New ADAE analytics on collision detection

Abstract

Systems and methods related to collision detection in a wireless communications system are disclosed. In one embodiment, a method performed by an Analytics Data Analytics Enablement (ADAE) server comprises obtaining ranging and / or sidelink positioning data of one or more User Equipments (UEs) and location information for objects and / or UEs from one or more data producers. The method further comprises deriving analytics data for collision detection of at least one of the one or more UEs based on the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs and providing the analytics data for collision detection to a consumer. In this manner, ADAE server can perform collision detection based on inputs from a wide range of data producers, which will increase collision detection accuracy.

Description

NEW ADAE ANAL YTICS ON COLLISION DETECTIONRelated Applications

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 631,265, filed April 8, 2024, the disclosure of which is hereby incorporated herein by reference in its entirety.Technical Field

[0002] The present disclosure relates to a wireless communications system and, more specifically, to collision detection in a wireless communications system.Background

[0003] In the 3rdGeneration Partnership Project (3GPP), study on enhanced application layer support for location has been agreed in SA6 for Release 19. As described in Key Issue #5 of 3GPP Technical Report (TR) 23.700-72 V0.4.0, the study aspects on support for ranging / sidelink positioning services include:- How to support the selection and configuration of Vertical Application Layer (VAL) User Equipments (UEs) acting as reference UEs?- Whether and how the enabler layer can support exposing ranging information to 3rd party consumers?There is no existing solution to address the challenges in the study aspects.Summary

[0004] Systems and methods related to collision detection in a wireless communications system are disclosed. In one embodiment, a method performed by an Analytics Data Analytics Enablement (ADAE) server comprises obtaining ranging and / or sidelink positioning data of one or more User Equipments (UEs) and location information for objects and / or UEs from one or more data producers. The method further comprises deriving analytics data for collision detection of at least one of the one or more UEs based on the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs and providing the analytics data for collision detection to a consumer. In this manner, ADAE server can perform collisiondetection based on inputs from a wide range of data producers, which will increase collision detection accuracy.

[0005] In one embodiment, the one or more data producers comprise any one or more of the following: one or more network functions in a core network of a wireless communication system, an ADAE client, a Service Enabler Architecture Layer for Verticals (SEAL) location management server, a SEAL location management client, a 3rdparty location management server, and an Application layer Analytical Data Repository Function (A-ADRF).

[0006] In one embodiment, the one or more data producers comprise any two or more of the following: one or more network functions in a core network of a wireless communication system, an ADAE client, a Service Enabler Architecture Layer for Verticals (SEAL) location management server, a SEAL location management client, a 3rdparty location management server, and an Application layer Analytical Data Repository Function (A-ADRF).

[0007] In one embodiment, obtaining the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs comprises, for each data producer of the one or more data producers, sending, to the data producer, a subscription request and receiving, from the data producer, at least some of the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs. In one embodiment, the subscription request comprises any one or more of the following information elements: information that identifies the consumer, information that identifies a data collection event, information that indicates one or more requirements for collection of the ranging and / or sidelink positioning data of the one or more UEs and / or the location information for objects and / or UEs, information that identifies an associated analytics event, a list of data producer identifiers, information that indicates one or more characteristics of data producers to be used for the subscription request, a list of Vertical Application Layer (VAL) UE identifiers for which the requested data or analytics applies, information that indicates a geographical area of interest, and information that indicates a validity time for the subscription request.

[0008] In one embodiment, the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs comprises any one or more of the following: ranging and / or sidelink positioning data of the one or more UEs,location information of UEs, location information of one or more static objects for a given time and area of interest, and relative proximity analytics for the one or more UEs in relation to one or more other UEs and / or one or more static objects.

[0009] In one embodiment, the method further comprises receiving, from the consumer, a collision data analytics subscription request, wherein providing the analytics data for collision detection to the consumer comprises providing, to the consumer, a collision data analytics notification or a collision data analytics response comprising the analytics data for collision detection. In one embodiment, the collision data analytics subscription request or the collision data analytics request comprises any one or more of the following information elements: information that indicates the one or more UEs, information that indicates a Vertical Application Layer, VAL, server to which the request applies, and information that indicates one or more attributes for collision detection. The information that indicates one or more attributes for collision detection includes any one or more of the following information elements: minimum distance between UEs or between UEs and objects, maximum velocity of UEs, an expected direction of UEs and / or moving objects, a movement track of UEs and / or moving objects, and a granularity of the movement track.

[0010] In one embodiment, the analytics data for collision detection comprises any one or more of the following information elements: information that identifies one or more UEs to which the analytics data applies, information that indicates one or more times of potential collision(s) between UEs or between UE(s) and object(s), and a confidence level(s) of the potential collision(s).

[0011] Corresponding embodiments of an ADAE server are also disclosed. In one embodiment, an ADAE server is adapted to obtain ranging and / or sidelink positioning data of one or more UEs and location information for objects and / or UEs, from one or more data producers. The ADAE server is further adapted to derive analytics data for collision detection of at least one of the one or more UEs based on the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs and provide the analytics data for collision detection to a consumer.

[0012] In one embodiment, a network node for implementing an ADAE server comprises processing circuitry configured to cause the network node to obtain ranging and / or sidelink positioning data of one or more UEs and location information for objects and / or UEs, from one or more data producers. The processing circuitry is furtherconfigured to cause the network node to derive analytics data for collision detection of at least one of the one or more UEs based on the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs and provide the analytics data for collision detection to a consumer.

