1.54 hectares [47] (about 124m by 124m).
NOTE 5: For a relatively large-sized industrialized smart dairy farm, the surface area of pasture for grazing is typically 430000 m2.
NOTE 6: Based on the statistics from the Netherlands [55], Wisconsin [49] and Australia [50], the total pasture is smaller than an area of 650 m by 650 m. Assuming the coverage by one base station, the communication range between the Ambient IoT device and the base station is smaller than 500m.
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5.23 Use case on smart pig farm enabled by Ambient IoT
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5.23.1 Description
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The global sensor market is predicted to grow from $193.9 billion in 2020 to $332.8 billion in 2025 at a CAGR of 11.4% [40]. Globally, for tracking and monitoring the IoT market size is forecast to grow from US$ 8,575 million in 2021 to US$ 18,525.0 million at a CAGR of 8.01% in 2031 [41].
It is certainly not new that connected sensors and IoT can play a role in animal husbandry. Precision livestock farming (PLF) as a trendier term adopts an innovative production system approach [42] playing a key role in Industry 4.0 [43]. More efficient production of quality food at lower cost will be an important tool to improve sustainability and respond to the imminent energy crisis and food shortage we are facing today. Physical vitals of livestock such as temperature are monitored for farmers to take early actions before potential diseases cause severe economic loss. The body temperature of livestock is a precise health indicator and changes in body temperature are often the first sign of an acute illness. For these purposes, the target data acquisition process of animal body temperatures is not latency-sensitive, rarely an acquisition interval down to minute level is needed. Also, the needed network coverage is usually local. As this use case addresses industrialized smart pig farming, the difference from existing NB-IoT/(e)MTC (i.e. they target at providing long-range communication while achieving long battery life time) is coverage intended for pig barns is indoor.
As the adoption of PLF continues, feedback is often received from livestock farmers at industry conferences. In EU the EU-PLF conference was held as early as 2016. Feedback includes that livestock farmers have been considering replacement of monitoring IoT devices (with battery-powered transponders) with cheaper ear tags. This is partly because of economical drawbacks with increasing pig herd sizes e.g. observed in EU [51]. More importantly, the thick and heavy neck- or leg-mounted devices can cause discomfort, so that they are often rubbed off against enclosures or damaged by animals.
These above aspects in smart livestock farming can be better addressed by Ambient IoT. Figure 5.23.1-1 illustrates a typical pig farm consisting of a number of pig barns. For intensive piggeries the typical surface area of a pig barn is 4000 ~ 6000 m2 [52].
Figure 5.23.1-1: An example pig farm (upper) consisting of pig barns (lower)
Attached to each pig is a small, thin and light tag (a type of Ambient IoT device) that includes a basic temperature sensor. These devices power themselves by harvesting ambient energy (e.g. solar).
The base stations provide to the tags random access and data transmission over the radio interface. The tags are capable of storing tags’ identifiers and small sized-data captured by sensors. The 5G system provides base station capability (e.g., “tag reading” functionality), tag operation and management. The monitored data is collected remotely according to the health-analyzing applications.
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5.23.2 Pre-conditions
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Pig farm BIO-Duurzaamheid is modernizing their hog health management process to improve efficiency and productivity. They attach to each pig a very light-weight wireless temperature sensor (tag), a form of Ambient IoT device, for the remote livestock health management application to retrieve pigs’ temperatures to detect early signs of ailment or infections that could take days or weeks to develop symptoms. The temperature rad-out takes places several times a day, interval time is in the order of tens of minutes. The remote livestock health management application analyses the collected sensor values to identify potential illness of certain animals before symptoms appear.
BIO-Duurzaamheid has a service level agreement with GroenTEL to deploy 5G network to enable the communication of Ambient IoT devices with the network. Inside each industrialized warehouse-like pig barn, a gNB is installed to provide the radio coverage. As part of the service level agreement, GroenTEL provides efficient 5G coverage and energy-efficient communication within each pig barn managed by BIO-Duurzaamheid. This includes:
• Interfacing with BIO-Duurzaamheid’s remote livestock health management system;
• Providing energy-efficient mechanisms for Ambient IoT devices’ network access
• Providing efficient communication between the network and Ambient IoT with the required communication performance
• Ensuring the long lifespan of Ambient IoT devices without human intervention of any energy storage component possibly used in Ambient IoT devices
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5.23.3 Service Flows
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1. The tags (type of Ambient IoT devices with wireless sensors) measure pigs’ body temperatures. The type of temperature sensors are very simple, typical sampling rate is less than 10 Hz with sample size of 32 bits [39], thus the data generated per tag is less than 320 bit/s. Assuming tag ID length is 96 bits, and it is transmitted together with sensor data, then the total throughput is < 500 bit/s. BIP-Duurzaamheid obtain pigs’ body surface temperature daily with varying monitoring intervals depending on the needs, but the monitoring frequency is not higher than once per 15 minutes, or on half-hourly basis.
2. Upon the request from the livestock health management application, the 5G network starts inventory process via the selected gNB(s). By detecting the signals from the gNB, the tags respond to the command.
3. The 5G core network, based on the requests issued by the application function, performs operations (i.e. "inventory", "read", etc.) on tags correspondingly. "Inventory" operation is to read the tag identifier. "Read" operation is to read temperature sensor data.
4. The 5G core network then sends the results of the operations to the livestock health management application. The application function includes analytics functions that detect the anomaly and notifies the farmers of BIO-Duurzaamheid when necessary.
5. In some additional situations, BIO-Duurzaamheid’s livestock management application requests the 5G core network to perform sensor data read-out operation on specific tags attached to particular individual livestock (e.g. pregnant sows, recovering boars). The corresponding tags respond to the operation and report the temperature data.
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22.840
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5.23.4 Post-conditions
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The 5G network enables efficient communication for Ambient IoT devices, the livestock management application is enabled by the 5G system to retrieve temperature sensor data collected by sensors in the Ambient IoT devices. Depending on the needs, the livestock management application is enabled by 5G system to retrieve the sensor data for either certain individual pigs or an entire drove.
Owing to the thin and light-weight Ambient_IoT devices, livestock are more receptive of wearing them without feeling discomfort. This reduces asset damage and increases livestock welfare. As a result of data analysis done by the livestock management application, early signs of ailment of livestock are identified. This increases BIO-Duurzaamheid’s pig farm production. Thanks to the efficient Ambient_enabled IoT communication enabled by the 5G system, BIO-Duurzaamheid continue to use Ambient_enabled IoT for daily monitoring once per 15 minutes (or per half hour) without worrying about energy drain leading to replacement or manual recharging of Ambient_IoT devices throughout the planned production lifespan of their livestock.
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93a47931cc679002202cfe56afd8b056
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22.840
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5.23.5 Existing features partly or fully covering the use case functionality
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SA1 has performed various studies on IoT in previous releases, where related normative stage 1 requirements are introduced in TS 22.011 [9], TS 22.278 [7], TS 22.368 [6], and TS 22.261 [8].
TS 22.011 introduces access control for MTC, examples of periodic network selection attempts are:
For UEs only supporting any of the following, or a combination of, NB-IoT, GERAN EC-GSM-IoT [18], and Category M1[13] of E-UTRAN enhanced-MTC, the UE shall interpret the interval value to be between 2 and 240 hours, with a step size of 2 hours between 2 and 80 hours and a step size of 4 hours between 80 and 240 hours.
In the absence of a permitted value in the SIM/USIM, or the SIM/USIM is phase 1 and therefore does not contain the datafield, then a default value of 60 minutes, shall be used by the UE except for those UEs only supporting any of the following, or a combination of: NB-IoT, GERAN EC-GSM-IoT [18], and Category M1 [17] of E-UTRAN enhanced-MTC. For those UEs a default value of 72 hours shall be used.
NOTE: Use of values less than 60 minutes may result in excessive UE battery drain.
TS 22.368 addresses features of MTC communication and service requirements related to MTC device triggering, addressing, identifiers, low mobility, small data transmission, infrequent MT communication, security, remote MTC device management, group-based MTC features including policing and addressing, etc. Example requirements are:
The system shall provide mechanisms to lower power consumption of MTC Devices.
The system shall provide mechanisms for the network operator to efficiently manage numbers and identifiers related to MTC Subscribers.
TS 22.261 captures some important service requirements for IoT, e.g.
The 5G system shall support a secure mechanism for a home operator to remotely provision the 3GPP credentials of a uniquely identifiable and verifiably secure IoT device.
The 5G system shall support a secure mechanism for the network operator of an NPN to remotely provision the non-3GPP identities and credentials of a uniquely identifiable and verifiably secure IoT device.
An IoT device which is able to access a 5G PLMN in direct network connection mode using a 3GPP RAT shall have a 3GPP subscription.
The 5G system shall allow the operator to identify a UE as an IoT device based on UE characteristics (e.g. identified by an equipment identifier or a range of equipment identifiers) or subscription or the combination of both.
An IoT device which is able to connect to a UE in direct device connection mode shall have a 3GPP subscription, if the IoT device needs to be identifiable by the core network (e.g. for IoT device management purposes or to use indirect network connection mode).
The 5G system shall support operator-controlled alternative authentication methods (i.e. alternative to AKA) with different types of credentials for network access for IoT devices in isolated deployment scenarios (e.g. for industrial automation).
In these specifications, albeit the service requirements addressing traits for IoT in terms of low device power consumption, small and infrequent data transmissions, long service lifetime, and resource efficiently, the IoT devices considered in 3GPP have been assumed to be powered by at least batteries up till now. To enable extremely small, light-weight, battery-less Ambient IoT devices that engage in basic IoT data transaction and appropriate level of operator management and charging suitable for the target scenarios, new challenges to the 5G system are foreseen and need to be addressed.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.23.6 Potential New Requirements needed to support the use case
|
[PR.5.23.6-1] The 5G system shall support energy efficient communication mechanisms (i.e. minimizing the device communication power consumption) for Ambient IoT devices, while meeting the communication performance requirements.
[PR 5.23.6-2] The 5G system shall provide a mechanism for a 3rd party application to write user data to and to read user data from an Ambient IoT device.
[PR 5.23.6-3] The 5G system shall be able to collect charging information for a large group of closely located Ambient IoT devices in an efficient way.
NOTE: for example, the efficiency could be reduced total number of charging data related to a group of Ambient IoT devices, the reduction is compared with already specified 3GPP technologies
[PR.5.23.6-4] The 5G system shall provide the network connection to address the following KPIs for the use of Ambient IoT devices on smart pig farms.
Table 5.23.6-1: Potential key performance requirements for the use of Ambient IoT devices industrialized smart pig farming
Scenario
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Smart livestock farming
(pig barns)
>10 s
(Note 1)
NA
NA
<500 bit/s
Typically,
[< 100 bytes]
(note 2)
850 000 devices / km2
(note 4)
250 m
Indoor
6000 m2
(note 5)
Quasi-stationary
15 minutes to half an hour
(note 3)
NA
NA
NA
NOTE 1: Latency is not critical for this use case.
NOTE 2: Electronic Product Code standard [5], this size is the payload size.
NOTE 3: The livestock health management application monitors pigs’ temperature on a half-hourly basis, sometimes even down to once per 15 minutes [53].
NOTE 4: Stocking density of 1.2 m2/pig is considered high and 2.4 m2/pig considered low [54]. In [55] the stockinggrazing density range from 0.82 m2/pig and 2.46 m2/pig is studied and 1.23 m2/pig proofs suitable stocking density for growing pigs. The device density of 850000 is from a real farm and translates to stocking density of 1.17 m2/pig.
NOTE 5: For a relatively large-sized industrialized smart pig farm, the surface area of a barn is typically 6000 m2.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.24 Use case on smart manhole cover safety monitoring using Ambient IoT
| |
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.24.1 Description
|
Manholes date back to the mid-19th century. Sanitary sewer manholes are primarily used for joining or/and changing the direction of the sewer. As part of the underground infrastructure, manholes provide access for maintenance and for potentially installing additional sewer lines. Worldwide, there have been increasingly a large number of manholes in villages and cities (e.g. parks, sidewalks, parking lots, streets, etc.) as modern civilization grows. For example, U.S. EPA estimates the number of sewer manholes nationwide to be 12 million. Most coincide with the typical lengths of city and suburban blocks, about 100 to 500 feet apart [56]. The total count of utility manholes (adding onto sewer manholes) in the United States is approximately 20 million. A typical large Chinese city has around 1 million manholes. For example, more than 123 million manholes are in use in Wuhan alone [57], which the local government has plans to digitally identify and register each of them. Usually local authorities such as municipalities monitor and inspect assets of city infrastructure. At times manned manhole inspection is carried out with cameras underground to verify degrees of deterioration and provide rehabilitation recommendations. In that process, surface features such as manhole cover and pavement can be reported if restoration is needed [58].
However, manhole covers alone are rarely monitored frequently enough. Often gone unnoticed are they doing their job to keep traffic (e.g. motorist, cyclists) and pedestrians safe, until one falls. In and outside busy cities, falling into manholes causes potential danger of severe injuries or death is lurking, not only where poorly lit.
A recent incident in October 2022 downtown Saint-Nazaire (west coast France) concerns a 39-year-old man found dead early Saturday morning, drowned head down leaving lower legs hanging upright outside the manhole [59]. There are also many stories where children fall into manholes, parents desperately trying to pull them outside but often deadly tragedy prevails [60]. As a matter of fact, accidental fall due to damaged or missing manhole covers has become a silent killer around us. But this is preventable thanks to the use of Ambient IoT.
In Q1 2022, China published intelligent manhole cover national standard GB/T 41401 [61] for municipalities to digitally manage this important asset. The standard requires the manholes to be identifiable by the asset management application, displacement of manhole cover (due to e.g. accidental damage or theft) can be detected by tilt sensors. Additionally, underground water level sensors, vibration sensors (e.g. to detect shock events), and temperature sensors could be deployed.
Figure 5.24.1-1: Manhole where the fatal accident took place , incident as in [59]
In general, manhole use case depends on network deployment. This use case assumes relatively dense network deployment.
For the manhole cover use case, a large number of sensors (a type of Ambient IoT devices) need to be efficiently connected, particularly because they have very limited power source. The communication power consumption of such Ambient IoT devices are expected to be less than 1 mW [86] [87]. As manhole covers are stationary and deployed in outdoor public areas. And because this use case concerns road safety, the communication service availability with sufficient 5G network coverage is important. The data acquisition process of these sensor data is not latency critical. The sensor data (tilt, underground water level, shock) is needed once every 15 minutes. The acquisition of detected abnormality is required within 30 seconds [61]. All these sensors should be durable and maintenance free, as sending technicians to solely replace sensors at each manhole location would be an extra process adding to municipalities OPEX and environmental impact.
