Interaction and interoperation of analytics functions in wireless communication network

Abstract

An apparatus is provided that includes a receiver, a processor, and a transmitter. The receiver is arranged to receive a first analysis request from a consumer. The processor is arranged to determine that a counterpart analysis from the counterpart functionality is required to serve the first analysis request. The transmitter is arranged to transmit a counterpart analysis request to a counterpart function. The receiver is further arranged to receive a response to the counterpart analysis request from the counterpart function. The processor is further arranged to prepare an analysis response using the counterpart analysis. The transmitter is further arranged to transmit the analysis response to the consumer.

Description

Technical Field

[0001] The subject matter disclosed herein generally relates to the field of interaction and interoperation of analysis functions in wireless communication networks.This document defines an apparatus, a method in an apparatus, a central node, a method in a central node, a counterpart node, and a method in a counterpart node. Background Art

[0002] Data analytics in 3GPP are used in the control plane, management plane, and application support plane. In the control plane, the network data analysis function (NWDAF) mainly focuses on (multiple) UEs, sessions, interactions with applications and services, while the management data analysis (MDA) in the management plane focuses on resource management and network optimization. In addition, in the application support plane, the application data analysis support server (ADAES) focuses on application server / session analysis and edge analysis.

[0003] These analyses can complement each other. For example, the service experience analysis ID (3GPP TS23.288 v17.5.0) in the NWDAF relies on RAN performance analysis, or the slice load level analysis ID (3GPP TS23.288 v17.5.0) relies on network slice throughput and network slice service prediction (3GPP TS28.104 v17.0.1), which can be provided from the MDA. Similarly, MDA analyses such as SLS analysis (3GPP TS28.104 v17.0.1) require quality of experience (QoE) or UE mobility analysis (3GPP TS23.288 v17.5.0). Another example is the derivation of application layer performance analysis (3GPP TR23.700-36 v0.4.0), which takes NWDAF and MDA analyses related to quality of service (QoS) and performance management (PM) data as input.

[0004] In US2021 / 0083956 A1, a method for obtaining information and interacting between NWDAF and other 5G core network functions (NFs) is proposed. In US 2021 / 0021494A1, a method for MDA considering the consumption of various data sources is proposed, focusing on enhancing self-organizing network (SON) functions. Summary of the invention

[0005] When an analysis function receives a consumer request associated with an analysis ID that relies on the output results of another analysis ID from an inter-plane analysis function, i.e., the NWDAF requires the MDAF analysis ID output as input data and vice versa, a method is provided that tends to: (i) identify the appropriate inter-plane analysis function based on the desired capabilities that need to be analyzed and determined considering the capabilities contained in the original consumer request, (ii) derive analysis attributes, and automatically formulate a new analysis request to the corresponding counterpart plane analysis function. The analysis ID information element is used to identify the type of supported analysis provided by the analysis function. The term inter-plane analysis refers to the exchange of analysis information between NFs (e.g., NWDAF, MDA, ADAES) residing in different network planes or network domains. A network plane or network domain refers to a technical domain, such as 5G core, radio, network management, and / or it also refers to an administrative domain, such as a domain that allows network operators to divide the network into smaller parts for easier control and management. The terms MDA, MDAF, and MDAS are used interchangeably in this document and have the same meaning, i.e., identifying an administrative analysis function. The term MDA MnS Producer refers to the capability of the MDAF to produce analytics, and MDA MnS Consumer refers to the capability of the MDAF to consume 5C NF services and / or application support services and / or management services.

[0006] Disclosed herein is a process for interaction and interoperation of analysis functions in a wireless communication network. The above process can be implemented by an apparatus, a method in an apparatus, a central node, a method in a central node, a counterpart node, and a method in a counterpart node.

[0007] Therefore, a device is provided, which includes a receiver, a processor and a transmitter. The receiver is arranged to receive a first analysis request from a consumer. The processor is arranged to determine that a counterparty analysis from a counterparty function is required to service the first analysis request. The transmitter is arranged to send the counterparty analysis request to the counterparty function. The receiver is also arranged to receive a response to the counterparty analysis request from the counterparty function. The processor is also arranged to prepare an analysis response using the counterparty analysis. The transmitter is also arranged to send the analysis response to the consumer.

[0008] A method in an apparatus is also provided, the method comprising: receiving a first analysis request from a consumer; determining that a counterpart analysis from a counterpart function is required to service the first analysis request; and sending the counterpart analysis request to the counterpart function. The method also includes receiving a response to the counterpart analysis request from the counterpart function; preparing an analysis response using the counterpart analysis; and sending the analysis response to the consumer.