[0013] Embodiments of a method performed by a data producer are also disclosed. In one embodiment, a method performed by a data producer comprises providing at least one of ranging and / or sidelink positioning data of one or more UEs and location information for objects and / or UEs, to an ADAE server to be used to derive collision detection analytics.

[0014] Corresponding embodiments of a data producer and a network node for implementing a data producer are also disclosed. In one embodiment, a data producer is adapted to provide at least one of ranging and / or sidelink positioning data of one or more UEs and location information for objects and / or UEs, to an ADAE server to be used to derive collision detection analytics.

[0015] In one embodiment, a network node for implementing a data producer comprises processing circuitry configured to cause the network node to provide at least one of ranging and / or sidelink positioning data of one or more UEs and location information for objects and / or UEs, to an ADAE server to be used to derive collision detection analytics.

[0016] Embodiments of method performed by an analytics consumer are also disclosed. In one embodiment, a method performed by an analytics consumer comprises receiving collision detection analytics data for one or more UEs from an ADAE server in response to sending a request that comprises attributes for collision detection to be applied when generating collision detection analytics data. In one embodiment, the method further comprises performing one or more operations based on the collision detection analytics data.

[0017] Corresponding embodiments of an analytics consumer and a network node for implementing an analytics consumer are also disclosed.Brief Description of the Drawings

[0018] The accompanying drawing figures incorporated in and forming a part of this specification illustrate several aspects of the disclosure, and together with the description serve to explain the principles of the disclosure.

[0019] Figure 1 illustrates one example of a system for Application Data Analytics Enablement (ADAE), in which embodiments of the present disclosure may be implemented.

[0020] Figure 2 and Figure 3 illustrate the operation of a data producer, an ADAE Server, and a consumer, in accordance with example embodiments of the present disclosure.

[0021] Figure 4 illustrates a procedure for Unmanned Aerial System (UAS) Application Enabler (UAE) server based Detect and Avoid (DAA), in accordance with one example embodiment of the present disclosure.

[0022] Figure 5 illustrates one example embodiment of the data collection subscription response of step 212 of Figure 2.

[0023] Figure 6 is a schematic block diagram that illustrates a virtualized embodiment of the network node according to some embodiments of the present disclosure.Detailed Description

[0024] Some of the embodiments contemplated herein will now be described more fully with reference to the accompanying drawings. Other embodiments, however, are contained within the scope of the subject matter disclosed herein, the disclosed subject matter should not be construed as limited to only the embodiments set forth herein; rather, these embodiments are provided by way of example to convey the scope of the subject matter to those skilled in the art.

[0025] There currently exist certain challenge(s). As discussed in the Background section above, there is no existing solution to address the challenges in study aspects for Key Issue (KI) #5 in 3rdGeneration Partnership Project (3GPP) Technical Report (TR) 23.700-72 V0.4.0 on "Whether and how the enabler layer can support exposing ranging information to 3rd party consumers?"

[0026] Certain aspects of the present disclosure and their embodiments may provide solutions to the aforementioned or other challenges. Ranging and / or sidelink positioning information available in a telecommunication system such as the 5thGeneration (5G) System (5GS), or 6thGeneration (6G) system or beyond can be used in many applications with the support of an enabler layer (e.g., Service Enabler Architecture Layer for Verticals (SEAL)). For example, such ranging and / or sidelinkinformation may be used by an Application Data Analytics Enablement (ADAE) Server to generate analytics for various applications. The embodiments herein are described with 5GS as an example of a telecommunication system, but the embodiments can be applied to other telecommunication systems such as 4thGeneration (4G) system, 6G systems, and beyond.

[0027] To support exposing ranging information to 3rd party consumers, systems and methods are disclosed herein that provide new ADAE analytics for collision detection by using the ranging / sidelink positioning information of User Equipments (UEs) from the 5thGeneration (5G) Core (5GC) and location information of objects from SEAL Location Management (LM) server and 3rdparty LM server.

[0028] For example, the ADAE Server can use the ranging / sidelink positioning information of UEs from the 5GC, location information of objects from the SEAL LM server (e.g., location information of moving objects like Unmanned Aerial System (UAS) devices, Vehicle-to-Anything (V2X) devices, robots, and / or people), and the location information about the environment (e.g., static objects such as, for example, buildings) from the 3rdparty LM server, to generate predictions on collision detection. The analytics output includes a list of objects with the alleged collision location and times for the given time horizon. The predictions on potential collisions can be used, for example:- to minimize the effect of collisions between moving robots in a factory environment,- to avoid collisions between vehicles and pedestrians for intelligent driving,- for planning a best moving route for robots in a smart warehouse environment,- by UAS Application Enabler (UAE) Server and / or UAS application specific server for Detect and Avoid (DAA), planning flight route of Unmanned Aerial Vehicles (UAVs), and determining a proper control entity of a UAV.

[0029] It should be noted that the new ADAE analytics for collision detection disclosed herein provides advantages over existing solutions by using the ranging / sidelink positioning information of UEs from 5GC, and the location information of objects from SEAL LM server and 3rdparty LM server. More specifically, as compared to the existing Network Data Analytics Function (NWDAF) Analytics ID "RelativeProximity" (procedure given in 3GPP Technical Specification (TS) 23.288 V18.5.0, clause 6.19.4), the new ADAE analytics disclosed herein can take inputs from a wider range of data producers, e.g., from 5GC for ranging / sidelink positioning information of UEs andfrom SEAL LM server and 3rdparty LM server for location information of objects, from ADAE client for location of UE. Based on information available in the application layer (e.g., Vertical Application Layer (VAL) Service ID), the ADAE server of the present disclosure can determine the shape and size of the objects that will increase the collision detection accuracy. The new ADAE analytics considers a wider range of objects for collision detection, e.g., moving objects (e.g., UAS devices, V2X devices, robots, and / or people), static objects (e.g., buildings, infrastructure), and UEs in 5G network. In contrast, the existing NWDAF analytics only focus on the UEs which are registered in 5G network.