In this use case, the municipality M responds to a recent tragic incident similar to [59] by implementing the smart manhole cover management programme “La Bouche d'égout sans Souci”. M has service level agreement with La-Tel-Verte to provide 5G network coverage and enable communication of Ambient IoT devices with the 5G network. La-Tel-Verte per service level agreement provides energy-efficient communication and management services to the municipality M:
- interfacing with municipality M’s manhole cover management platform where application “La Bouche d'égout sans Souci” runs;
- providing energy efficient device management for the Ambient IoT devices based on the instructions from the manhole cover management platform;
- providing energy efficient operation (e.g. inventory, read) the Ambient IoT devices based on the instructions from the manhole cover management platform;
- providing energy efficient security mechanisms for the communication between Ambient IoT devices and the network.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.24.2 Pre-conditions
|
Municipality M has a service level agreement with La-Tel-Verte that ensures Ambient IoT communication service availability by providing sufficient 5G network coverage. This enables the communication of Ambient IoT devices with the 5G network. Municipality M’s manhole project team has installed wireless sensors, a form of Ambient IoT devices, onto all manhole covers within its responsible area to monitor the corresponding parameters (e.g. water level [62], tilt of manhole cover [63], vibration [64]). Water level sensor information can be used to forecast potential flooding. Based on data from tilt sensors and/or vibration sensors, displacing or missing manhole covers could be detected for safety intervention.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.24.3 Service Flows
|
1. The 5G core network receives the request from the application function (“La Bouche d'égout sans Souci” in municipality M’s manhole cover management platform) to operate on the Ambient IoT devices in a certain area. The 5G network starts to operate on these devices accordingly. Once detecting the signals from the 5G network these Ambient IoT devices can respond to the command.
2. Since each of these Ambient IoT devices are uniquely identifiable, in response they send the identification information to the 5G core network and complete the authentication procedure.
3. The Ambient IoT devices (wireless sensors) measure the parameters, such as water level, tilt, and shock/vibration.
In this use case, sample size for water level sensor and tilt sensor is respectively 8 bits [62] and 32 bits [63]. With typical sampling rate being 10 Hz, the data generation is less than 400 bit/s. For vibration measurement, typical sampling rate is 10 Hz with sample size of max 48 bits [64] (e.g. 3-axis, 8 bit per axis; possibly per axis two measurement values to register acceleration). Thus, in total the data generation per Ambient IoT device is up to 880 bit/s.
4. The 5G core network, based on the requests issued by the application function, performs operations such as "inventory" and "read" on the Ambient IoT devices correspondingly. "Inventory" operation is to read the Ambient IoT device identifier. "Read" operation is to read sensor data.
5. The 5G core network then sends the results of the operations to the application function. The application function includes diagnostic functions that analyze the sensor data and detect the anomaly and trigger maintenance actions when necessary. Typically, the sensor data is collected once per 15 minutes.
6. When the application function “La Bouche d'égout sans Souci” receives sensor data that is considered by the application function to be related to potential problem of a specific manhole cover, the application function can request the information of the Ambient IoT device on that manhole cover more frequently. The max allowed latency is 30 seconds [61].
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.24.4 Post-conditions
|
The 5G network enables efficient communication for Ambient IoT devices. Thanks to that, municipality M’s intelligent manhole cover management application function “La Bouche d'égout sans Souci” is enabled by the 5G system to remotely monitor the large number of manholes in its responsible area for safety and maintenance reasons. Depending on the needs/logic of the application function, the application function is enabled by 5G system to retrieve the sensor data from a specific or a given group of Ambient IoT devices.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.24.5 Existing features partly or fully covering the use case functionality
|
SA1 has performed various studies on IoT in previous releases, where related normative stage 1 requirements are introduced in TS 22.011 [9], TS 22.278 [7], TS 22.368 [6], and TS 22.261 [8].
TS 22.011 introduces access control for MTC, examples of periodic network selection attempts are:
For UEs only supporting any of the following, or a combination of, NB-IoT, GERAN EC-GSM-IoT [18], and Category M1[13] of E-UTRAN enhanced-MTC, the UE shall interpret the interval value to be between 2 and 240 hours, with a step size of 2 hours between 2 and 80 hours and a step size of 4 hours between 80 and 240 hours.
In the absence of a permitted value in the SIM/USIM, or the SIM/USIM is phase 1 and therefore does not contain the datafield, then a default value of 60 minutes, shall be used by the UE except for those UEs only supporting any of the following, or a combination of: NB-IoT, GERAN EC-GSM-IoT [18], and Category M1 [17] of E-UTRAN enhanced-MTC. For those UEs a default value of 72 hours shall be used.
NOTE: Use of values less than 60 minutes may result in excessive UE battery drain.
TS 22.368 addresses features of MTC communication and service requirements related to MTC device triggering, addressing, identifiers, low mobility, small data transmission, infrequent MT communication, security, remote MTC device management, group-based MTC features including policing and addressing, etc. Example requirements are:
The system shall provide mechanisms to lower power consumption of MTC Devices.
The system shall provide mechanisms for the network operator to efficiently manage numbers and identifiers related to MTC Subscribers.
TS 22.261 captures some important service requirements for IoT, e.g.
The 5G system shall support a secure mechanism for a home operator to remotely provision the 3GPP credentials of a uniquely identifiable and verifiably secure IoT device.
The 5G system shall support a secure mechanism for the network operator of an NPN to remotely provision the non-3GPP identities and credentials of a uniquely identifiable and verifiably secure IoT device.
An IoT device which is able to access a 5G PLMN in direct network connection mode using a 3GPP RAT shall have a 3GPP subscription.
The 5G system shall allow the operator to identify a UE as an IoT device based on UE characteristics (e.g. identified by an equipment identifier or a range of equipment identifiers) or subscription or the combination of both.
An IoT device which is able to connect to a UE in direct device connection mode shall have a 3GPP subscription, if the IoT device needs to be identifiable by the core network (e.g. for IoT device management purposes or to use indirect network connection mode).
The 5G system shall support operator-controlled alternative authentication methods (i.e. alternative to AKA) with different types of credentials for network access for IoT devices in isolated deployment scenarios (e.g. for industrial automation).
Additional consideration needs to be given in support of Ambient IoT devices that are battery-less or with limited energy storage capability, which present new challenges to the 5G system.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.24.6 Potential New Requirements needed to support the use case
|
[PR.5.24.6-1] The 5G system shall support energy efficient communication mechanisms (i.e. minimizing the device communication power consumption) for Ambient IoT devices, while meeting the communication performance requirements.
[PR 5.24.6-2] The 5G system shall provide a mechanism for a 3rd party application to write user data to and to read user data from an Ambient IoT device.
[PR 5.24.6-3] The 5G system shall be able to collect charging information for a large group of closely located Ambient IoT devices in an efficient way.
NOTE: for example, the efficiency could be reduced total number of charging data related to a group of Ambient IoT devices, the reduction is compared with already specified 3GPP technologies.
[PR.5.24.6-4] The 5G system shall provide the network connection to address the KPIs for the use of Ambient IoT devices for smart manhole cover monitoring, see table 5.24.6-1.
Table 5.24.6-1: Potential key performance requirements for the use of Ambient IoT devices for smart manhole cover monitoring
Scenario
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Smart manhole cover remote monitoring
10 s - 30 s
(note 1)
99%
NA
<1 kbit/s
Typically,
[< 100 bytes]
(note 2)
<1000 devices / km2
(note 3)
300 m - 500 m
Outdoor(note 6, note 7)
City wide including rural areas
(note 4)
Stationary
15 min
(note 5)
NA
NA
NA
NOTE 1: Latency is not critical. Per GB/T 41401 [61], the max latency is smaller than 30 seconds.
NOTE 2: This size is the payload size, compatible with allowed business data length by Electronic Product Code standard [5]. Considering EPC for identification is 96 bits, the total message size is < 100 bytes.
NOTE 3: Assuming there is one manhole every 200 feet [56]. Referring to data from the United States [56], sewer manholes are about 100 to 500 feet apart, additionally there are other utility manholes present. According to Wuhan data [57], 123 million manholes are known per 8569 km2.
NOTE 4: As local authority is the customer, the service should be available for all the utility manholes within the responsible area of that municipality.
NOTE 5: For manhole cover remote monitoring, per 15-minutes data acquisition is sufficient to largely increase road traffic safety.
NOTE 6: The value is dependent on the actual network deployment.
NOTE 7: This communication range implies a relatively dense network deployment.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.25 Use case on smart bridge health monitoring using Ambient IoT
| |
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.25.1 Description
|
Bridges as public infrastructure characterize city formation. To facilitate transportation, more bridges are built as cities form and evolve. Apart from obvious roles bridges play in transortation of people and goods, its importance also lies in its being the social infrastructure and cutural assets [65]. As the number of bridges grow, longer and bigger bridges are put in use. Incidents of bridge collapsing usually lead to catastrophy. In the course of city expansion and population growth, numerous deaths due to bridge collapse have been recorded, such as recent events reported in [66], [67] and [68]. The most heart-breaking tragic to date is the Indian pedestrian bridge collapse in Guikarat in the midst of Diwali religious celebration, where death toll rises above 130 [69]. As awareness continues to rise, various actors including local governements are starting to take on a more active role in monitoring and maintenance of those vital infrastructure [70].
Ambient IoT can be used for smart bridge health monitoring to contribute to prevention of disasters. As bridges are parts of outdoor public infrastructure and the use case is about safety, the communication service availability with sufficient 5G network coverage are important. Additionally, as more health data of a bridge is collected, the corresponding actors (e.g. local governmement) have deeper knowledge in its health state to better control the maintenance work and eventually control the cost [71]. In 2022, China published national specification GB/T 39339.2 that hightlights safety monitoring of bridges as part of transit facilities in cities [72].
In this use case, local government of city Philario responds to a recent tragic incident by implementing the smart bridge health monitoring programme “SAFE”. Philario has service level agreement with O-Tel to provide 5G network coverage and enable communication of Ambient IoT devices with the 5G network O-Tel per service level agreement provides energy-efficient communication and management services to the local government of Philario:
- interfacing with local government Philario’s smart bridge health monitoring platform;
- providing energy efficient device management for the Ambient IoT devices based on the instructions from Philario’s smart bridge health monitoring platform;
- providing energy efficient operation (e.g. inventory, read) the Ambient IoT devices based on the instructions from Philario’s smart bridge health monitoring platform;
- providing energy efficient security mechanisms for the communication between Ambient IoT devices and the network.
The communication power consumption of such Ambient IoT devices are expected to be less than 1 mW [86] [87].
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.25.2 Pre-conditions
|
Philario’s local government’s bridge safety maintenance project team X has installed wireless sensors, a form of Ambient IoT devices, onto selected bridges within its responsible area to monitor the corresponding parameters (e.g. tilt sensors to monitor inclination of bridge deck or pier [73], vibration [74]). X has a service level agreement with service provider Y that deploys sufficient 5G network coverage to ensure communication service availability. This enables the communication of Ambient IoT devices with the 5G network, where needed. Based on per 15-minute data from tilt sensors and vibration sensors, health status of bridges is recorded and analyzed for safety intervention.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.25.3 Service Flows
|
1. The 5G core network receives the request from the application function (request sent from Philario’s smart bridge health monitoring platform) to operate on the Ambient IoT devices installed on a given bridge or a given set of bridges. The 5G core network starts to operate on these devices accordingly. Once detecting the signals from the 5G network these Ambient IoT devices can respond to the command.
2. Since each of these Ambient IoT devices are uniquely identifiable, in response they send the identification information to the 5G core network and complete the authentication procedure.
3. The Ambient IoT devices (wireless sensors) measure the parameters, such as water level, tilt, and vibration.
The sample size for tilt sensor 32 bits [73]. With typical sampling rate being 10 Hz, the data generation is less than 400 bit/s. For vibration measurement, typical sampling rate is 10 Hz with sample size of max 48 bits [74] (e.g. 3-axis, 8 bit per axis; possibly per axis two measurement values to register acceleration). Thus, in total the data generation per Ambient IoT device is up to 880 bit/s.
4. The 5G core network, based on the requests issued by the application function, performs operations such as "inventory" and "read" on the Ambient IoT devices correspondingly. "Inventory" operation is to read the Ambient IoT device identifier. "Read" operation is to read sensor data.
5. The 5G core network then sends the results of the operations to the application function. The application function includes diagnostic functions that analyze the sensor data and detect the anomaly and trigger maintenance actions when necessary. Typically, the sensor data is collected once per 15 minutes.
6. When the bridge health monitoring application receives sensor data, by analysis it may decide to request the information of the Ambient IoT device associated with a specific bridge more frequently (e.g. per 10-minute) on-demand.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.25.4 Post-conditions
|
The 5G network enables efficient communication for Ambient IoT devices. Thanks to that, local government Philario’s bridge health monitoring application function is enabled by the 5G system to remotely monitor the large number of sensors (Ambient IoT devices) on the target bridges within Philario’s responsible area. Depending on the needs/logic of the application function, the application function is enabled by 5G system to retrieve the sensor data from a specific or a given group of Ambient IoT devices.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.25.5 Existing features partly or fully covering the use case functionality
|
SA1 has performed various studies on IoT in previous releases, where related normative stage 1 requirements are introduced in TS 22.011 [9], TS 22.278 [7], TS 22.368 [6], and TS 22.261 [8].
TS 22.011 introduces access control for MTC, examples of periodic network selection attempts are:
For UEs only supporting any of the following, or a combination of, NB-IoT, GERAN EC-GSM-IoT [18], and Category M1[13] of E-UTRAN enhanced-MTC, the UE shall interpret the interval value to be between 2 and 240 hours, with a step size of 2 hours between 2 and 80 hours and a step size of 4 hours between 80 and 240 hours.
In the absence of a permitted value in the SIM/USIM, or the SIM/USIM is phase 1 and therefore does not contain the datafield, then a default value of 60 minutes, shall be used by the UE except for those UEs only supporting any of the following, or a combination of: NB-IoT, GERAN EC-GSM-IoT [18], and Category M1 [17] of E-UTRAN enhanced-MTC. For those UEs a default value of 72 hours shall be used.
NOTE: Use of values less than 60 minutes may result in excessive UE battery drain.
TS 22.368 addresses features of MTC communication and service requirements related to MTC device triggering, addressing, identifiers, low mobility, small data transmission, infrequent MT communication, security, remote MTC device management, group-based MTC features including policing and addressing, etc. Example requirements are:
The system shall provide mechanisms to lower power consumption of MTC Devices.
The system shall provide mechanisms for the network operator to efficiently manage numbers and identifiers related to MTC Subscribers.
TS 22.261 captures some important service requirements for IoT, e.g.
The 5G system shall support a secure mechanism for a home operator to remotely provision the 3GPP credentials of a uniquely identifiable and verifiably secure IoT device.
The 5G system shall support a secure mechanism for the network operator of an NPN to remotely provision the non-3GPP identities and credentials of a uniquely identifiable and verifiably secure IoT device.
An IoT device which is able to access a 5G PLMN in direct network connection mode using a 3GPP RAT shall have a 3GPP subscription.
The 5G system shall allow the operator to identify a UE as an IoT device based on UE characteristics (e.g. identified by an equipment identifier or a range of equipment identifiers) or subscription or the combination of both.
An IoT device which is able to connect to a UE in direct device connection mode shall have a 3GPP subscription, if the IoT device needs to be identifiable by the core network (e.g. for IoT device management purposes or to use indirect network connection mode).
The 5G system shall support operator-controlled alternative authentication methods (i.e. alternative to AKA) with different types of credentials for network access for IoT devices in isolated deployment scenarios (e.g. for industrial automation).
Additional consideration needs to be given in support of Ambient IoT devices that are battery-less or with limited energy storage capability, which present new challenges to the 5G system.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.25.6 Potential New Requirements needed to support the use case
|
[PR.5.25.6-1] The 5G system shall support energy efficient communication mechanisms (i.e. minimizing the device communication power consumption) for Ambient IoT devices, while meeting the communication performance requirements.
[PR 5.25.6-2] The 5G system shall provide a mechanism for a 3rd party application to write user data to and to read user data from an Ambient IoT device.