[0030] Further, as compared to the existing solutions for UAV / UAV Controller (UAV- C) Triggered Network-assisted DAA (procedure given in 3GPP TR 23.700-59 VO.2.0, clause 6.5.3.1), the new ADAE analytics disclosed herein generates collision detection analytics of potential collisions, not only between UAVs, but also between UAVs and the objects in environment (e.g., buildings, infrastructure), which is not possible in the existing solution. The existing solution requires that information of the UE is known to request service from 5GC, e.g., identifier of the UAV(s) (e.g., Generic Public Subscription Identifier(s) (GPSI(s)), Civil Aviation Authority (CAA)-Level UAV ID(s)) as inputs to request 5GC for Gateway Mobile Location Center (GMLC) service on Ranging / Sidelink Positioning location and / or Relative Proximity predictions on collision from NWDAF via the Network Exposure Function (NEF). The new ADAE analytics disclosed herein does not have such limitations.

[0031] Figure 1 illustrates one example of a system 100 for ADAE, in which embodiments of the present disclosure may be implemented. The system 100 includes a VAL UE 102, a 3GPP network system 104, a VAL server(s) 106, and an ADAE server 108. The VAL UE 102 includes a VAL client(s) 110 and an ADAE client 112. The ADAE server 108 is one example of the ADAE Server (ADAES) 202 described below in the description of Figure 2 and Figure 3 and the associated information flows.

[0032] Figure 2 and Figure 3 illustrate the operation of a data producer 200, an ADAES 202, and a consumer 204, in accordance with example embodiments of the present disclosure. The data producer 200 is a network function such as, for example, a GMLC, a NWDAF, an Application Data Analytics Engine (ADAE) client, a LM server, LM client, 3rdparty LM server, Application layer Analytical Data Repository Function (A- ADRF) for historical data, or the like. Note that while only one data producer 200 isshown in Figure 2, there may be more than one data producer from which data is collected and analyzed, separately or together, by the ADAES 202. The consumer 204 can be any type of analytics data consumer such as, e.g., a VAL server, an LM server, a UAE server, a UAS application specific server, or the like.

[0033] The procedures of Figures 2 and 3 provide new ADAE analytics on collision detection. The collision detection analytics are based on the ranging / sidelink positioning information of UEs from 5GC, and the location information of objects from SEAL LM server, SEAL LM client, 3rd party LM server, and / or A-ADRF (for historical data).

[0034] The following description specify procedures, information flows and Application Programming Interfaces (APIs) to support new ADAE analytics on collision detection among objects by using ranging / sidelink positioning information of UEs exposure from 5GC, and the location information of objects from SEAL LM server, SEAL LM client, 3rd party LM server, and / or A-ADRF (for historical data).

[0035] Pre-conditions:- Information about the environment, e.g. static objects, and buildings, is available from the 3rdparty LM server.- The location information about the UEs is available at SEAL LM server.- The Ranging / Sidelink Positioning information exposure of the UEs is allowed at 5GC.

[0036] Figure 2 illustrates the operation of the data producer 200, the ADAES 202, and the consumer 204 to provide new ADAE analytics on collision detection using a subscribe-notify mechanism, in accordance with one embodiment of the present disclosure. The steps of the procedure of Figure 2 are as follows.

[0037] Step 206: The analytics consumer 204 (e.g. VAL Server, LM server, UAE server, UAS application specific server) sends analytics subscription request for collision detection analytics to the ADAE server 202. Table 1 below illustrates one example embodiment of the information elements contained in the analytics subscription request. Note that this is only an example. In this example embodiment, the Analytics ID in the request message is set to "Collision detection analytics".

[0038] Step 208: Upon receiving the analytics subscription request from the consumer 204, the ADAE server 202 checks for the relevant authorization for this event subscription. If the authorization is successful, the ADAE server 202 stores the request information (e.g., all or some of the information contained in the sends analyticssubscription request). The ADAE server 202 sends a service API event subscription response indicating successful subscription. In the illustrated example, the API event subscription response is a collision detection analytics subscription response. Table 2 below illustrates one example embodiment of the information elements contained in the analytics subscription response. Note that this is only an example.

[0039] Step 210: The ADAE server 202 sends a subscription request to the Data Producer 200 (e.g. 5GC NFs (e.g. GMLC, NWDAF), ADAE Client (e.g. the ADAE Client deployed at a UE), LM server, LM client, 3rd party LM server, A-ADRF for historical data) with the respective Data Collection Event ID and the requirement for collection of ranging and / or sidelink positioning related data or analytics of UEs, and location information of UEs and / or objects. For example, data collection at the UE(s) reuses the SA4 mechanism based on Event Exposure (EVEX) study (3GPP TS 26.531 V18.1.0). Table 4 below illustrates one example embodiment of the data collection subscription request of Step 210. Note that this is only an example.

[0040] Step 212: The Data Producer 200 sends subscription response as a positive or negative acknowledgement to the ADAE server 202. Figure 5 illustrates one example embodiment of the data collection subscription response of step 212. Note that this is only an example.

[0041] Step 214: The ADAE server 202, based on the subscription of step 210, receives ranging and / or sidelink positioning related data / analytics of UEs, and location information of UEs and / or objects. Table 6 below illustrates one example embodiment of the data notification of step 214. Note that this is only an example.