[PR 5.25.6-3] The 5G system shall be able to collect charging information for a large group of closely located Ambient IoT devices in an efficient way.
NOTE: for example, the efficiency could be reduced total number of charging data related to a group of Ambient IoT devices, the reduction is compared with already specified 3GPP technologies.
[PR.5.25.6-4] The 5G system shall provide the network connection to address the KPIs for the use of Ambient IoT devices for smart bridge health monitoring as in the table below.
Table 5.25.6-1: Potential key performance requirements for the use of Ambient IoT devices for smart bridge health monitoring
Scenario
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Smart bridge health monitoring
10 s
(note 1)
99%
NA
<1 kbit/s
Typically,
[< 100 bytes]
(note 2)
<1000 devices / km2
(note 4)
300 m - 500 m
Outdoor(note 5)
Along the bridge
Stationary
15 min
(note 3)
NA
NA
NA
NOTE 1: Latency of smart bridge health monitoring is not critical, as the sensor information is needed by the monitoring application on a per-15 minutes basis.
NOTE 2: This size is the payload size, compatible with allowed business data length by Electronic Product Code standard [5]. Considering EPC for identification is 96 bits, the total message size is < 100 bytes.
NOTE 3: For bridge health monitoring, per 15-minutes data acquisition is sufficient.
NOTE 4: For bridge health monitoring applications, the distances among sensors are larger than 10 meters. Big data analysis-based bridge health monitoring deploys 369 sensors of various types on Changjiang bridge, in Shanghai [75]. In Beijing, around 150 sensors are deployed on Dongsha bridge of 1360 meter length [76]. In busy sections of mega cities, concentration of bridges can be considerate.
NOTE 5: The value is dependent on the actual deployment.
5.26 Use case on Elderly Health Care
5.26.1 Description
As elderly population is increasing, close, daily monitoring of their health is acquiring more relevance in health care systems. Chronic diseases that require continuous attention are common among this age group. Moreover, autonomy of the elderly has an important role in active aging, as it is strongly associated with longevity, good self-assessed health, and the prevention of depression and cognitive deterioration. Autonomy is an essential concept because it relates directly to dignity, regardless of health circumstances.
Due to extreme conditions, like local epidemics, pandemic or natural disasters, health care systems can be overwhelmed. Relying on technology such as automated assistance using mobile communications system infrastructure can lower pressure on the health system, as chronic diseases are appropriately followed up. This improves the overall health system, freeing resources for other critical, life-threatening situations.
This use case presents a scenario where an elder is aided to quickly locate medicines both indoors and outdoors using Ambient IoT devices (Ambient IoT tags). These Ambient IoT tags are very small, battery-less powered IoT devices that use an energy harvesting mechanism to produce a limited amount of power, at microwatts level. After some initial setup, we assume that the Ambient IoT device can harvest the energy necessary from RF signals to be able to operate.
This use case is about an elder, Scott. He is 85 and had heart attack at 80. Since then, he needs to take a variety of medicines daily prescribed by Rachel, his doctor. During his last check-up, his heart condition has worsened because he forgets sometimes to take his medicines. Scott’s memory is not what used to be. He remembers he must take medicines but forgets which ones.
To help Scott to be autonomous on his own, and improve his heart condition, Rachel decided to prescribe him medicines from a new supplier: DontForgetYourMed. DontForgetYourMed offers a personalised service that allows the patient’s doctor to set up the quantity and frequency of the medicines prescribed. Using medicines packets with Ambient IoT tags attached, DontForgetYourMed reaches the patient to take those medicines at specific times, making the availability of the service on demand.
In the case of Scott, his heart rate is monitored with his smartwatch, and it is notified regularly to DontForgetYourMed service. This way, Rachel can modify the frequency of some medicines depending on a configured threshold of Scott’s heart rate.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.26.2 Pre-conditions
|
The following pre-conditions and assumptions apply to this use case:
• A subscription to DontForgetYourMed service that establishes a communication with the UE of the elder to send alerts and request confirmations related to the medicines prescribed.
• A smart watch (UE) to receive and confirm alerts and monitor elder’s heart rate continuously.
• 5G network to support the communication with Ambient IoT devices.
• Medicine packets equipped with an Ambient IoT tag and a small led. When the medicine packet is received by the elder, some pre-settings will give energy to the Ambient IoT device, and it will also establish the location of the Ambient IoT device.
• Each Ambient IoT tag is connected to the 5G network, and the communication is enabled
• Communication will be established on demand, not continuously.
5.26.3 Service Flows
Indoors scenario is more focused in habit: medicine is taken daily at specific time of the day. Outdoors scenario is more focused as an exception of the normal routine: the service reacts to the elder’s heart rate. Both scenarios could be combined.
Indoors scenario
1. Each morning, Scott receives an alert in his smart watch where the medicine dose is displayed. This alert recommends him to take one pill from ‘packet Blue’ and one pill from ‘packet Pink’.
2. Scott confirms the reception of the message and then, DontForgetYourMed requests the 5G system to establish a downlink communication with the ambient IoT tag and switches on a small LED embedded within the same tag.
3. Scott walks to his medicine cabinet to retrieve the medicines. Inside, 2 packets are lit: ‘packet Blue’ and ‘packet Pink’. After taking both pills, he returns the packets to the medicine cabinet.
4. After a pre-configured timer expires, Scott receives another alert to confirm he has taken each of the requested medicines. He confirms them both, and starts a new, healthy day.
5. After the confirmation, DontForgetYourMed requests the 5G system to establish another downlink communication with the ambient IoT tag, and the small LED is switched off.
Outdoors scenario
1. Scott feels far better so he decides to go to play tennis with Oliver and informs Rachel. She prescribes an additional medicine to take during the game, depending on Scott’s heart rate. When the game is on, Scott’s heart rate is too high, so he receives an alert to take one pill from ‘packet Blue’.
2. Scott confirms the reception of the message and then, DontForgetYourMed requests the 5G system to establish a downlink communication with the ambient IoT tag and switches on a small LED embedded within the same tag.
3. He starts to feel bad but as the medicine packet is in his backpack, Oliver helps him to retrieve it. He looks for Scott’s backpack to see one medicine blue packet lit: ‘packet Blue’. He gets the packet to Scott and helps him to get his medicine.
4. After the pre-configured timer expires, Scott receives another alert to confirm he has taken the medicine. Oliver helps Scott to confirm it, and rests until he feels better.
5. After the confirmation, DontForgetYourMed requests the 5G system to establish another downlink communication with the ambient IoT tag, and the small LED is switched off.
5.26.4 Post-conditions
5G communication has been established to a UE to prescribe medicines, and request for confirmation of medicine intake.
Several downlink communications have been established from the gNB to one or several medicine packets. This downlink communication has been low power, and for a small period, and the amount of data sent has been minimal.
5.26.5 Existing features partly or fully covering the use case functionality
None.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.26.6 Potential New Requirements needed to support the use case
|
[PR.5.26.6-001] The 5G system shall be able to support mechanisms to communicate efficiently with Ambient IoT devices.
[PR.5.26.6-002] When setting up communication to an Ambient IoT device the 5G system shall be able to handle the unavailability of Ambient IoT devices either due to lack of power or due to power saving mechanisms of the Ambient IoT device.
[PR.5.26.6-003] The 5G system shall be able to provide an Ambient IoT service with following KPIs:
Table 5.26.6-1: Ambient IoT service KPI for elderly health care
Scenario
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Indoors elderly health care scenario
1 s
NA
NA
<1 kbit/s
<100 bits
<20 per 100 m2
20 m
<250 m2
(note 1)
Static
NA
NA
NA
NA
Outdoors elderly health care scenario
1 s
NA
NA
<1 kbit/s
<100 bits
<20 per 100 m2
(note 2)
200 m
City wide including rural areas
Static
NA
NA
NA
NA
NOTE 1: Average size of a big house.
NOTE 2: For the outdoor scenario the device density is expected to be generally lower than indoor[88]. For example, based on outdoor tennis court sizes (four players in a 23.77m x 10.97m doubles matches court), assuming one medicine box per elderly consumer, the device density is not higher than 5/100m2.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.27 Use case on end-to-end logistics
| |
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.27.1 Description
|
In a logistics scenario, Ambient IoT devices can be used to track specific goods (e.g. TVs) from the factory where they are made until delivery at the final end-customer. E.g. an Ambient IoT device could be attached to the packaging of a TV, which can then be used for tracking in the factory, in one or more warehouses on the way from factory to the customer and finally to the track the delivery at the end customer.
In this end-to-end logistics trajectory, an Ambient IoT device will encounter multiple different networks (NPNs, PLMNs) in different regions and countries. Each of these networks have to follow different frequency regulations and have different frequency licenses. The Ambient IoT device needs to be able to deal with these differences.
Limitations in range for Ambient IoT can imply that some additional infrastructure needs to be deployed. However, it is not assumed that a network needs to be deployed specifically for Ambient IoT support. It should be possible to integrate Ambient IoT communication in networks that are also used for other 5G communication.
The assumption in this use case is that the Ambient IoT devices need to be triggered to send their identification. When the Ambient IoT devices are not triggered they remain in a suspended state and cannot send or receive information.
The owner of a network (e.g. in a factory or warehouse) can decide which part of the network (e.g. which base stations) to use to trigger Ambient IoT devices. This way, e.g. Ambient IoT devices in only part of the factory are triggered. It should also be possible to trigger only a selected group of Ambient IoT devices (e.g. through broadcasting a group ID), or to trigger the Ambient IoT devices for specific actions (e.g. receive information instead of broadcasting an ID).
Figure 5.27.1-1: Tracking a cardboard box a TV is transported in by attaching an Ambient IoT Device to the box
Where the network itself does not have the support to trigger the Ambient IoT device (e.g. in the PLMN where the TV is delivered to the door of the customer), a handheld device can be used. This handheld device can, when needed, relay the communication from the Ambient IoT device towards the network. The handheld device can collect several messages from one or more Ambient IoT devices before forwarding these messages to the network. This ‘store-and-forward’ messaging also allows messaging from an Ambient IoT device when there is no end-to-end connectivity from Ambient IoT device to the network.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.27.2 Pre-Conditions
|
Factory A has deployed a standalone NPN.
TV_company has an agreement with the NPN in Factory A and with PLMN_X to use a third party interface to trigger Ambient IoT devices.
The Ambient IoT device has credentials with PLMN_X that can also be used for the standalone NPN in factory A. Furthermore, PLMN_X has roaming agreements with operators in other countries.
Warehouse B deploys a NPN implemented as a slice on PLMN_Y.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.27.3 Service Flows
|
1. TV_company uses Factory A to manufacture its TVs. After manufacturing, the TVs are packaged in a cardboard box and the box is then equipped with an Ambient IoT device (in the form of a sticker) for tracking/tracing of the TV.
2. Within the Factory A, the TVs are stored for a while in internal storage. Tracking of the TVs in storage is possible through Ambient IoT. The TV_company instructs the NPN that is deployed in the Factory A to trigger the TVs in the internal storage only. TVs that are still in the production area do not need to be triggered. The Ambient IoT devices are triggered to send their ID. This way the TV_company can create an inventory of all TVs that are still in store at the factory. The Ambient IoT devices can also be triggered to receive information (e.g. instructions).
3. A shipment of TV is sent to a warehouse in a Country_X. The warehouse uses a NPN implemented as a slice on PLMN_Y. Because of roaming agreements between PLMN_Y and PLMN_X, the Ambient IoT devices can access the NPN network in the warehouse. Note for the NPN in Country_X different regulations apply than for the NPN in Factory A.
4. TV_company wants to create an inventory of the TVs that are stored in the warehouse. However, the warehouse also stores products from other companies. Therefore the TV_company instructs the NPN to trigger only the TVs from TV_company through the use of a group ID that identifies these TVs. Ambient IoT devices on other products will not be triggered to respond.
5. Finally the TV is delivered to the end-customer. The delivery driver uses a handheld device to trigger the Ambient IoT device on the box to send its ID to the network. If the network is within range, the Ambient IoT device can communicate directly to the network. Otherwise the handheld device can relay the communication. Even if the handheld device is not connected to the network either, the Ambient IoT devices can still send messages to the handheld device. The handheld device can forward these messages to the network when it connects to the network.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.27.4 Post-Conditions
|
TV_Company has full traceability of its products from the factory in one country, to the delivery at the end-customer in another country.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.27.5 Existing features partly or fully covering the use case functionality
|
3GPP TS22.101 Clause 29.2 contains the following requirements:
Support of 3rd party requested broadcast
- The 3GPP Core Network shall enable a 3rd party service provider to request sending a broadcast message in a specified geographic area (as specified in TS 22.368 [52]) expecting to reach a group of devices that are served by the 3rd party service provider.
A 3rd party requested broadcast can be used to trigger a group of IoT devices in a specific geographic area. But this requirement does not include the feature of waking up Ambient IoT devices.
3GPP TS22.368 Clause 7.1.2 contains the following requirements on MTC Device triggering:
- The network shall be able to trigger MTC Devices to initiate communication with the MTC Server based on a trigger indication from the MTC Server.
- The system shall provide a mechanism such that only trigger indications received from authorized MTC Servers will lead to triggering of MTC Devices.
- Upon receiving a trigger indication from a source that is not an authorized MTC Server, the network shall be able to provide the details of the source (e.g. address) to the MTC User.
- The system shall provide a mechanism to the MTC User to provide a set of authorized MTC Server(s).
- Upon receiving a trigger indication, if the network is not able to trigger the MTC Device, the 3GPP system may send an indication to the MTC Server that triggering the MTC Device has been suppressed.
Note: Suppression of triggering could be due to system conditions such as network congestion.
- A MTC Device shall be able to receive trigger indications from the network and shall establish communication with the MTC Server when receiving the trigger indication. Possible options may include:
- Receiving trigger indication when the MTC Device is not attached to the network.
- Receiving trigger indication when the MTC Device is attached to the network, but has no data connection established.
- Receiving trigger indication when the MTC Device is attached to the network and has a data connection established.
Based on the requirements in 3GPP TS22.368, 3GPP TS23.682 Clause 4.5.1 contains the following description:
Device Triggering is the means by which a SCS sends information to the UE via the 3GPP network to trigger the UE to perform application specific actions that include initiating communication with the SCS for the indirect model or an AS in the network for the hybrid model. Device Triggering is required when an IP address for the UE is not available or reachable by the SCS/AS.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.27.6 Potential New Requirements needed to support the use case
|
[PR.5.27-001] The 5G system shall be able to support an Ambient IoT device to function in different countries in accordance with local regulations.
[PR.5.27-002] The 5G system shall support Ambient IoT device triggering to get one or more Ambient IoT devices to perform specific actions including to initiate communication with the network.
[PR.5.27-003] The 5G network shall be able to trigger Ambient IoT devices. The 5G system shall enable an authorized 3rd party to instruct the 5G network in which area, which group of Ambient IoT devices needs to be triggered and which action the Ambient IoT devices need to perform when triggered (e.g. send ID, receive further information, send measurement value).
[PR.5.27-004] The 5G system shall support relaying communication from an Ambient IoT device to the network.