[0042] That that the procedures for UE related data collection preferably take user consent into account.

[0043] Step 216: The ADAE server 202 performs analytics relevant operations to generate the analytics based on the data received from the Data Producer 200 (e.g. 5GC NFs, ADAE Client, LM server, LM client, 3rdparty LM server, and / or A-ADRF for historical data). The details of the analytics of step 216 and how these analytics are performed are outside of the scope of the present disclosure. Note, however, that the analytics is based on the ranging and / or sidelink positioning related data / analytics of UEs, and location information of objects received from the data producer(s) 200 (e.g., 5GC NFs, ADAE Client, LM server, LM client, 3rdparty LM server, and / or A-ADRF for historical data).

[0044] Step 218: The ADAE server 202 sends a notification(s) to the consumer 204 with the requested collision detection analytics. One example embodiment of the information elements contained in this notification of step 218 is illustrated in Table 3 below. Note that this is only an example.

[0045] Figure 3 illustrates the operation of the 3 the ADAES 202 and the consumer 204 to provide new ADAE analytics on collision detection using a subscribe-notify mechanism, in accordance with one embodiment of the present disclosure. The steps of the procedure of Figure 3 are as follows.

[0046] Pre-conditions:- ADAE Server 202 already has the analytics data derived from steps 3-6 in the procedure of Figure 2.

[0047] Step 300: The analytics consumer 204 (e.g. VAL Server, LM Server, UAE server, UAS application specific server) sends a request message to the ADAE server 202 to receive analytics data for collision detection analytics with Analytics ID in the request message setting to "Collision detection analytics". In one example embodiment, the request of step 300 contains the information elements as defined in Table 7. However, this is only an example.

[0048] Step 302: Upon receiving the request, the ADAE server 202 authenticates and authorizes the analytics consumer.

[0049] Step 304: If the analytics consumer 204 is authorized, the ADAE server 202 sends a response message including the analytics data (statistical and / or predictive) of the collision detection analytics. In one example embodiment, the response includes the information elements as defined in Table 8 below. However, this is only an example.

[0050] Table 1 describes the information flow from the consumer 204 (e.g. VAL Server, LM Server, UAE server, UAS application specific server) as a request or update request for the collision detection analytics (e.g., in step 206 of Figure 2 or similar in step 300 of Figure 3).Table 1: Collision detection analytics subscription request

[0051] Table 2 describes the information elements for the collision detection analytics subscription response from the ADAE server 202 to the consumer 204 in step 208 of Figure 2.Table 2: Collision detection analytics subscription response

[0052] Table 3 describes the information flow from the ADAE server 202 to the consumer 204 (e.g. VAL Server, LM Server, UAE server, UAS application specific server) as a response for the collision detection analytics (e.g., in step 218 of Figure 2 or similar in step 304 of Figure 3).Table 3: Collision detection analytics notification

[0053] Table 4 describes information elements for the Ranging / SL positioning data and location information collection subscription request from the ADAE server 202 to the Data Producer 200, e.g. 5GC NFs (e.g. GMLC, NWDAF), ADAE Client (e.g. the ADAE Client deployed at an AAM), LM server, LM client, 3rdparty LM server, A-ADRF for historical data, in step 210 of Figure 2 .Table 4: Data collection subscription request

[0054] Table 5 describes information elements for the Data collection subscription response from the Data Producer 200, e.g. 5GC NFs (e.g. GMLC, NWDAF), ADAE Client (e.g. the ADAE Client deployed at a UE), LM server, LM client, 3rdparty LM server, A- ADRF for historical data, in step 212 of Figure 2.Table 5: Data collection subscription response

[0055] Table 6 describes information elements for the Data Notification from the Data Producer 200 to the ADAE server 202, in step 214 of Figure 2.Table 6: Data notification

[0056] Table 7 describes information elements for the collision detection analytics request from the analytics consumer 204 to the ADAE server 202, in step 300 of Figure 3.Table 7: Get analytics data request

[0057] Table 8 describes information elements for the Get collision detection analytics response from the ADAE server 202 to the consumer 204 in step 304 of Figure 3. Table 8: Get analytics response

[0058] Some further embodiments of the present disclosure in which, for example, the new ADAE analytics on collision detection described above may be utilized. In particular, Figure 4 illustrates a procedure for UAE server based DAA, in accordance with one example embodiment of the present disclosure. As illustrated, the procedure of Figure 4 involves a UAE client 400, a UAE server 402, and a UAS application specific server 404. The procedure of Figure 4 is as follows:

[0059] Pre-conditions:• UAE server has established a UAE session with the respective UAE clients as the UAE clients are successfully registered to the UAE server.• UAE Server determines to do DAA if the UAV does not contain DAA assist capability in its UAS UE information during the UAS UE registration procedure, or based on its local policy, or according to the request from UAS application specific server.

[0060] Step 406: The UAE Server 402 has received information / analytics about UAVs (e.g., via the procedure of Figure 2 or Figure 3, where the UAE server 402 corresponds to the consumer 204). The UAE Server 402 determines the UAVs which may be in the proximity of the UAV based on the information / analytics.

[0061] Step 408: The UAE Server 402 sends the DAA event information to the UAS application specific server 404 and / or the UAE client 400, which includes information of other UAVs in the proximity of the UAV.

[0062] Step 408a: The UAE server 402 may send the DAA event information to the UAS application specific server 404 comprising the UAVs information and location of each UAV in proximity of the UAV.

[0063] Step 408b: The UAE server 402 may send the DAA event information to the UAE client 400 comprising the UAVs information and location of each UAV in proximity of the UAV.