[PR.5.27-005] The 5G system shall support authenticated, encrypted and integrity protected store-and-forward communication from an Ambient IoT device to the network via a single UE when there is no end-to-end connection between the Ambient IoT device and the network
NOTE: It is assumed that the UE and the Ambient IoT device are authorized by the operator to communicate with each other.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.28 Use case on pressure powered switch
| |
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.28.1 Description
|
A pressure powered switch can harvest energy from the kinetic energy of the pushing on the switch. Existing non-3GPP products can e.g. connect wirelessly to a controller over approximately 25 m indoor and 150 m outdoor. These products do not adhere to 3GPP protocols for signalling and user communication.
Figure 5.28.1-1: A pressure powered switch
The registration procedure for 5G according to TS 23.502 [77] shows 25 different steps which 8 involve the UE. Several of these steps involve multiple interactions. This registration procedure does not even include the actual data communication. Compared to the minimal information transfer requirement for a button switch (only its ID), it is clear that the registration involves far more information than the actual data transport. Furthermore, a registration procedure will likely take longer than the time the switch has power available. This runs the risk that the switch can start a registration (or other) signaling procedure, but cannot successfully complete it. Furthermore, it is important to note that some procedures are timer-driven. For example, the UE is configured with a periodic registration timer and can be implicitly de-registered if the UE is not able to perform a registration procedure when the timer expires. It cannot be assumed that switch will be pressed frequently enough to avoid an implicit de-registration.
The purpose of the use case is to propose a requirement to optimize Ambient IoT signaling to reduce the amount of signaling interactions and thus save power and time.
Note: The pressure powered switch is an example for other Ambient IoT devices that only have a very limited amount of energy for a very short amount of time (e.g. door/window sensors, vibration sensors).
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.28.2 Pre-conditions
|
None
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.28.3 Service Flows
|
1. The switch is being pushed.
2. The switch harvests the energy from the push, wakes up and communicates to the network.
3. Through optimized protocols only a minimal number of signalling interactions is needed. This allows the switch to complete the signalling procedure. As part of the signalling, the switch also transmits its identity.
4. The network transfers the identity information from the switch to an application server, which e.g. determines that a light needs to be turned on.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.28.4 Post-conditions
|
The light is successfully switched on.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.28.5 Existing features partly or fully covering the use case functionality
|
Existing signaling procedures and data transfer procedures for 5G are specified in TS 23.502 [77]. It is clear that these procedures are not optimized for a minimal number of signaling interactions. This runs the risk that an Ambient IoT device cannot complete these procedures before running out of power.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.28.6 Potential New Requirements needed to support the use case
|
[P.R.5.1.6-001] The 5G system shall support more efficient procedures for Ambient IoT control and user data transmission compared to earlier 3GPP technologies; in terms of a reduced number of interactions between the network and the Ambient IoT device.
NOTE: In this context each interaction is a single instance of control or user data transmission to or from the Ambient IoT device
[P.R.5.1.6-002] The 5G system shall support procedures that take into account the specific nature of Ambient IoT devices (e.g. some Ambient IoT devices will not be able to initiate procedures periodically or after a specific time).
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.29 Use case on Device Permanent Deactivation
| |
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.29.1 Description
|
This use case illustrates the need to define capabilities that allows the end user or a third party to remotely manage the permanent deactivation of an Ambient IoT device.
The scenario describes a production manager who oversees the manufacture of Integrated Circuits (IC) wafers. The environmental conditions under which the wafers are produced may be considered as industrial secrets, as the production process may require a precise combination of pressure, temperature and humidity to produce IC wafers of optimal quality. To assist in quality control, the production process includes the use of Ambient IoT devices to record the environmental conditions under which the wafers are produced. The production manager may use the sensor data recorded by the Ambient IoT device following the completion of the manufacturing process to verify that environmental conditions were maintained as required.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.29.2 Pre-conditions
|
The production manager has inactive Ambient IoT devices in storage that can collect sensor data, record the data and transmit the recorded data.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.29.3 Service Flows
|
Device activation
1. As a new batch of IC wafers is about to be manufactured, the production manager removes from storage the Ambient IoT devices and adds an Ambient IoT device to each pre-production wafer.
2. The production manager accesses an application that is used to manage the connectivity and operations of Ambient IoT devices. Via this application, the production manager activates an Ambient IoT device to enable the operations of the device (e.g., take and record sensor data).
Device operation
3. During the manufacture process, the Ambient IoT device records the data collected by its sensors.
4. Following completion of the manufacturing process, the production manager wants to access the sensor data that has been recorded on the Ambient IoT device.
5. The production manager accesses an application to manage the connectivity and operations of the Ambient IoT devices. Via this application, the production manager triggers the Ambient IoT device to upload the recorded sensor data to the network.
6. Following completion of the manufacturing process, the production manager wants to clear the sensor data that has been recorded on the Ambient IoT device.
7. The production manager accesses an application to manage the connectivity and operations of the Ambient IoT devices. Via this application, the production manager triggers the Ambient IoT device to delete the recorded sensor data.
Device deactivation
8. The production manager wants to deactivate Ambient IoT devices to disable their operation while the devices are not being used in the manufacturing process.
9. The production manager accesses an application to manage the connectivity and operation of the Ambient IoT devices. Via this application, the production manager deactivates and disables the operation of the device.
10. The production manager removes the deactivated Ambient IoT devices from the finished wafers and returns the devices to storage for possible re-use.
Device end of life cycle
11. The production manager determines that the Ambient IoT devices have reached the end of their life cycle and should no longer be used during the wafer manufacturing process.
12. The production manager accesses an application to manage the connectivity and operation of the Ambient IoT devices. Via this application, the production manager permanently configures an Ambient IoT Device such that all transmissions of the Ambient IoT device are permanently deactivated.
13. The production manager discards the permanently deactivated Ambient IoT device as it is no longer possible to activate, enable its operation or access recorded data.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.29.4 Post-conditions
|
Device permanently deactivated
Two-way communications by an Ambient IoT device are permanently deactivated.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.29.5 Existing features partly or fully covering the use case functionality
|
TS 22.261 clause 6.14.1 describe the following:
During their life cycle these IoT devices go through different stages, …, the activation of the IoT device by the preferred operator, a possible change of operators, etc. These stages need to be managed securely and efficiently.
Clause 6.14.2 defines the following requirement:
Based on operator policy, the 5G system shall provide means for authorised 3rd parties to request changes to UE subscription parameters for access to data networks, e.g., static IP address and configuration parameters for data network access.
The requirement above covers remote UE subscription activation and subscription suspension / deactivation.
If the subscription of an Ambient IoT device has been suspended or terminated, the device can still continually harvest energy and therefore may continue to attempt accessing the network or be accessed by a network. This can result in a security risk where a discarded Ambient IoT Device may be obtained by unauthorized users such that data or other parameters of the device may be subject to unauthorized access.
Therefore, there is a need to permanently deactivated the device such that the device may never be activated and accessed again.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.29.6 Potential New Requirements needed to support the use case
|
[PR 5.29.6-1] Based on operator policy, the 5G system shall provide suitable mechanism to permanently disable the capability of an Ambient IoT device or a group of Ambient IoT devices to transmit RF signals.
[PR 5.29.6-2] Based on operator policy, the 5G system shall provide means for a trusted third party to request the deletion of any digitally stored information of an Ambient IoT device.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.30 Use case on Ambient IoT device acting as a controller in smart agriculture
| |
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.30.1 Description
|
In agricultural production, there are many factors that affect the growth of crops, such as soil, climate, water, species, pests and weeds, etc. The yield of crops is the result of the combined influence of these factors. The smart agriculture can increase production, expand planting range and planting cycle by using sensors to monitor the growing environment of crops, and using some controller to correspondingly periodically control the equipment (e.g., the pesticide spraying equipment and irrigation equipment) in the farmland based on the sensed results.
It’s hard to provide a stable and continuous power supply for the controller deployed in the outdoor farmland. The Ambient power-enabled IoT devices, which can obtain and/or store energy from the environment, can be attached in the smart agriculture equipment and used as the controller to control the equipment in the farmland. The ambient IoT devices can harvest the energy from the environment to support its communication implementation.
Considering the operations of the pesticide spraying and irrigation equipment in the farmland is periodically, the ambient IoT controller can be activated periodically to save its energy. After the 5G network receives the demand from the Farm Management Platform, it can periodically activate the ambient IoT controller and then the ambient IOT controller will receive operation information and operate accordingly. The operation information includes e.g., the period to switch on and switch off the irrigation equipment, the amount of sprayed pesticide in each time, the spraying direction of each pesticide spraying equipment and etc.
Following is an example of service flow to describe the ambient IoT device is activated periodically and acting as a controller to control the equipment in the farmland.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.30.2 Pre-conditions
|
The farmer “FF” owns a huge farmland, and installed several pesticide spraying and irrigation equipment in the different location of the farmland to cover the whole farmland. Each pesticide spraying or irrigation equipment is attached with an ambient IoT device, which is an “Ambient IoT controller” to control the operation of pesticide spraying and irrigation equipment (e.g., to control the on/off of pesticide spraying and irrigation system, the spraying direction operation of pesticide spraying system, and etc.) .
Some sensors are also deployed in the farmland to sense and monitor the condition and environment of the farmland.
The operator M has deployed 5G network to provide the “Green Farm comm.” communication service for farmers. The farmer “FF” has subscribed the service.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.30.3 Service Flows
|
1. The FMP collects the sensing results from the sensors in the farmland. Based on the analysis of the current condition of farmland, the FMP decides which pesticide spraying and irrigation equipment should be put into use.
2. Considering the growth regulation of farmland crops, irrigation and pesticide spraying can work periodically. Thus, the FMP decides the communication patterns of ambient IoT controllers and ask the 5G network to periodically activate the ambient IoT controllers.
3. According to FMP’s command, the 5G network periodically trigger the ambient IoT controllers to be activated. After the ambient IoT controllers have been activated, they receive the operation information via 5G network. The operation information includes e.g. the period to switch on and switch off the irrigation equipment, the period to switch on and switch off the pesticide spraying equipment, the amount of sprayed pesticide in each time, the spraying direction of each pesticide spraying equipment, the period to report the status information etc.
4. After receiving the operation information from the 5G network, the ambient IoT controllers can control the corresponding pesticide spraying and irrigation equipment accordingly, and report the operation status information to the FMP via the 5G network. The status information can include the feedback information about whether to receive the operation information and to operate successfully, and can include the current status of the controlled pesticide spraying and irrigation equipment). In the configured switch off period, the ambient IoT controllers can keep inactive to save the power.
5. The FMP continuously collects the sensing results from the sensors in the farmland. When the FMP observes that the farmland condition varies, the FMP decides to update the operation of the pesticide spraying and irrigation equipment, e.g., change to another set of pesticide spraying and irrigation equipment, change the switch on period, adjust the direction of the pesticide spraying equipment etc.
6. Then the FMP can ask the 5G network to periodically trigger the corresponding new ambient IoT controllers associated with the updated pesticide spraying and irrigation equipment and begin new operation.
7. Additionally, if there is an emergency order from FMP, e.g. high temperature warning to trigger the irrigation operation at once, the message need to be delivered with as short the latency as possible.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.30.4 Post-conditions
|
The ambient IoT controller can periodically activated and control the pesticide spraying and irrigation equipment accordingly.
The on-demand control of all the pesticide spraying and irrigation equipment can be realized to adapt the variation of farmland condition, then the crops in the farmland can grow normally and the yield of crops can be improved.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.30.5 Existing features partly or fully covering the use case functionality
|
None.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
5.30.6 Potential New Requirements needed to support the use case
|
[P.R.5.30.6-001] The 5G system shall provide means for a trusted third-party to trigger an ambient IoT device or group of ambient IoT devices to communicate periodically.
[P.R.5.30.6-002] The 5G system shall be able to provide ambient IoT service with following KPIs：
Table 5.30.6-1: KPI Table of Ambient IoT controller in smart agriculture
Scenario
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Ambient IoT controller in smart agriculture
Several seconds
99%
N/A
NA
128bit (DL)
(note1)
NA
500m
outdoors
40,000m2
to 4,000,000m2
(note 2)
Static
NA
NA
NA
NA
NOTE 1: this size refers to the payload size of the control information sent by the 5G network to the ambient IoT controller.
NOTE 2: This is typical outdoor farmland size range in China.
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
6 Traffic Scenarios
|
6.1 Traffic scenario on flower auction
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
6.1.1 Description
|
In the Netherlands, there is extensive logistics industry for flowers and vegetables. A specific case are the auctions where flowers from all over the world are brought in by the growers, then auctioned and subsequently distributed to buyers all over the world.
Flowers are transported on four-wheel containers that can be rented and are that used throughout the logistic chain. These containers are now equipped with a RFID tag. It would be beneficial if Ambient IoT tags could be used. RFID tags are scanned when containers with flowers arrive or leave the auction; tracking and tracing with Ambient IoT could get regular reports from all containers anywhere at the auction.
Figure 6.1.1-1: Logistics at a flower auction
Shipments of flowers can be tracked and traced based on the containers they are on. This is of interest for growers, buyers and the auction. There is also logistics of empty containers, where also the company that owns the containers can benefit from Ambient IoT. Finally, the auction has an interest in managing its space. Companies that own or rent containers are charged for leaving containers on the auction grounds overnight.
Communication service availability is important. Tracking and tracing is mainly done to find out where things have gone wrong in the logistics, e.g., missing containers. If the communication from tags is not significantly more reliable than the logistics itself, then tracking and tracing does not provide a benefit.
Some numbers:
- There are multiple flower auctions in The Netherlands.
- The size of the flower auction location in Aalsmeer is 1 732 769 m2.
- 44 million flowers are auctioned per day
|
93a47931cc679002202cfe56afd8b056
|
22.840
|
6.1.2 Assumptions
|
We assume every four wheeled container is equipped with a tag in the form of an Ambient IoT device.
Figure 6.1.2-1: Container with flowers (Photo: Container Centralen)
Density of containers can be estimated based on the dimensions of the containers. A container is (lxwxh) 1350 mm x 565 mm x 1900m. Packing these containers closely together gives a density of 740 x 1770 = 1,3 million containers per km2.
Figure 6.1.2-2: Density of flower containers (Photo: Royal FloraHolland)
Ceiling in the flower auction is at 9 meters. We assume that base stations are attached to the ceiling. Number of base stations that is needed to cover the flower auction is dependent on the communication range and on the number of devices per base station. Here we assume a base station spacing of one base station for every 50 m x 50 m of ceiling. This gives a maximum range of approx. 35 meters from ceiling to container. The number of containers in that 50 m x 50 m area is approximately 3000.
The assumption is that the Ambient IoT devices are woken up and triggered for communication on demand by the 5G network, where e.g., the flower auction or a flower grower can decide when to wake up and trigger the Ambient IoT devices for communication. When woken up and triggered the Ambient IoT devices respond by transmitting information, e.g., their identity numbers, to the network.
The flower auction can decide in which parts of the flower auction the Ambient IoT devices are woken up. This can be done by e.g. only providing the wake up via some of the base stations. The flower auction can also decide to trigger only part of the Ambient IoT devices.
Assumption is that an identity can be provided within 96 bits (is EPC length used for identification).
Assumption is that probability of errors in logistics handling (e.g., a container is left behind) is <1%. A communication service availability of 99,99% would imply that the chance that communication for tracking a container is approximately 2 orders of magnitude better than the logistics handling reliability.
There is no strict latency requirement when large amounts of containers are triggered. A latency in the order of 10 seconds is acceptable.
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22.840
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6.1.3 Potential Functional Requirements
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None identified.