[0064] Step 410: The UAS application specific server 404 and / or the UAE client 400 sends the UAE server 402 a DAA event information acknowledge.

[0065] Step 410a: If received DAA event information in step 408, the UAS application specific server 404 sends to the UAE server a DAA event information acknowledge.

[0066] Step 410b: If received DAA event information in step 408, the UAE client 400 sends to the UAE server 402 a DAA event information acknowledge.

[0067] Table 9 describes one example embodiment of the information flow DAA event information from the UAE server 402 to the UAS application specific server 404 (step 408a) and the UAE client 400 (step 408b).Table 9: DAA event information

[0068] Table 10 describes one example embodiment of the information flow DAA event information acknowledge from the UAE client 400 (step 410b) and the UAS application specific server 404 (step 410a) to the UAE server 402.Table 10: DAA event information client acknowledge

[0069] Figure 5 is a schematic block diagram of a network node 500 according to some embodiments of the present disclosure. Optional features are represented by dashed boxes. The network node 500 may be, for example, a network node that implements one or more of the network functions acting as the data producer 200, a network node that implements the ADAE server 202, a network node that implements the consumer 204, a network node that implements the UAE client 400, a network node that implements the UAE server 402, or a network node that implements the UAS application specific server 404. As illustrated, the network node 500 includes a one or more processors 504 (e.g., Central Processing Units (CPUs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), and / or the like), memory 506, and a network interface 508. The one or more processors 504 are also referred to herein as processing circuitry. The one or more processors 504 operate toprovide one or more functions of the network node 500 as described herein (e.g., one or more functions of the data producer 200, the ADAE server 202, the consumer 204, the UAE client 400, the UAE server 402, or the UAS application specific server 404 as described herein). In some embodiments, the function(s) are implemented in software that is stored, e.g., in the memory 506 and executed by the one or more processors 504.

[0070] Figure 6 is a schematic block diagram that illustrates a virtualized embodiment of the network node 500 according to some embodiments of the present disclosure. Again, optional features are represented by dashed boxes. As used herein, a "virtualized" network node is an implementation of the network node 500 in which at least a portion of the functionality of the network node 500 is implemented as a virtual component(s) (e.g., via a virtual machine(s) executing on a physical processing node(s) in a network(s)). As illustrated, in this example, the network node 500 includes one or more processing nodes 600 coupled to or included as part of a network(s) 602. Each processing node 600 includes one or more processors 604 (e.g., CPUs, ASICs, FPGAs, and / or the like), memory 606, and a network interface 608. In this example, functions 610 of the network node 500 described herein (e.g., one or more functions of the data producer 200, the ADAE server 202, the consumer 204, the UAE client 400, the UAE server 402, or the UAS application specific server 404 as described herein) are implemented at the one or more processing nodes 600 or distributed across the two or more processing nodes 600 in any desired manner. In some particular embodiments, some or all of the functions 610 of the network node 500 described herein are implemented as virtual components executed by one or more virtual machines implemented in a virtual environ ment(s) hosted by the processing node(s) 600.

[0071] In some embodiments, a computer program including instructions which, when executed by at least one processor, causes the at least one processor to carry out the functionality of the network node 500 or a node (e.g., a processing node 600) implementing one or more of the functions 610 of the network node 500 in a virtual environment according to any of the embodiments described herein is provided. In some embodiments, a carrier comprising the aforementioned computer program product is provided. The carrier is one of an electronic signal, an optical signal, a radio signal, or a computer readable storage medium (e.g., a non-transitory computer readable medium such as memory).

[0072] Any appropriate steps, methods, features, functions, or benefits disclosed herein may be performed through one or more functional units or modules of one or more virtual apparatuses. Each virtual apparatus may comprise a number of these functional units. These functional units may be implemented via processing circuitry, which may include one or more microprocessor or microcontrollers, as well as other digital hardware, which may include Digital Signal Processor (DSPs), special-purpose digital logic, and the like. The processing circuitry may be configured to execute program code stored in memory, which may include one or several types of memory such as Read Only Memory (ROM), Random Access Memory (RAM), cache memory, flash memory devices, optical storage devices, etc. Program code stored in memory includes program instructions for executing one or more telecommunications and / or data communications protocols as well as instructions for carrying out one or more of the techniques described herein. In some implementations, the processing circuitry may be used to cause the respective functional unit to perform corresponding functions according to one or more embodiments of the present disclosure.

[0073] While processes in the figures may show a particular order of operations performed by certain embodiments of the present disclosure, it should be understood that such order is exemplary (e.g., alternative embodiments may perform the operations in a different order, combine certain operations, overlap certain operations, etc.).

[0074] Some exemplary embodiments of the present disclosure are as follows:

[0075] Embodiment 1: A method performed by an Analytics Data Analytics Enablement, ADAE, server (202), the method comprising: obtaining (210-214) ranging and / or sidelink (ranging / sidelink) positioning data of one or more User Equipments, UEs, and location information for objects and / or UEs, from one or more data producers (200); deriving (216) analytics data for collision detection of at least one of the one or more UEs, based on the ranging / sidelink positioning data of the one or more UEs and the location information for objects and / or UEs; providing (218; 304) the analytics data for collision detection to a consumer (204).

[0076] Embodiment 2: The method of embodiment 1, wherein the one or more data producers (200) comprise any one or more of the following: one or more network functions in a core network of a wireless communication system (e.g., one or more 5GC NFs such as, e.g., GMLC and / or NWADF); an ADAE client; a SEAL location managementserver; a SEAL location management client; a 3rdparty location management server; an A-ADRF.