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22.840
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6.1.4 Potential Key Performance Requirements
|
[PR 6.1-001] The 5G system shall be able to provide Ambient IoT service with the following KPIs:
Table 6.1.4-1: KPIs for Flower Auction scenario
Scenario
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Container logistics in a flower auction
<10 s
99,99%
(note 1)
NA
<1 kbit/s
(note 3)
96 bits
(note 2)
< 1,3Million/km2 (note 4)
35 m
Indoors
1 700 000 m2
(note 5)
NA
NA
NA
NA
NA
NOTE 1: Chance of communication service unavailability needs to be significantly lower than chance of errors in logistics handling. This communication service availability applies at application level, the communication service availability at radio level can be different.
NOTE 2: Only an identifier for the tag is sent (Electronic Product Code (EPC) lengths used for identification is 96 bits).
NOTE 3: This value is calculated as the instant data rate for transmitting 96 bits within 100 ms time period. The need for data transmission is infrequent.
NOTE 4: Based on closely packing containers.
NOTE 5: Size of the flower auction location in Aalsmeer.
6.2 Traffic Scenario on cow stable
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6.2.1 Description
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In the dairy industry, there is an increase in the scale of farms. Whilst the number of farms decreases the number of cows per farm increases. The largest dairy farms in the US have over 15000 cows. A more typical dairy farm has around 200 cows.
Figure 6.2.1-1: A typical dairy farm
Because of the increase of the number of cows, there is a lot of automation in dairy farming. For example cows are milked using a milk robot, and manure is removed with robots.
Figure 6.2.1-2: Dairy farm automation with milk robot (left) and manure robot (right)
In order to identify individual cows (e.g. in the milk robot), the cows have tags. These tags also perform measurements of the cows vital signs (e.g. temperature, movement) to e.g. determine the fertility cycle of the cow and monitor health.
Figure 6.2.1-3: Cow sensor (sensor is just behind the ear)
It is also possible to create a cow sensor in the form of a capsule (or bolus) that can be swallowed by cows and remains in the first of the cow’s four stomachs. The advantage of this is that the sensor is smaller, providing more freedom to the cow, and that more internal data from within the cow can be measured.
Many cows spend their whole life in the stable. However, data in the Netherlands shows that more than 80% of cows also can graze outside in the meadows around the farm.
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6.2.2 Assumptions
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We assume a typical farm with 200 cows. Every cow is equipped with a sensor.
The dimensions of the stable vary with the interior design of the stable, but 30 m x 60 m is a realistic dimension. For simplicity we assume that cows can go everywhere within the stable. The assumption is that there is an indoor base station on the ceiling in the middle of the stable.
The sensors provide measurement data every hour, but can also provide immediate alerts in case the cow is in distress (e.g. during calving). Assumption is that each measurement (identifier, plus 4 measured values) can be provided within 500 bits.
The cow sensor can harvest energy from the movement and temperature of the cow. A continuous power scenario is assumed where the sensor continuously has power available.
Maximum range for the sensor to base station is approximately 35 meters. Note that when the cows are outside, the distance to outside base stations can be much larger (kilometres). It is not assumed that the sensors can communicate over such long range. Even though the sensor may detect the base station, it should not attempt to connect to the base station when it is out of range.
A typical size of a capsule / bolus for cows is approximately 30 mm by 100 mm. For smaller ruminants, such as sheep or goats, this size is not suitable and smaller capsules will have to be made.
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6.2.3 Potential Functional Requirements
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Ambient IoT devices shall not transmit (creating interference) when the network is outside communication range.
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22.840
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6.2.4 Potential Key Performance Requirements
|
[PR 6.1-001] The 5G system shall be able to provide Ambient IoT service with the following KPIs:
Table 6.2.4-1: KPIs for dairy stable scenario
Scenario
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Cows in dairy stable
1 s
(note 4)
99,9%
NA
< 0.5 kbit/s (note 2)
500 bits
(note 1)
< 1 /km2 (note 3)
35 m
Indoors
1 800m2
(note 5)
NA
NA
NA
NA
NA
NOTE 1: An identifier and four measurement values (e.g. temperature, movement, …).
NOTE 2: This value is calculated as the instant data rate for transmitting 500 bits within 1s transmission time. The need for data transmission is infrequent (e.g. once per hour).
NOTE 3: 200 cows in the stable
NOTE 4: There is no great urgency with cow monitoring that requires a lower latency.
NOTE 5: Assuming a 30 m x 60 m stable.
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6.3 Traffic Scenario on Electronic Shelf Label
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6.3.1 Description
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Recently, a growing number of electronic shelf labels (ESLs) have been deployed in retail industry. The technology has freed the retail stores from labour-intensive paper label replacement work, where a typical grocery store needs to replace about 10,000 price tags per week [78]. The ESLs also help retailers and manufactures to use real-time inventory data to optimize inventory and automate shelf refilling. More importantly, the ESLs and smart shelves system enable retailers to build a better, friendly, and smarter shopping experience to improve shopper engagement. For example, some retailers have integrated electronic shelf label with smart shopping cart to bring better shopper engagement by guiding customers in the store to their shopping items quickly and reduce customer line-up time to zero [79]. Additionally, data collected from ESL system provide good insights on consumer shopping behaviours, which allows retailers to implement a dynamic pricing strategy.
The ESL device is usually equipped with battery, RF module, microcontroller, plastic housing, electronic paper display. Although, most recent electronic paper technologies allow ESL units to draw minimum to zero energy from battery to keep static text and images [80], from time to time, battery replacement still make environment-friendly concern and maintenance cost two pain points for most retailers when the mass deployment of these labels becomes mainstream.
Figure 6.3.1-1: Electronic Shelf Labels deployed in a retail store
In the coming years, Ambient-powered ESL is going to gain momentum in the market. It will dramatically reduce the cost of ESLs. And battery change, from both environment-friendly and labour-saving perspectives, is no longer a concern for retail stores. The Ambient-powered ESL helps to automate several store routines, e.g. price tag change, stock refilling, dynamic price adjustment, customer behaviour analysis, etc. Integrated with a rich set of 5G features, the Ambient-powered IoT ESL is potentially going to drive the next wave of retail industry ESL system upgrade.
In addition to benefits gained from battery-less deployment, thanks to the 5G Ambient IoT system in the retail store, now the store manager does not need to worry about the long-lasting issue where some items’ paper price labels do not match advertised flyer prices. He can just feed the store management portal with the same source pricing data used for weekly flyer promotion. The Ambient IoT store management system will then automatically update the affectedly Ambient IoT price tags based on the same pricing strategy as the store flyer. This process can be done remotely without presence of store clerks. It usually completes in just a few minutes. Previously, to get similar task done, the process might require four night-shift clerks on-site to complete for a large retail store.
In another scenario, the Ambient IoT ESL unit, equipped with temperature sensor, could be used to monitor anomaly in the frozen food area, and report to the store management platform periodically. An anomaly alert then triggers the store management platform to page store clerks to check the status of the freezer. On the smart shelf, the Ambient IoT system could report that items on the self are now out of stock. Store clerks will then be notified to refill the shelf in a timely manner.
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22.840
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6.3.2 Assumptions
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We assume a retailing giant starts to deploy 5G network to provide Ambient IoT communication service for ESL system in the store. The retail store, average 15,800 square meters, offer more than 100,000 different items. The ESL devices are installed on the 6-shelf racks with dimension of 1.8mx1.2mx0.5m. In addition to the Ambient IoT label, some items on the shelf are also attached with trackable tags. Averaging over effective display area in the store, it is estimated that the device density is less than 1.5 million/km2. It is also noted that in certain area of the retail store where small items are stocked as illustrated in Figure 6.3.2-1, the shelf could accommodate about 90 labels per square meter. In the other example illustrated in Figure 6.3.2.1-1, the device density of ESLs equipped with temperature and humidity sensor inside refrigerators is estimated to be less than 10 per 100 square meters.
Fig. 6.3.2-1: display shelfs in a retailing super market
In an electronic shelf label (ESL) system, product pricing and descriptions on the labels can be updated upon request, without applying a fixed transfer interval. However, the temperature and humidity conditions of the shelf or refrigerators are typically reported at predetermined intervals via sensors integrated into the ESL. These intervals are commonly determined in accordance with food safety guidelines that vary across regions and organizations. For example, the United States Department of Agriculture (USDA) recommends that food should not be left outside of refrigeration for more than two hours, and if the temperature exceeds 32°C, this time limit is reduced to one hour [90]. Meanwhile, the Australian Food and Grocery Council (AFGC) stipulates that chilled food should not be left outside of refrigeration for more than 20 minutes [91]. Based on these industry guidelines, we propose employing a transfer interval key performance indicator (KPI) of “20 minutes to 2 hours” for this particular traffic scenario. These transfer intervals can be provisioned into Ambient IoT devices or the management system by the Ambient IoT service providers or 5G operators.
In the other assumption, we assume the Ambient IoT system has a communication service availability of 99%. This implies there might be 1% Ambient IoT devices could not be reachable even after multiple retransmissions. For a retail store with 2,000 different items to update price tag, this means about 20 ESL price tags need to be updated with human intervention. This workload is acceptable for such a store.
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22.840
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6.3.3 Potential Key Performance Requirements
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[PR.6.3.3-1] The 5G system shall be able to support Ambient IoT devices with the following KPIs
Table 6.3.3.1 – Potential key performance requirements for Electronic Shelf Label use case
Scenario
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Electronic Shelf Label
1s
99%
NA
0.8kbit/s DL (note 1)
100 Bytes (note 2)
less than 1.5 million/km2 (inventory), less than 0.1 million/km2 (temperature sensor)
50m indoors
15,800 square meters
stationary
20 minutes to 2 hours [Note 3]
NA
NA
NA
Note 1: the user experience data rate is estimated based on transmission of 100 Bytes within 1 second.
Note 2: the message payload size is calculated based on the capacity of 50 Unicode characters for item description and pricing on the electronic shelf label.
Note 3: These are the typical intervals where electronic shelf labels equipped with sensors report temperature and humidity conditions of the shelf or refrigerators in accordance with food safety guidelines that vary across regions and organizations.
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7 Consolidated potential requirements and KPIs
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7.1 Consolidated potential requirements
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Mapping table is used per each subclause for consolidated potential requirements.
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22.840
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7.1.1 Communication aspects of Ambient IoT devices
|
Table 7.1.1-1 Consolidated Requirements for communication aspects of Ambient IoT devices
CPR #
Consolidated Potential Requirement
Original PR #
Comment
CPR 7.1.1-1
The 5G system shall be able to support mechanisms to communicate:
• between an Ambient IoT device and the 5G network using Ambient IoT direct network communication or Ambient IoT indirect network communication.
• between an Ambient IoT device and Ambient IoT capable UE using Ambient IoT device to UE communication.
PR.5.2.6-001
PR.5.6.6-001
PR.5.11.6-001
PR.5.12.6-002
PR.5.13.6-001
PR.5.1.6-001
PR.5.4.6-001
PR.5.2.6-002
PR.5.12.6-002
PR.5.8.6-003
PR.5.27-004
PR.5.13.6-004
PR.5.3.6-001
PR.5.22.6-1,
PR5.23.6-1,
PR.5.24.6-1
PR.5.26.6-001
CPR 7.1.1-1 is updated to include communication modes.
Note 1: This requirement applies to the 5G network and only UEs with the capability to communicate with an Ambient IoT device.
Note 2: Examples of the communication between 5G network/Ambient IoT capable UE and Ambient IoT devices can include periodic sensor reporting or network-initiated inventory.
CPR 7.1.1-2
The 5G system shall be able to support 5G network or an Ambient IoT capable UE to communicate with a group of Ambient IoT devices simultaneously.
PR 5.2.6-001
PR.5.6.6-001
PR.5.11.6-001
PR.5.12.6-002
PR.5.13.6-001
PR.5.1.6-001
PR.5.4.6-001
PR.5.2.6-002
PR.5.12.6-002
PR.5.8.6-003
PR.5.27-004
PR.5.13.6-004
PR.5.3.6-001
PR.5.22.6-1,
PR.5.23.6-1,
PR.5.24.6-1
PR.5.26.6-001
CPR 7.1.1-3
The 5G network shall support a mechanism to authorize an Ambient IoT capable UE to communicate with an Ambient IoT device.
PR.5.8.6-002
PR.5.12.6-001
PR.5.14.6-001
PR.5.21.6-003
PR.5.21.6-001
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22.840
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7.1.2 Positioning/location of Ambient IoT devices
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Table 7.1.2-1 Consolidated Requirements for positioning/location of Ambient IoT devices
CPR #
Consolidated Potential Requirement
Original PR #
Comment
CPR 7.1.2-1
The 5G system shall support location services for Ambient IoT devices (e.g., to locate Ambient IoT devices using absolute or relative positioning methods)
Note: The intention is not to use Ambient IoT devices to locate other Ambient IoT devices.
PR.5.9.6-002
PR.5.12.6-004
PR.5.2.6-004
PR.5.8.6-001
PR 5.10.6-001
PR.5.21.6-002
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22.840
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7.1.3 Management of Ambient IoT devices
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Table 7.1.3-1 Consolidated Requirements for management of Ambient IoT devices
CPR #
Consolidated Potential Requirement
Original PR #
Comment
CPR 7.1.3-1
The 5G network shall support suitable management mechanisms for an Ambient IoT device or a group of Ambient IoT devices.
PR.5.1.6-005
PR.5.16.6-003
PR.5.17.6-001
CPR 7.1.3-2
The 5G system shall support a mechanism to:
- disable the capability to transmit RF signals for one or more Ambient IoT device that is / are currently able to transmit RF signals
- enable the capability to transmit RF signals for one or more Ambient IoT device that is / are currently disabled to transmit RF signals
CPR 7.1.3-3
Based on operator policy, the 5G system shall provide a suitable mechanism to permanently disable the capability of an Ambient IoT device or a group of Ambient IoT devices to transmit RF signals.
CPR-7.1.3-4
Subject to operator policy and regulatory requirements, the 5G system shall support suitable mechanisms for the Ambient IoT device to move between one or more networks and countries.
PR.5.27-001
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7.1.4 Collected information and network capability exposure
|
Table 7.1.4-1 Consolidated Requirements for “collected information” and network capability exposure
CPR #
Consolidated Potential Requirement
Original PR #
Comment
CPR 7.1.4-1
Subject to user consent, operator policy and 3rd party request, the 5G system shall be able to get information from Ambient IoT devices (e.g. sensor data) and provide it to a trusted 3rd party via the 5G network.
PR.5.1.6-002
PR.5.12.6-003
PR.5.13.6-005 PR.5.14.6-003
PR.5.16.6-004
PR.5.18.6-1 PR.5.21.6-004
PR 5.2.6-003
CPR 7.1.4-2
Subject to user consent, operator’s policy and 3rd party request, the 5G system shall provide information about an Ambient IoT device or a group of Ambient IoT devices (e.g. position) to the trusted 3rd party via the 5G network.
CPR 7.1.4-3
The 5G system shall enable an authorized 3rd party to instruct the 5G network to trigger a group of Ambient IoT devices in a specific area and which action the Ambient IoT devices need to perform when triggered (e.g. send ID, receive further information, send measurement value).
PR.5.3.6-003
PR.5.19.6-001
PR.5.27-003
CPR 7.1.4-4
The 5G system shall provide suitable mechanisms to support communication between a trusted and authorized 3rd party and an Ambient IoT device or group of Ambient devices.