[0077] Embodiment 3: The method of embodiment 1, wherein the one or more data producers (200) comprise any two or more of the following: one or more network functions in a core network of a wireless communication system (e.g., one or more 5GC NFs such as, e.g., GMLC and / or NWADF); an ADAE client; a SEAL location management server; a SEAL location management client; a 3rdparty location management server; an A-ADRF.

[0078] Embodiment 4: The method of any of embodiments 1 to 3, wherein obtaining (210-214) the ranging / sidelink positioning data of the one or more UEs and the location information for objects and / or UEs comprises, for each data producer (200) of the one or more data producers (200): sending (210), to the data producer (200), a subscription request; and receiving (212), from the data producer (200), at least some of the ranging / sidelink positioning data of the one or more UEs and the location information for objects and / or UEs.

[0079] Embodiment 5: The method of embodiment 4, wherein the subscription request comprises any one or more of the following information elements: information that identifies the consumer (204); information that identifies a data collection event; information that indicates one or more requirements (e.g., data format, frequency of reporting, level of data abstraction, level of data accuracy) for collection of the ranging / sidelink positioning data of the one or more UEs and / or the location information for objects and / or UEs; information that identifies an associated analytics event; a list of data producer identifiers; information that indicates one or more characteristics of data producers to be used for the subscription request; a list of VAL UE identifiers for which the requested data or analytics applies; information that indicates a geographical area of interest; information that indicates a validity time for the subscription request.

[0080] Embodiment 6: The method of any of embodiments 1 to 5, wherein the ranging / sidelink positioning data of the one or more UEs and the location information for objects and / or UEs comprises any one or more of the following: ranging / sidelink positioning data of the one or more UEs; location information of UEs (e.g., moving devices); location information one or more static objects for a given time and area of interest; relative proximity analytics for the one or more UEs in relation to one or more other UEs and / or one or more static objects.

[0081] Embodiment 7: The method of any of embodiments 1 to 6, further comprising: receiving (206), from the consumer (204), (e.g., prior to 210-214) a collision data analytics subscription request; wherein providing (218) the analytics data for collision detection to the consumer (204) comprises providing (218), to the consumer (204), a collision data analytics notification comprising the analytics data for collision detection.

[0082] Embodiment 8: The method of any of embodiments 1 to 6, further comprising: receiving (300), from the consumer (204), a collision data analytics request; wherein providing (304) the analytics data for collision detection to the consumer (204) comprises providing (304), to the consumer (204), a collision data analytics response comprising the analytics data for collision detection.

[0083] Embodiment 9: The method of embodiment 7 or 8, wherein the collision data analytics subscription request (embodiment 7) or the collision data analytics request (embodiment 8) comprises any one or more of the following information elements: information that indicates the one or more UEs; information that indicates a VAL server to which the request applies; information that indicates one or more attributes for collision detection, which may include any one or more of the following information elements: minimum distance between UEs or between UEs and objects); maximum velocity of UEs; an expected direction of UEs and / or moving objects; a movement track of UEs and / or moving objects; a granularity of the movement track).

[0084] Embodiment 10: The method of any of embodiments 1 to 9, wherein the analytics data for collision detection comprises any one or more of the following information elements: information that identifies one or more UEs to which the analytics data applies; information that indicates one or more times of potential collision(s) between UEs or between UE(s) and object(s); a confidence level(s) of the potential collision(s).

[0085] Embodiment 11: An Analytics Data Analytics Enablement, ADAE, server (202) adapted to perform the method of any of embodiments 1 to 10.

[0086] Embodiment 12: A network node (500) for implementing an Analytics Data Analytics Enablement, ADAE, server (202), the network node (500) comprising processing circuitry configured to cause the network node (500) to perform the method of any of embodiments 1 to 10.

[0087] Embodiment 13: A method performed by data producer (200), the method comprising: providing (214) ranging and / or sidelink (ranging / sidelink) positioning data of one or more User Equipments, UEs, and location information for objects and / or UEs, to an Analytics Data Analytics Enablement, ADAE, server (202).

[0088] Embodiment 14: The method of embodiment 13, wherein the data producer (200) is any one or more of the following: one or more network functions in a core network of a wireless communication system (e.g., one or more 5GC NFs such as, e.g., GMLC and / or NWADF); an ADAE client; a SEAL location management server; a SEAL location management client; a 3rdparty location management server; an A-ADRF.

[0089] Embodiment 15: The method of any of embodiments 13 to 14, wherein providing (214) the ranging / sidelink positioning data of the one or more UEs and the location information for objects and / or UEs comprises: receiving (210), from the ADAE server (202), a subscription request; and sending (214), to the ADAE server (202), a subscription notification(s) comprising the ranging / sidelink positioning data of the one or more UEs and the location information for objects and / or UEs.

[0090] Embodiment 16: The method of embodiment 15, wherein the subscription request comprises any one or more of the following information elements: information that identifies the consumer (204); information that identifies a data collection event; information that indicates one or more requirements (e.g., data format, frequency of reporting, level of data abstraction, level of data accuracy) for collection of the ranging / sidelink positioning data of the one or more UEs and / or the location information for objects and / or UEs; information that identifies an associated analytics event; a list of data producer identifiers; information that indicates one or more characteristics of data producers to be used for the subscription request; a list of VAL UE identifiers for which the requested data or analytics applies; information that indicates a geographical area of interest; information that indicates a validity time for the subscription request.

[0091] Embodiment 17: The method of any of embodiments 13 to 16, wherein the ranging / sidelink positioning data of the one or more UEs and the location information for objects and / or UEs comprises any one or more of the following: ranging / sidelink positioning data of the one or more UEs; location information of UEs (e.g., moving devices); location information one or more static objects for a given time and area of interest; relative proximity analytics for the one or more UEs in relation to one or more other UEs and / or one or more static objects.

[0092] Embodiment 18: A data producer (200) adapted to perform the method of any of embodiments 13 to 17.

[0093] Embodiment 19: A network node (500) for implementing a data producer (200), the network node (500) comprising processing circuitry configured to cause the network node (500) to perform the method of any of embodiments 13 to 17.

[0094] Embodiment 20: A method performed by an analytics consumer (204; 402), the method comprising: receiving (218; 304) collision detection analytics data for one or more User Equipments, UEs, from an Analytics Data Analytics Enablement, ADAE, server (202).

[0095] Embodiment 21: The method of embodiment 20, further comprising performing (406) one or more operations based on the collision detection analytics data.

[0096] Embodiment 22: The method of embodiment 20 or 21, wherein the collision detection analytics data comprises any one or more of the following: information that identifies one or more UEs; information that indicates one or more times of potential collision(s) between UEs or between UE(s) and object(s); a confidence level(s) of the potential collision(s).

[0097] Embodiment 23: The method of any of embodiments 18 to 20, further comprising: sending (206), to the ADAE server (202), a collision data analytics subscription request; wherein receiving (218) the analytics data for collision detection comprises receiving a collision data analytics subscription notification comprising the collision detection analytics data.

[0098] Embodiment 24: The method of any of embodiments 20 to 22, further comprising: sending (300), to the ADAE server (202), a collision data analytics request; wherein receiving (304) the analytics data for collision detection comprises receiving (304), from the ADAE server (202), a collision data analytics response comprising the analytics data for collision detection.

[0099] Embodiment 25: An analytics consumer (204; 402) adapted to perform the method of any of embodiments 20 to 24.

[0100] Embodiment 26: A network node (500) for implementing an analytics consumer (204; 402), the network node (500) comprising processing circuitry configured to cause the network node (500) to perform the method of any of embodiments 20 to 24.

Claims

Claims1. A method performed by an Analytics Data Analytics Enablement, ADAE, server (202), the method comprising: obtaining (210-214) ranging and / or sidelink positioning data of one or more User Equipments, UEs, and location information for objects and / or UEs, from one or more data producers (200); deriving (216) analytics data for collision detection of at least one of the one or more UEs, based on the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs; and providing (218; 304) the analytics data for collision detection to a consumer (204).

2. The method of claim 1, wherein the one or more data producers (200) comprise any one or more of the following: one or more network functions in a core network of a wireless communication system; an ADAE client; a Service Enabler Architecture Layer for Verticals, SEAL, location management server; a SEAL location management client; a 3rdparty location management server; an Application layer Analytical Data Repository Function, A-ADRF.

3. The method of claim 1, wherein the one or more data producers (200) comprise any two or more of the following: one or more network functions in a core network of a wireless communication system; an ADAE client; a Service Enabler Architecture Layer for Verticals, SEAL, location management server; a SEAL location management client; a 3rdparty location management server; an Application layer Analytical Data Repository Function, A-ADRF.

4. The method of any of claims 1 to 3, wherein obtaining (210-214) the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs comprises, for each data producer (200) of the one or more data producers (200): sending (210), to the data producer (200), a subscription request; and receiving (212), from the data producer (200), at least some of the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs.

5. The method of claim 4, wherein the subscription request comprises any one or more of the following information elements: information that identifies the consumer (204); information that identifies a data collection event; information that indicates one or more requirements for collection of the ranging and / or sidelink positioning data of the one or more UEs and / or the location information for objects and / or UEs; information that identifies an associated analytics event; a list of data producer identifiers; information that indicates one or more characteristics of data producers to be used for the subscription request; a list of Vertical Application Layer, VAL, UE identifiers for which the requested data or analytics applies; information that indicates a geographical area of interest; information that indicates a validity time for the subscription request.

6. The method of any of claims 1 to 5, wherein the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs comprises any one or more of the following: ranging and / or sidelink positioning data of the one or more UEs; location information of UEs; location information of one or more static objects for a given time and area of interest;relative proximity analytics for the one or more UEs in relation to one or more other UEs and / or one or more static objects.

7. The method of any of claims 1 to 6, further comprising: receiving (206; 300), from the consumer (204), a collision data analytics subscription request; wherein providing (218; 304) the analytics data for collision detection to the consumer (204) comprises providing (218; 304), to the consumer (204), a collision data analytics notification or a collision data analytics response comprising the analytics data for collision detection.

8. The method of claim 7, wherein the collision data analytics subscription request or the collision data analytics request comprises any one or more of the following information elements: information that indicates the one or more UEs; information that indicates a Vertical Application Layer, VAL, server to which the request applies; information that indicates one or more attributes for collision detection, which includes any one or more of the following information elements: minimum distance between UEs or between UEs and objects; maximum velocity of UEs; an expected direction of UEs and / or moving objects; a movement track of UEs and / or moving objects; a granularity of the movement track.

9. The method of any of claims 1 to 8, wherein the analytics data for collision detection comprises any one or more of the following information elements: information that identifies one or more UEs to which the analytics data applies; information that indicates one or more times of potential collision(s) between UEs or between UE(s) and object(s); a confidence level(s) of the potential collision(s).