PR.5.20.6-001
PR.5.22.6-2,
PR.5.23.6-2,
PR.5.24.6-2
PR.5.30.6-001
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7.1.5 Charging
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Table 7.1.5-1 Consolidated Requirements for charging
CPR #
Consolidated Potential Requirement
Original PR #
Comment
CPR. 7.1.5-1
The 5G system shall be able to collect charging information in a suitable way for using Ambient IoT services on per Ambient IoT device basis or a group of Ambient IoT devices (e.g., total number of communications per charging period).
PR.5.3.6-004
PR.5.3.6-005
PR.5.22.6-3,
PR.5.23.6-3,
PR.5.24.6-3
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7.1.6 Security and privacy
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Table 7.1.6-1 Consolidated Requirements for security and privacy
CPR #
Consolidated Potential Requirement
Original PR #
Comment
CPR 7.1.6-1
The 5G system shall be able to provide a mechanism to protect the privacy of information (e.g., location and identity) exchanged during communication between an Ambient IoT device and the 5G network or an Ambient IoT capable UE.
PR.5.1.6-003
PR 5.3.6-002 PR.5.6-002 PR.5.13.6-002 PR.5.21.6-005 PR.5.8.6-004
PR.5.1.6-004
PR.5.8.6-005
PR.5.12.6-006 PR.5.13.6-003
PR.5.14.6-005
PR.5.16.6-001 PR.5.20.6-002
CPR 7.1.6-2
The 5G system shall enable security protection suitable for Ambient IoT, without compromising overall 5G security protection.
PR.5.1.6-003
PR.5.3.6-002 PR.5.6-002 PR.5.13.6-002 PR.5.21.6-005 PR.5.8.6-004
PR.5.1.6-004
PR.5.8.6-005
PR.5.12.6-006 PR.5.13.6-003
PR.5.14.6-005
PR 5.16.6-001 PR.5.20.6-002
CPR 7.1.6-3
Based on subscription and operator policies, the 5G system shall authorize an Ambient IoT capable UE to communicate with a specific Ambient IoT device.
PR.5.12.6-005
PR.5.14.6-004
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7.2 Consolidated potential KPIs
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7.2.1 KPIs for inventory
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Table 7.2.1-1 KPIs for inventory
Scenarios
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range (Note 1)
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Remark
inventory or asset management
Typically, seconds level
99%
NA
<2 Kbit/s
96/256 bits
<1,5 Million/km²
indoor only
(Note 2)
30~50m indoor,
200m~400m outdoor
1-10km²
3~10km/h
NA
NA
NA
3 m indoor,
cell-level outdoor
UC#5.1, UC#5.2, UC#5.5, UC#5.7, UC#5.16
TS#6.1
NOTE 1: The communication range is the communication distance between the ambient IoT device and the 5G network or between the ambient IoT device and an ambient IoT capable UE.
NOTE 2: The device density is much lower outdoors as only a subset of assets (e.g. stored indoors) will be in transit, and a much larger area for transit applies.
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7.2.2 KPI for sensor data collection
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Table 7.2.2-1 KPIs for sensor data collection
Deployment
Scenarios
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range
(Note 1)
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Remark
Indoor
Room envirionment monitoring (e.g. domicile, machinery)
20-30 s
99 %
NA
<1 kbit/s
< 100 bits
1.5
10-30m
NA
Stationary
NA
NA
NA
NA
UC#5.6, UC#5.13
Indoor agriculture and husbandry
>10 s
99.9%
NA
<1 kbit/s
Typically,
< 1000 bits
1 per m²
30 - 200 m
6000 m²~30,000m²
Quasi-stationary
15 minutes to half an hour
NA
NA
NA
UC#5.20 UC#5.23
TS#6.2
UC#5.18
Outdoor
Smart grid
1 s
99%
NA
< 1kbit/s
Typically,
< 100 bytes
< 10,000 /km²
Typically 50-200 meters
[several km² up to 100 000 km²]
Stationary
5-15 min
NA
NA
several 10 m
UC#5.3
Outdoor husbandry and logistics
Typically, > tens of seconds
99%
NA
<500 bit/s
Typically,
[< 100 bytes]
<5200 devices / km²
[300 m - 500 m]
430000 m²
Up to 3 km/h
15 min
NA
NA
NA
UC#5.22, UC#5.19
Smart city
10 s - 30 s
99%
NA
<1 kbit/s
Typically,
< 100 bytes
<1000 devices / km²
300 m - 500 m
City wide including rural areas
Stationary
15 min
NA
NA
NA
UC#5.24, UC#5.25
NOTE 1: The communication range is the communication distance between the ambient IoT device and the 5G network or between the ambient IoT device and an ambient IoT capable UE.
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7.2.3 KPI for tracking
|
Table 7.2.3-1 KPIs for tracking
Deployment
Scenarios
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range
(Note 1)
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Remark
Indoor
Indoor tracking
1s
99.9%
NA
<1 kbit/s
<1k bits
25/100 m²
10m indoor
200 m²
up to 3km/h
1 per hour
1s
90%
1-3 m, 90% availability
UC#5.8
UC#5.10
UC#5.12, UC#5.14
UC#5.21
Outdoor
Outdoor tracking
1s
99.9%
NA
<1 kbit/s
<1 kbits
<10 per 100 m²
500m
Up to the whole PLMN
up to 10 km/h
1 per hour
1 s
95%
several 10m
UC#5.8
UC#5.9
UC5.12
NOTE 1: The communication range is the communication distance between the ambient IoT device and the 5G network or between the ambient IoT device and an ambient IoT capable UE.
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22.840
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7.2.4 KPI for actuator control
|
Table 7.2.4-1 KPIs for actuator control
Deployment
Scenarios
Max. allowed end-to-end latency
Communication Service Availability
Reliability
User-experienced data rate
Message Size
Device density
Communication Range
(Note 1)
Service area dimension
Device speed
Transfer interval
Positioning service latency
Positioning service availability
Positioning Accuracy
Remark
Indoor
Indoor actuator control
Several seconds
99%
NA
2 kbit/s
<100 Bytes
less than 1.5 million/km²
50m indoors
<250 m² for home, and
15,800 square meters for supermarket
stationary
20 minutes to 2 hours
NA
NA
3 m to 5 m indoor
UC#5.11UC#5.26TS#6.3
Outdoor
Outdoor actuator control for large coverage
Several seconds
99%
N/A
NA
128bit (DL)
NA
[500]m
outdoors
40,000~4,000,000m2
Static
NA
NA
NA
NA
UC#5.30
Outdoor actuator control for medium coverage
Several seconds
99%
NA
<2 kbit/s
<200 bits
<20per 100 m²
200 m
City wide including rural areas
Static
NA
NA
NA
NA
UC#5.26UC#11
NOTE 1: The communication range is the communication distance between the ambient IoT device and the 5G network or between the ambient IoT device and an ambient IoT capable UE.
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8 Conclusion and recommendations
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This technical report identifies use cases and potential new requirements related to ambient IoT. The resulting service requirements have been consolidated in clause 7. It is recommended to consider the consolidated requirements identified in this TR for the subsequent normative work. Annex A: Ambient IoT availability scenarios The Ambient IoT devices foresee to have different kind of communication pattern that could be dependent on power available for communication e.g. harvesting and the availability of storage capability or the specific use case. Following pattern are foreseen: - Normal operation: In this scenario, Ambient IoT devices have power available continuously or at least for signicant amounts of time, either because there is continuous power harvesting or possibly in combination with limited energy storage (e.g. in a capacitor) to overcome momentary variations in power harvesting. The main effect of this scenario is that the processor and communications module in the Ambient IoT device can be continuously active. The communications module can listen to network at regular intervals to determine if there is mobile terminated traffic (e.g. trigger messages) and can transmit data when relevant. - Device triggered operation: In this scenario, devices have power available only intermittently. The main effect of this scenario is that the Ambient IoT device can only be active for the short periods of time. And it is the Ambient IoT device that decides when to communicate with the network. It is possible that the Ambient IoT device is not able to listen to the network for mobile terminated traffic for very long periods of time. This has an impact on service aspects such as provisioning. - On demand operation: in this scenario 5G network will wake up and trigger the device to communicate in a relevant manner. This scenario only considers the network to trigger the communication and the Ambient IoT device cannot determine when to communicate. Waking up of the Ambient IoT device can be combined with a trigger to perform a specific action (e.g. do measurement) or to communicate (e.g. send an identifier). Waking up can also imply that the Ambient IoT device starts listening to the network for further instructions. These scenarios are not intended as definitions for device categories. The purpose is to enable discussion of service aspects that are associated with different scenarios. Annex B: Ambient power and energy storage B.1 Typical ambient power For ambient IoT devices, energy can be harvested from different types of ambient power sources. Some examples of which could be ambient power includes radio waves, solar energy/light, thermal energy and mechanical vibration etc. RF Energy RF-based energy can be harvested from radio waves ranging from 3 kHz to 300 GHz using a single-stage or multistage converter (i.e., rectifier circuit, as shown in Figure B-1). The amount of power that can be harvested depends on the source power, antenna gain, and the distance from the RF source. Ambient RF energy has a relatively low energy density, e.g., from several microwatts to tens of microwatts. Figure B.1-1: rectifier circuit For RF energy harvesting Based on the current state of art, the minimum RF power can be harvested is around -30dB 00. The conversion efficiency for RF Energy is listed in the table below. Table B.1-1: Conversion efficiency for RF Energy 0 Efficiency（%） Input power（dBm） Center frequency（MHz） Reflector unit 1.2 -14 950 0.3-μm CMOS convertor 5.1 -14.1 920 0.18-μm CMOS convertor 10 -22.6 906 0.25-μm CMOS convertor 11 -14 915 90-μm CMOS convertor 12.8 -19.5 900 0.18-μm CMOS , CoSi2 - Si Schottky 13 -14.7 900 0.35-μm CMOS convertor 16.4 -9 963 0.35-μm COMS convertor 18 -19 869 0.5-μm CMOS convertor 26.5 -11.1 900 0.18-μm CMOS convertor 36.6 -6 963 0.35-μm CMOS convertor 47 -8 915 0.18-μm CMOS convertor 49 -1 900 Skyworks SMS7630 Si Schottky The main advantage of RF-based energy harvesting is its availability in deployed environments and the fact that RF power is controllable (e.g., power can be sent by a transmitter on demand or periodically). Potential applications include logistics/warehouse, manufacturing, smart homes, health monitoring, and environmental monitoring etc. Solar Energy/Light Solar power/light can be transformed into electrical power using photovoltaic cells and it uses photovoltaic effect for energy harvesting with conversion efficiency of 10-40% 0. For the outdoor case, solar energy is one of the most common ambient power, it can supply inexhaustible clean energy and has high power density of up to 100 mW/cm2 0. Figure B.1-2: The equivalent electrical circuit of a single diode solar PV cell [21] Solar power is unstable, inconsistent, and intermittent. It is highly dependent on the atmospheric condition, surrounding obstructions, etc. It is available during daytime but inefficient on a cloudy day or during the night. Solar energy harvesting can be mainly used for outdoor environmental monitoring, agriculture, husbandry, transportation, etc. For the indoor cases, light from the lighting equipment can be used. Although the power density is lower than solar, e.g., 100uw/cm2, it is much stable and controllable. Energy harvested from light can be used for manufacturing, indoor environmental monitoring etc. Thermal Energy Thermal energy is another ambient power source that are available for lots of use cases. Electrical power is directly generated by exploiting the temperature difference in thermoelectric devices taking advantage of thermoelectric effects, such as the Seebeck effect or the Thomson effect. Thermoelectric generators have low efficiency (only about 5–6%) 0. The power density is 25~1000uw/cm2 depending the environment condition. Figure B.1-3: Seebeck effect Although with low conversion efficiency, thermal energy can be used in many outdoor applications or indoor cases as long as temperature difference or temperature fluctuation can be expected in the environment. For example, outdoor environmental monitoring, smart grid, agriculture, husbandry etc. Mechanical Vibration The piezoelectric effect generates electrical voltages or currents from mechanical strains, such as vibration or deformation. Typical piezoelectric-based energy harvesters keep creating power when there is a continuous mechanical motion, such as acoustic noises and wind, or they sporadically generate power for intermittent strains, such as human motion (walking, clicking a button, etc.). The volume of the piezoelectric power generators is relatively small and typical output power density values of usual piezoelectric materials are around 250 μW/cm3 but they can create more power when a motion or deformation is intense 0Error! Reference source not found.. Figure B.1-4: Piezoelectric energy harvesting generator [25] B.2 Energy storage From the discussion above, it can be seen that kinds of ambient power have the following characteristics: • For typical ambient power, it can be observed the power harvested is very limited, e.g. from 1uW to 100mW (per cm2/cm3). • For some ambient power from artificial power source (e.g., light, RF waves), the power can be stable and constant. But for some other kind of ambient power such as solar, heat or vibration, the ambient power will be unstable (intermittent, not constant). It is impossible to use the ambient power as a direct power source for electronic devices. Therefore, Energy storage element is needed, at least for some ambient IoT devices due to the following reasons: • The energy storage element is able to stabilize and control the power output, smooth the fluctuation. • It is able to collect the weak harvested power (e.g., in the level of micro Ampere or even nano Ampere) and provide the required higher peak discharge current (e.g., in the level of tens of micro ampere to hundreds of micro ampere) for the ambient IoT devices. • Therefore, it makes it possible to use more kinds of ambient power sources for ambient IoT by using the energy storage element. Note: It is still necessary to have no power storage for some types of ambient IoT devices (e.g. using energy from radio waves). Capacitor can be considered as the basic energy storage elements for ambient IoT devices. Capacitor have limited power perseverance time and storage capacity, which can restrict the ambient IoT application. For example, with a fully charged capacitor of 24uF, it can drive the ambient IoT devices for 3.6k bits communication (1.5V, 10uA and 1kbit/s are assumed). ◦ 24uF*1.5V= 36uC = 36 uAs The communication is depending on the power consumption. Capacitor could be used in case power source are stable and constant. The printed solid-state battery can be considered as an additional power storage with similar durability and higher capacity. With a solid-state battery of 1uAh@1.5V as example, it can drive the ambient IoT devices for even 360k bits communication (1.5V and 10uA). Annex C: Considerations when choosing harvesting source When using energy harvesting as the main source of energy for low power devices there are a lot of design parameters to understand. The harvesting sources needs to match the total energy consumption of the Ambioent IoT device. The available energy needs to balance the energy demand for the communication, the computation and other present elements like sensors. Other factors that matters are if it is possible to harvest continously or only part of the time, e.g. if solar cells are used as harvesting method it is only possible to harvest during day time. Below there is a schematic picture of the different parts of the system for an Ambient IoT device. Not all parts are mandatory in an Ambient IoT device, for instance sensors and energy storage are not always present. The power management will ensure that the correct voltage will be available for the sensor, communication and compute parts. Ambient IoT devices can be both with and without some kind of energy storage and there are many types of storage components, from capacitors, super capacitors to more battery types of storages. Figure C-1 Example of parts in an Ambient IOT device The following example assumes that some storage capability is available in the device Below shows two examples with same type of harvesting but with different length of the active time periods that the sensor/compute/communication system needs to be active. In the first example, the Ambient IoT device transmits in shorter bursts and with a higher power compared to second example. In the second example the time for the sensor/compute/communication is active longer. This would mean that, given everything else is equal, the available power for the active period in example two is lower. Figure C-2 Example where the active period for the device is relative short Figure C- 3 Example where the active period for the device is relative long There is therefore not a simple formula to determine the available power for the sensor/compute/communication functionsfrom the characteristics of the energy harvesting method. Annex D: Change history Change history Date Meeting TDoc CR Rev Cat Subject/Comment New version 2022.05 SA1#98e S1-221254 - - - Initial Skeleton 0.0.0 2022.05 SA1#98e Inclusion of: S1-221255; S1-221256; S1-221257; S1-221258; S1-221259; S1-221260; S1-221261; S1-221262 0.1.0 2022.09 SA1#99e - - - Add agreed use cases, power scenarios etc. Inclusion of: S1-222362; S1-222363; S1-222364; S1-222365; S1-222366; S1-222367; S1-222368; S1-222369; S1-222370; S1-222371; S1-222372; S1-222373; S1-222374; S1-222375; S1-222376; S1-222377; S1-222378; S1-222379; S1-222380; S1-222122 0.2.0 2022.11 SA1#100 - - - Update of names, formats. Corrections. Inclusion of: S1-223207 0.2.1 2022.11 SA1#100 - - - Update of requirements, more use cases, annex and others. The KPI tables are updated in unified format base on S1-223799. Inclusion of: S1-223207; S1-223321; S1-223698; S1-223545; S1-223546; S1-223356; S1-223357; S1-223360; S1-223361; S1-223480; S1-223481; S1-223363; S1-223364; S1-223583; S1-223556; S1-223582; S1-223235; S1-223571; S1-223700; S1-223573; S1-223562; S1-223702; S1-223703; S1-223704; S1-223705; S1-223555; S1-223706; S1-223707; S1-223708; S1-223229; S1-223699; S1-223166; S1-223737 0.3.0 2023.02 SA1#101 - - - New use cases, updates of the existing use cases, clear up of FFS etc Inclusion of: S1-230654; S1-230655; S1-230757; S1-230758; S1-230662; S1-230663; S1-230526; S1-230123; S1-230759; S1-230609; S1-230610; S1-230760; S1-230761; S1-230231; S1-230613; S1-230614; S1-230615; S1-230238; S1-230616; S1-230621; S1-230665; S1-230763; S1-230619; S1-230800; S1-230765 1.1.0 2023.05 SA1#102 - - - updates of the existing use cases, clear up of FFS/Editor note etc Inclusion of: S1-231400; S1-231293; S1-231401; S1-231292; S1-231403; S1-231405; S1-231812; S1-231682; S1-231407; S1-231459; S1-231409; S1-231402; S1-231410; S1-231460; S1-231411; S1-231300; S1-231413; S1-231227; S1-231414; S1-231461; S1-231813; S1-231464 1.2.0 2023.08 SA1#103 - - - updates of the existing use cases, clear up of FFS/Editor note, remove the brackets of KPI value, CPR and KPI consolidation, conclusion etc Inclusion of: S1-232178; S1-232033; S1-232315; S1-232379; S1-232349; S1-232303; S1-232279; S1-232304; S1-232305; S1-232149; S1-232157; S1-232355; S1-232388; S1-232359; S1-232387; S1-232310; S1-232380; S1-232172; S1-232381; S1-232389; S1-232313; S1-232391; S1-232644; S1-232619; S1-232392; S1-232393; S1-232645; S1-232647; S1-232648; S1-232352 1.3.0 2023.09 SA#101 SP-231015 MCC Clean-up for presentation for SA approval 2.0.0 2023.11 SA1#104 Final KPI consolidation etc. Inclusion of: S1-233401; S1-233402; S1-233403; S1-233404 2.1.0 2023.12 SA#102 SP-231404 MCC clean-up for 2nd attempt for SA approval 2.2.0 2023.12 SA#102 - Approved by SA#102 19.0.0
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1 Scope
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The present document specifies the session control protocols needed to support Mission Critical Push To Talk (MCPTT). The present document specifies both on-network and off-network protocols.
Mission critical communication services are services that require preferential handling compared to normal telecommunication services, e.g. in support of police or fire brigade.
The MCPTT service can be used for public safety applications and also for general commercial applications (e.g., utility companies and railways).
The present document is applicable to User Equipment (UE) supporting the MCPTT client functionality, and to application servers supporting the MCPTT server functionality.
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2 References
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The following documents contain provisions which, through reference in this text, constitute provisions of the present document.
- References are either specific (identified by date of publication, edition number, version number, etc.) or non‑specific.
- For a specific reference, subsequent revisions do not apply.
- For a non-specific reference, the latest version applies. In the case of a reference to a 3GPP document (including a GSM document), a non-specific reference implicitly refers to the latest version of that document in the same Release as the present document.
[1] 3GPP TR 21.905: "Vocabulary for 3GPP Specifications".
[2] 3GPP TS 22.179: "Mission Critical Push To Talk (MCPTT) over LTE; Stage 1".
[3] 3GPP TS 23.379: "Functional architecture and information flows to support mission critical communication services; Stage 2".
[4] 3GPP TS 24.229: "IP multimedia call control protocol based on Session Initiation Protocol (SIP) and Session Description Protocol (SDP); Stage 3".
[5] 3GPP TS 24.380: "Mission Critical Push To Talk (MCPTT) floor control Protocol specification".
[6] IETF RFC 3841 (August 2004): "Caller Preferences for the Session Initiation Protocol (SIP)".
[7] IETF RFC 4028 (April 2005): "Session Timers in the Session Initiation Protocol (SIP)".
[8] Void .
[9] IETF RFC 6050 (November 2010): "A Session Initiation Protocol (SIP) Extension for the Identification of Services".
[10] IETF RFC 3550 (July 2003): "RTP: A Transport Protocol for Real-Time Applications".
[11] Void.
[12] IETF RFC 4566 (July 2006): "Session Description Protocol".
[13] IETF RFC 3605 (October 2003): "Real Time Control Protocol (RTCP) attribute in Session Description Protocol (SDP)".
[14] IETF RFC 3325 (November 2002): "Private Extensions to the Session Initiation Protocol (SIP) for Asserted Identity within Trusted Networks".
[15] IETF RFC 5626 (October 2009): "Managing Client-Initiated Connections in the Session Initiation Protocol (SIP)".
[16] IETF RFC 3840 (August 2004): "Indicating User Agent Capabilities in the Session Initiation Protocol (SIP)".
[17] Void.
[18] IETF RFC 5373 (November 2008): "Requesting Answering Modes for the Session Initiation Protocol (SIP)".
[19] Void.
[20] IETF RFC 5366 (October 2008): "Conference Establishment Using Request-Contained Lists in the Session Initiation Protocol (SIP)".
[21] IETF RFC 2046 (November 1996): "Multipurpose Internet Mail Extensions (MIME) Part Two: Media Types".
[22] IETF RFC 4488 (May 2006): "Suppression of Session Initiation Protocol (SIP) REFER Method Implicit Subscription".
[23] IETF RFC 4538 (June 2006): "Request Authorization through Dialog Identification in the Session Initiation Protocol (SIP)".
[24] IETF RFC 3261 (June 2002): "SIP: Session Initiation Protocol".
[25] IETF RFC 3515 (April 2003): "The Session Initiation Protocol (SIP) Refer Method".
[26] IETF RFC 6665 (July 2012): "SIP-Specific Event Notification".
[27] IETF RFC 7647 (September 2015): "Clarifications for the use of REFER with RFC 6665".
[28] 3GPP TS 24.334: "Proximity-services (ProSe) User Equipment (UE) to Proximity-services (ProSe) Function Protocol aspects; Stage 3".
[29] IETF RFC 4412 (February 2006): "Communications Resource Priority for the Session Initiation Protocol (SIP)".
[30] IETF RFC 4575 (August 2006): "A Session Initiation Protocol (SIP) Event Package for Conference State".
[31] 3GPP TS 24.481: "Mission Critical Services (MCS) group management Protocol specification".
[32] IETF RFC 4483 (May 2006): "A Mechanism for Content Indirection in Session Initiation Protocol (SIP) Messages.
[33] IETF RFC 3428 (December 2002): "Session Initiation Protocol (SIP) Extension for Instant Messaging".
[34] IETF RFC 4964 (October 2007): "The P-Answer-State Header Extension to the Session Initiation Protocol for the Open Mobile Alliance Push-to-talk over Cellular".
[35] IETF RFC 7614 (August 2015): "Explicit Subscriptions for the REFER Method".
[36] IETF RFC 5318 (December 2008): "The Session Initiation Protocol (SIP) P-Refused-URI-List Private-Header (P-Header)".
[37] IETF RFC 3903 (October 2004): "Session Initiation Protocol (SIP) Extension for Event State Publication".
[38] IETF RFC 5368 (October 2008): "Referring to Multiple Resources in the Session Initiation Protocol (SIP)".
[39] IETF RFC 5761 (April 2010): "Multiplexing RTP Data and Control Packets on a Single Port".
[40] 3GPP TS 23.003: "Numbering, addressing and identification".
[41] 3GPP TS 23.203: "Policy and charging control architecture".
[42] 3GPP TS 29.468: "Group Communication System Enablers for LTE (GCSE_LTE); MB2 Reference Point; Stage 3".
[43] 3GPP TS 24.008: "Mobile Radio Interface Layer 3 specification; Core Network Protocols; Stage 3".
[44] IETF RFC 3264 (June 2002): "An Offer/Answer Model with the Session Description Protocol (SDP)".
[45] 3GPP TS 24.483: "Mission Critical Services (MCS) Management Object (MO)".
[46] Void.
[47] IETF RFC 4567 (July 2006): "Key Management Extensions for Session Description Protocol (SDP) and Real Time Streaming Protocol (RTSP)".
[48] IETF RFC 8101 (March 2017): "IANA Registration of New Session Initiation Protocol (SIP) Resource-Priority Namespace for Mission Critical Push To Talk service".
[49] 3GPP TS 24.482: "Mission Critical Services (MCS) identity management Protocol specification.
[50] 3GPP TS 24.484: "Mission Critical Services (MCS) configuration management Protocol specification".
[51] IETF RFC 3856 (August 2004): "A Presence Event Package for the Session Initiation Protocol (SIP)".
[52] IETF RFC 3863 (August 2004): "Presence Information Data Format (PIDF)".
[53] IETF RFC 7519 (May 2015): "JSON Web Token (JWT)".
[54] 3GPP TS 23.032: "Universal Geographical Area Description (GAD)".
[55] IETF RFC 4354 (January 2006): "A Session Initiation Protocol (SIP) Event Package and Data Format for Various Settings in Support for the Push-to-Talk over Cellular (PoC) Service".
[56] 3GPP TS 24.007: "Mobile radio interface signalling layer 3; General aspects".
[57] 3GPP TS 23.468: "Group Communication System Enablers for LTE (GCSE_LTE); Stage 2".
[58] 3GPP TS 24.237: "IP Multimedia Subsystem (IMS) Service Continuity; Stage 3".
[59] 3GPP TS 29.199-9: "Open Service Access (OSA); Parlay X Web Services; Part 9: Terminal location".
[60] W3C: "XML Encryption Syntax and Processing Version 1.1", https://www.w3.org/TR/xmlenc-core1/.
[61] W3C: "XML Signature Syntax and Processing (Second Edition)", http://www.w3.org/TR/xmldsig-core/.
[62] IETF RFC 2392 (August 1998): "Content-ID and Message-ID Uniform Resource Locators".
[63] IETF RFC 4661 (September 2006): "An Extensible Markup Language (XML)-Based Format for Event Notification Filtering".
[64] IETF RFC 6086 (January 2011): "Session Initiation Protocol (SIP) INFO Method and Package Framework".
[65] IETF RFC 3891 (September 2004): "The Session Initiation Protocol (SIP) Replaces Header".
[66] 3GPP TS 24.216: "Communication continuity managed object".
[67] IETF RFC 9562 (May 2024): " Universally Unique IDentifier (UUIDs)".
[68] IETF RFC 2045 (November 1996): "Multipurpose Internet Mail Extensions (MIME) Part One: Format of Internet Message Bodies".
[69] 3GPP TS 26.179: "Mission Critical Push To Talk (MCPTT) Codecs and media handling".
[70] 3GPP TS 24.301: "Non-Access-Stratum (NAS) protocol for Evolved Packet System (EPS); Stage 3".
[71] IETF RFC 4648 (October 2006): "The Base16, Base32, and Base64 Data Encodings".
[72] IETF RFC 5627 (October 2009): "Obtaining and Using Globally Routable User Agent URIs (GRUUs) in the Session Initiation Protocol (SIP)".
[73] 3GPP TS 29.283: "Diameter Data Management Applications".
[74] 3GPP TS 29.061: "Interworking between the Public Land Mobile Network (PLMN) supporting packet based services and Packet Data Networks (PDN)".
[75] IETF RFC 6509 (February 2012): "MIKEY-SAKKE: Sakai-Kasahara Key Encryption in Multimedia Internet KEYing (MIKEY)".
[76] 3GPP TS 22.280: "Mission Critical Services Common Requirements (MCCoRe); Stage 1".
[77] IETF RFC 7462 (March 2015): "URNs for the Alert-Info Header Field of the Session Initiation Protocol (SIP)".
[78] 3GPP TS 33.180: "Security of the mission critical service".
[79] 3GPP TS 29.214: "Policy and Charging Control over Rx reference point".
[80] IETF RFC 5795 (March 2010): "The Robust Header Compression (ROHC) Framework".
[81] IETF RFC 3095 (July 2001): "RObust Header Compression (ROHC): Framework and four profiles: RTP, UDP, ESP, and uncompressed".
[82] 3GPP TS 23.280: "Technical Specification Group Services and System Aspects; Common functional architecture to support mission critical services; Stage 2".
[83] IETF RFC 5288 (August 2008): "AES Galois Counter Mode (GCM) Cipher Suites for TLS".
[84] 3GPP TS 24.281: "Mission Critical Video (MCVideo) signalling control; Protocol specification".
[85] 3GPP TS 24.282: "Mission Critical Data (MCData) signalling control; Protocol specification".
[86] IETF RFC 5576 (June 2009): "Source-Specific Media Attributes in the Session Description Protocol (SDP)".
[87] 3GPP TS 24.501: "Non-Access-Stratum (NAS) protocol for 5G System (5GS); Stage 3".
[88] 3GPP TS 29.379: "Mission Critical Push To Talk (MCPTT) call control interworking with Land Mobile Radio (LMR) systems; Stage-3".
[89] IETF RFC 8445 (July 2018): "Interactive Connectivity Establishment (ICE): A Protocol for Network Address Translator (NAT) Traversal".
[90] IETF RFC 8839 (January 2021): "Session Description Protocol (SDP) Offer/Answer Procedures for Interactive Connectivity Establishment (ICE)".
[91] 3GPP TS 23.247: "Architectural enhancements for 5G multicast-broadcast services; Stage 2".
[92] 3GPP TS 23.289: "Mission Critical services over 5G System; Stage 2".
[93] IETF RFC 6809 (November 2012): "Mechanism to Indicate Support of Features and Capabilities in the Session Initiation Protocol (SIP)".
[94] 3GPP TS 24.554: " Proximity-services (ProSe) in 5G System (5GS) protocol aspects; Stage 3".
[95] 3GPP TS 23.501: "System architecture for the 5G System (5GS)".
[96] 3GPP TS 29.514: "5G System; Policy Authorization Service; Stage 3".
[97] 3GPP TS 29.522: "5G System; Network Exposure Function Northbound APIs; Stage 3".