10. An Analytics Data Analytics Enablement, ADAE, server (202) adapted toobtain (210-214) ranging and / or sidelink positioning data of one or more User Equipments, UEs, and location information for objects and / or UEs, from one or more data producers (200); derive (216) analytics data for collision detection of at least one of the one or more UEs, based on the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs; and provide (218; 304) the analytics data for collision detection to a consumer (204).

11. The ADAE server (202) of claim 10, further adapted to perform the method of any of claims 2 to 9.

12. A network node (500) for implementing an Analytics Data Analytics Enablement, ADAE, server (202), the network node (500) comprising processing circuitry (504; 604) configured to cause the network node (500) to: obtain (210-214) ranging and / or sidelink positioning data of one or more User Equipments, UEs, and location information for objects and / or UEs, from one or more data producers (200); derive (216) analytics data for collision detection of at least one of the one or more UEs, based on the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs; and provide (218; 304) the analytics data for collision detection to a consumer (204).

13. The network node (500) of claim 12, wherein the processing circuitry (504; 604) is further configured to cause the network node (500) to perform the method of any of claims 2 to 9.

14. A method performed by a data producer (200), the method comprising: providing (214) at least one of ranging and / or sidelink positioning data of one or more User Equipments, UEs, and location information for objects and / or UEs, to an Analytics Data Analytics Enablement, ADAE, server (202) to be used to derive collision detection analytics.

15. The method of claim 14, wherein the data producer (200) is any one or more of the following: one or more network functions in a core network of a wireless communication system; an ADAE client; a Service Enabler Architecture Layer for Verticals, SEAL, location management server; a SEAL location management client; a 3rdparty location management server; an Application layer Analytical Data Repository Function, A-ADRF.

16. The method of any of claims 14 to 15, wherein providing (214) the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs comprises: receiving (210), from the ADAE server (202), a subscription request; and sending (214), to the ADAE server (202), a subscription notification(s) comprising the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs.

17. The method of claim 16, wherein the subscription request comprises any one or more of the following information elements: information that identifies the consumer (204); information that identifies a data collection event; information that indicates one or more requirements for collection of the ranging and / or sidelink positioning data of the one or more UEs and / or the location information for objects and / or UEs; information that identifies an associated analytics event; a list of data producer identifiers; information that indicates one or more characteristics of data producers to be used for the subscription request; a list of Vertical Application Layer, VAL, UE identifiers for which the requested data or analytics applies; information that indicates a geographical area of interest;information that indicates a validity time for the subscription request.

18. The method of any of claims 14 to 17, wherein the ranging and / or sidelink positioning data of the one or more UEs and the location information for objects and / or UEs comprises any one or more of the following: ranging and / or sidelink positioning data of the one or more UEs; location information of UEs; location information of one or more static objects for a given time and area of interest; relative proximity analytics for the one or more UEs in relation to one or more other UEs and / or one or more static objects.

19. A data producer (200) adapted to: provide (214) ranging and / or sidelink positioning data of one or more User Equipments, UEs, and location information for objects and / or UEs, to an Analytics Data Analytics Enablement, ADAE, server (202).

20. The data producer (200) of claim 19, further adapted to perform the method of any of claims 15 to 18.

21. A network node (500) for implementing a data producer (200), the network node (500) comprising processing circuitry (504; 604) configured to cause the network node (500) to: provide (214) ranging and / or sidelink positioning data of one or more User Equipments, UEs, and location information for objects and / or UEs, to an Analytics Data Analytics Enablement, ADAE, server (202).

22. The network node (500) of claim 21, wherein the processing circuitry (504; 604) is further configured to cause the network node (500) to perform the method of any of claims 15 to 18.

23. A method performed by an analytics consumer (204; 402), the method comprising:receiving (218; 304) collision detection analytics data for one or more User Equipments, UEs, from an Analytics Data Analytics Enablement, ADAE, server (202) in response to sending a request that comprises attributes for collision detection to be applied when generating collision detection analytics data.

24. The method of claim 23, wherein the attributes for collection detection comprise any one or more of the following: distance, velocity, direction, movement track, and granularity.

25. The method of claim 23 or 24, further comprising performing (406) one or more operations based on the collision detection analytics data.

26. The method of any of claims 23 to 25, wherein the collision detection analytics data comprises any one or more of the following: information that identifies one or more UEs; information that indicates one or more times of potential collision(s) between UEs or between UE(s) and object(s); a confidence level(s) of the potential collision(s).

27. The method of any of claims 23 to 26, wherein the request is a collision data analytics subscription request; and receiving (218) the analytics data for collision detection comprises receiving a collision data analytics subscription notification comprising the collision detection analytics data.

28. The method of any of claims 23 to 26, wherein: the request is a collision data analytics request; and receiving (304) the analytics data for collision detection comprises receiving (304), from the ADAE server (202), a collision data analytics response comprising the analytics data for collision detection.

29. An analytics consumer (204; 402) adapted to:receive (218; 304) collision detection analytics data for one or more User Equipments, UEs, from an Analytics Data Analytics Enablement, ADAE, server (202) in response to sending a request that comprises attributes for collision detection to be applied when generating collision detection analytics data.

30. The analytics consumer (204; 402) of claim 29 further adapted to perform the method of any of claims 24 to 28.

31. A network node (500) for implementing an analytics consumer (204; 402), the network node (500) comprising processing circuitry configured to cause the network node (500) to: receive (218; 304) collision detection analytics data for one or more User Equipments, UEs, from an Analytics Data Analytics Enablement, ADAE, server (202) in response to sending a request that comprises attributes for collision detection to be applied when generating collision detection analytics data.

32. The network node of claim 31, wherein the processing circuitry is further configured to cause the network node to perform the method of any of claims 24 to 28.

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