[98] IETF RFC 3326 (December 2002): "The Reason Header Field for the Session Initiation Protocol (SIP)".
[99] IETF RFC 4826 (May 2007): "Extensible Markup Language (XML) Formats for Representing Resource Lists".
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3 Definitions, symbols and abbreviations
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3.1 Definitions
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For the purposes of the present document, the terms and definitions given in 3GPP TR 21.905 [1] and the following apply. A term defined in the present document takes precedence over the definition of the same term, if any, in 3GPP TR 21.905 [1].
An MCPTT user is affiliated to an MCPTT group: The MCPTT user has expressed interest in an MCPTT group it is a member of, and both the MCPTT server serving the MCPTT user and the MCPTT server owning the MCPTT group have authorized the MCPTT user's interest in the MCPTT group communication.
An MCPTT user is affiliated to an MCPTT group at an MCPTT client: The MCPTT user is affiliated to the MCPTT group, the MCPTT client has a registered IP address for an IMPU related to the MCPTT ID, and the MCPTT server serving the MCPTT user has authorised the MCPTT user's interest in the MCPTT group at the MCPTT client.
Affiliation status: Applies for an MCPTT user to an MCPTT group and has one of the following states:
a) the "not-affiliated" state indicating that the MCPTT user is not interested in the MCPTT group and the MCPTT user is not affiliated to the MCPTT group;
b) the "affiliating" state indicating that the MCPTT user is interested in the MCPTT group but the MCPTT user is not affiliated to the MCPTT group yet;
c) the "affiliated" state indicating that the MCPTT user is affiliated to the MCPTT group and there was no indication that MCPTT user is no longer interested in the MCPTT group; and
d) the "deaffiliating" state indicating that the MCPTT user is no longer interested in the MCPTT group but the MCPTT user is still affiliated to the MCPTT group.
Ambient listening call: a call type allowing an authorized MCPTT user to cause an MCPTT client to initiate a communication which results in no indication on the MCPTT UE that it is transmitting. Ambient listening can be initiated by an authorized MCPTT user who wants to be listened to by another authorized MCPTT user or can be initiated by an authorized MCPTT user who wants to listen to another MCPTT user.
Ambient listening client role: the role of an MCPTT client in an ambient listening call, which can be that of:
a) the "listening MCPTT user"; or
b) the "listened-to MCPTT user".
Ambient listening type: the type of an ambient listening call from the perspective of the relationship of the initiator of the call to the user being listened to. The two types of ambient listening call are:
a) "remote-init", indicating that the listening MCPTT user initiated the call; and
b) "local-init", indicating that the listened-to MCPTT user initiated the call.
First-to-answer call: A call initiated by one user towards a list of other users with the intention to establish an MCPTT private call or MCPTT emergency private call, with one of the users in the list of users.
Group document: when the group is not a regroup based on a preconfigured regroup, the term "group document" used within the present document refers to the group document for that group within the GMS as specified in 3GPP TS 24.481 [31]; when the group is a regroup based on a preconfigured group, the term "group document" used within the present document refers to the group document for the preconfigured group as specified in 3GPP TS 24.481 [31] restricted to the users or groups included in the regroup stored by the MCPTT server at the time of the regroup creation, see clause 16.
Group identity: An MCPTT group identity or a temporary MCPTT group identity.
In-progress emergency private call state: the state of two participants when an MCPTT emergency private call is in progress.
In-progress imminent peril group state: the state of a group when an MCPTT imminent peril group call is in progress.
Listening MCPTT user: the MCPTT user in an ambient listening call receiving the media transmission from the listened-to MCPTT user;
Listened-to MCPTT user: the MCPTT user in an ambient listening call who is being listened to, may or may not be aware of being listened to depending on ambient listening type of the call.
MCPTT client ID: is a globally unique identification of a specific MCPTT client instance. MCPTT client ID is a UUID URN as specified in IETF RFC 9562 [67].
MCPTT emergency alert state: MCPTT client internal perspective of the state of an MCPTT emergency alert.
MCPTT emergency group state: MCPTT client internal perspective of the in-progress emergency state of an MCPTT group maintained by the controlling MCPTT function.
MCPTT emergency group call state: MCPTT client internal perspective of the state of an MCPTT emergency group call.
MCPTT emergency private call: MCPTT emergency call between two MCPTT users that is initiated as a private call or a first-to-answer call with emergency indication, or without emergency indication when the MCPTT emergency state is already set,
MCPTT emergency private call state: MCPTT client internal perspective of the state of an MCPTT emergency private call.
MCPTT emergency private priority state: MCPTT client internal perspective of the in-progress emergency private call state of the two participants of an MCPTT emergency private call maintained by the controlling MCPTT function.
MCPTT imminent peril group call state: MCPTT client internal perspective of the state of an MCPTT imminent peril group call.
MCPTT imminent peril group state: MCPTT client internal perspective of the state of an MCPTT imminent peril group.
MCPTT private call: MCPTT call between two MCPTT users that is initiated as a private call or a first-to-answer call.
MCPTT private emergency alert state: MCPTT client internal perspective of the state of an MCPTT private emergency alert targeted to an MCPTT user.
MCPTT speech: Conversational audio media used in mission critical push to talk systems as defined by 3GPP TS 22.179 [2] and 3GPP TS 23.379 [3].
Media-floor control entity: A media control resource shared by participants in an MCPTT session, controlled by a state machine to ensure that only one participant can access the media resource at the same time.
N2: The maximum number of simultaneous affiliations to MCPTT groups that the MCPTT user may have. The value of N2 is specified in the <MaxAffiliationsN2> element of the <Common> element of the MCPTT user profile and corresponds to the parameter Nc2 specified in 3GPP TS 22.280 [76].
Private call: A call initiated by one user towards one other user with the intention to establish an MCPTT private call or MCPTT emergency private call.
Private Call Call-Back: A mechanism for a requesting MCPTT client to request a targeted MCPTT client to initiate an MCPTT private call with the requesting MCPTT client (at earliest convenience).
Remote change of an MCPTT user's selected group: A mechanism allowing an authorised user to remotely change the selected group of another MCPTT user.
Temporary MCPTT group identity: A group identity representing a temporary grouping of MCPTT group identities formed by the group regrouping operation as specified in 3GPP TS 24.481 [31].
Trusted mutual aid: A business relationship whereby the Partner MCPTT system is willing to share the details of the members of an MCPTT group that it owns with the Primary MCPTT system.
Untrusted mutual aid: A business relationship whereby the Partner MCPTT system is not willing to share the details of the members of an MCPTT group that it owns with the Primary MCPTT system.
User Requested Application Priority: The requested priority as defined in 3GPP TS 23.280 [82]. How the server determines the priority for the requested communication based on requested priority and in combination with other factors is up to MCPTT server implementation.
Functional alias status: Applies for the status of a functional alias for an MCTT user and has one of the following states:
a) the "not-activated" state indicating that the MCPTT user has not activated the functional alias;
b) the "activating" state indicating that the MCPTT user is interested in using the functional alias but the functional alias is not yet activated for the MCPTT user;
c) the "activated" state indicating that the MCPTT user has activated the functional alias;
d) the "deactivating" state indicating that the MCPTT user is no longer interested in using the functional alias but the functional alias is still activated for the MCPTT user; and
e) the "take-over-possible" state indicating that the MCPTT user interested in the functional alias is allowed to take-over the functional alias although the functional alias is already activated and used by another MCPTT user.
For the purposes of the present document, the following terms and definitions given in 3GPP TS 22.179 [2] apply:
In-progress emergency
MCPTT emergency alert
MCPTT emergency group call
MCPTT emergency state
Partner MCPTT system
Primary MCPTT system
For the purpose of the present document, the following terms and definitions given in 3GPP TS 24.380 [5] apply:
MBMS subchannel
For the purpose of the present document, the following terms and definitions given in 3GPP TS 23.379 [3] apply:
Pre-selected MCPTT user profile
Selected MCPTT user profile
For the purpose of the present document, the following terms and definitions given in 3GPP TS 33.180 [78] apply:
Client Server Key (CSK)
Multicast Floor Control Key (MKFC)
Multicast Signalling Key (MuSiK)
Multicast Signalling Key Identifier (MuSiK-ID)
MBMS subchannel control key (MSCCK)
MBMS subchannel control key identifier (MSCCK-ID)
Private Call Key (PCK)
Signalling Protection Key (SPK)
XML Protection Key (XPK)
For the purpose of the present document, the following terms and definitions given in 3GPP TS 22.280 [76] apply:
Functional alias
For the purposes of the present document, the following terms related to a MCPTT gateway UE function apply
MCPTT gateway UE: A functional entity that enables simultaneous access to the MCPTT system for multiple MCPTT clients.
MCPTT gateway client: A client that enables the authorized binding with one or more MCPTT GW UEs in order to be able to handle MCPTT services.
MCPTT gateway UE server: A server on an MCTT gateway UE that controls authorized binding with multiple MCPTT gateway clients.
MCPTT gateway UE function: Functional block as part of the MCPTT server that authorises and manages the association between MCPTT client and MCPTT gateway UE.
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e34e50ff54835e88e5e7b14a5e4c1405
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24.379
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3.2 Abbreviations
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For the purposes of the present document, the abbreviations given in 3GPP TR 21.905 [1] and the following apply. An abbreviation defined in the present document takes precedence over the definition of the same abbreviation, if any, in 3GPP TR 21.905 [1].
CID Context ID
CSK Client-Server Key
ECGI E-UTRAN Cell Global Identification
IPEG In-Progress Emergency Group
IPEPC In-Progress Emergency Private Call
IPIG In-Progress Imminent peril Group
MBMS Multimedia Broadcast and Multicast Service
MBS Multicast/Broadcast Service
MBSFN Multimedia Broadcast multicast service Single Frequency Network
MCPTT Mission Critical Push To Talk
MCPTT group ID MCPTT group Identity
MC Mission Critical
MCS Mission Critical Service
MEA MCPTT Emergency Alert
MEG MCPTT Emergency Group
MEGC MCPTT Emergency Group Call
MEPC MCPTT Emergency Private Call
MEPP MCPTT Emergency Private Priority
MES MCPTT Emergency State
MIME Multipurpose Internet Mail Extensions
MIG MCPTT Imminent peril Group
MIGC MCPTT Imminent peril Group Call
MONP MCPTT Off-Network Protocol
MPEA MCPTT Private Emergency Alert
NAT Network Address Translation
PCC Policy and Charging Control
PCCB Private Call Call-Back
PLMN Public Land Mobile Network
PPPP ProSe Per-Packet Priority
PQI PC5 5QI
QCI QoS Class Identifier
ROHC Robust Header Compression
RTP Real-time Transport Protocol
SAI Service Area Identifier
SDP Session Description Protocol
SIP Session Initiation Protocol
SPK Signalling Protection Key
SSRC Synchronization SouRCe
TGI Temporary MCPTT Group Identity
TMGI Temporary Mobile Group Identity
UE User Equipment
URI Uniform Resource Identifier
XPK XML Protection Key
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e34e50ff54835e88e5e7b14a5e4c1405
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24.379
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4 General
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e34e50ff54835e88e5e7b14a5e4c1405
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24.379
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4.1 MCPTT overview
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The MCPTT service supports communication between several users (i.e., group call), where each user has the ability to gain access to the permission to talk in an arbitrated manner. The MCPTT service also supports private calls between two users. Group calls and private calls can be provided on-network and off-network. In this release of the present document, support is only allowed for MCPTT speech communications.
The present document provides the call control protocol enhancements to support the MCPTT architectural procedures specified in 3GPP TS 23.379 [3].
For on-network calls, the present document makes use of the existing IMS procedures specified in 3GPP TS 24.229 [4], and provides new IMS application procedures specific for MCPTT. For on-network group calls, the procedures in the present document allow the use of unicast or multicast bearers. Multicast bearers are only supported in EPS.
The on-network procedures in this document allow an MCPTT user to:
- initiate a new MCPTT group call;
- join an MCPTT group call that has already been established; and
- leave an established MCPTT group call and then rejoin the same MCPTT group call if still established.
For off-network calls in EPS, the present document utilises the procedures for ProSe direct discovery for public safety; the procedures for one-to-one ProSe direct communication for Public Safety and the procedures for one-to-many ProSe direct communication for Public Safety, as specified in 3GPP TS 24.334 [28]. The present document specifies the MCPTT Off-Network Protocol (MONP) and the MONP application procedures.
For on-network and off-network calls, the present document provides support for MCPTT emergency calls, MCPTT imminent-peril calls and MCPTT emergency alerts.
NOTE: MCPTT emergency calls do not utilise emergency bearers. Instead the EPS bearer priority of a normal bearer is adjusted.
The MCPTT procedures provided by the present document refer to:
- the floor-control procedures defined in 3GPP TS 24.380 [5];
- the group management procedures defined in 3GPP TS 24.481 [31];
- the identity management procedures defined in 3GPP TS 24.482 [49];
- the security procedures defined in 3GPP TS 33.180 [78]; and
- the PS-PS access transfer procedures procedures defined in 3GPP TS 24.237 [58].
The MCPTT procedures provided by the present document access the configuration parameters provided by 3GPP TS 24.483 [45] and 3GPP TS 24.484 [50].
Codecs and media handling for MCPTT are specified in 3GPP TS 26.179 [69];
The following procedures are provided within this document:
- common procedures are specified in clause 6;
- procedures for registration in the IM CN subsystem and service authorisation are specified in clause 7;
- procedures for pre-established session establishment, modification and release are specified in clause 8;
- procedures for affiliation are specified in clause 9;
- procedures for management of functional alias in clause 9A;
- procedures for on-network and off-network group call are specified in clause 10;
- procedures for on-network and off-network private call are specified in clause 11;
- procedures for on-network and off-network emergency alert are specified in clause 12;
- location procedures are specified in clause 13;
- MBMS transmission usage procedures are specified in clause 14;
- MCPTT service continuity procedures are specified in clause 14A; and
- MBS transmission usage procedures are specified in clause 14B.
The MCPTT UE primarily obtains access to the MCPTT service via E-UTRAN or NG-RAN, using the procedures defined in 3GPP TS 24.301 [70] and 3GPP TS 24.501 [87].
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e34e50ff54835e88e5e7b14a5e4c1405
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24.379
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4.2 URI and address assignments
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In order to support MCPTT, the following URI and address assignments are assumed:
1) the participating MCPTT function is configured to be reachable using:
a) public service identities identifying pre-established sessions on the MCPTT server serving the MCPTT user;
b) the MBMS public service identity of the participating MCPTT function; and
c) the public service identity of the participating MCPTT function serving the MCPTT user.
NOTE: For b) and c) above, the PSI values are configured with the same URI. However for the purpose of readability the names of the PSIs mentioned in b) and c) are used in the present document.
The MCPTT client should use the <Server‑URI> element of the <MCPTT-Service-Details> element of the <anyExt> element of the <on-network> element in the MCS UE initial configuration document, as defined in reference 3GPP TS 24.484 [50] as public service identity of the participating function of the MCPTT client.
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e34e50ff54835e88e5e7b14a5e4c1405
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24.379
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4.3 MCPTT speech
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A session that contains MCPTT speech is either a full-duplex session or a half-duplex session with an SDP media component containing an audio media type with a codec suitable for conversational speech that exists between an MCPTT client and an MCPTT server.
If the MCPTT speech session is a half-duplex session, it additionally contains a media component that describes the characteristics of the media-floor control entity.
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