[0009] A central node is also provided, the central node comprising a receiver and a transmitter. The receiver is arranged to receive capability information from a plurality of opposite party nodes, the capability information defining the opposite party node's capability to generate an opposite party analysis. The receiver is further arranged to receive a request for capability information from a device. The transmitter is arranged to send a capability report in response to the request.

[0010] A method in a central node is also provided, the method comprising: receiving capability information from a plurality of counterpart nodes, the capability information defining the capability of the counterpart nodes to generate counterpart analysis; receiving a request for capability information from a device; and sending a capability report in response to the request.

[0011] There is also provided a counterpart node comprising a transmitter arranged to send capability information to a central node, the capability information defining a capability of the counterpart node to generate a counterpart analysis.

[0012] A method in a counterpart node is also provided, the method comprising sending capability information to a central node, the capability information defining a capability of the counterpart node to generate a counterpart analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to describe the manner in which the advantages and features of the present disclosure can be obtained, the present disclosure is described by reference to certain devices and methods shown in the accompanying drawings. Each of these drawings depicts only certain aspects of the present disclosure and should not be considered as limiting the scope thereof. For the sake of clarity, the drawings may have been simplified and are not necessarily drawn to scale.

[0014] Methods and apparatus for interaction and interoperation of analysis functions in a wireless communication network will now be described, by way of example only, with reference to the accompanying drawings, in which:

[0015] Figure 1 An embodiment of a wireless communication system for implementing interaction and interoperation of analysis functions in a wireless communication network as described herein is depicted;

[0016] Figure 2 The functional overview and interaction of MDA and NWDAF are shown;

[0017] Figure 3 depicts a user equipment device that may be used to implement the methods described herein;

[0018] Figure 4 depicts further details of a network node that may be used to implement the methods described herein;

[0019] Figure 5 The method in the apparatus is illustrated;

[0020] Figure 6 The method in the central node is illustrated;

[0021] Figure 7 The diagram shows the method in the other node;

[0022] Figure 8 An inter-plane analysis example is illustrated showing an analysis consumer requesting analysis from a receiving analysis function residing in a different domain;

[0023] Fig. 9 A flow chart of an inter-plane analysis request and response method is presented; and

[0024] Fig.10 The inter-plane analysis method between ADAES and 3GPP domain analysis is illustrated. DETAILED DESCRIPTION

[0025] Those skilled in the art will appreciate that aspects of the present disclosure may be embodied as systems, devices, methods or program products. Therefore, the arrangements described herein may be implemented in full hardware form, full software form (including firmware, resident software, microcode, etc.), or in a combination of software and hardware aspects.

[0026] For example, the disclosed methods and apparatus may be implemented as hardware circuits, including custom very large scale integrated (VLSI) circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. The disclosed methods and apparatus may also be implemented in programmable hardware devices, such as field programmable gate arrays, programmable array logic, programmable logic devices, etc. As another example, the disclosed methods and apparatus may include one or more physical or logical blocks of executable code, which may be organized, for example, as objects, procedures, or functions.

[0027] In addition, the method and apparatus may take the form of a program product embodied in one or more computer-readable storage devices storing machine-readable code, computer-readable code, and / or program code, hereinafter referred to as code. The storage device may be tangible, non-transitory, and / or non-transmitting. The storage device may not embody a signal. In some arrangements, the storage device uses only a signal for accessing the code.

[0028] Any combination of one or more computer readable media may be used. The computer readable medium may be a computer readable storage medium. The computer readable storage medium may be a storage device storing code. The storage device may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, holographic, micromechanical or semiconductor system, device or apparatus, or any suitable combination of the above.

[0029] More specific examples of storage devices (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the context of this document, a computer-readable storage medium may be any tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0030] In this specification, references to examples or similar language of a particular method or device indicate that the specific features, structures or characteristics described in conjunction with the example are included in at least one implementation of the methods and devices described herein. Therefore, unless otherwise expressly provided, references to examples or similar language features of a particular method or device may, but do not necessarily, all refer to the same example, but to "one or more but not all examples". Unless otherwise expressly provided, the terms "including", "comprising", "having" and their variations mean "including but not limited to". Unless otherwise expressly provided, a list of items listed does not mean that any or all items are mutually exclusive. Unless otherwise expressly provided, the terms "a", "an" and "the" also mean "one or more".

[0031] As used herein, a list with the conjunction "and / or" includes any single item in the list or a combination of items in the list. For example, a list of A, B, and / or C includes only A, only B, only C, a combination of A and B, a combination of B and C, a combination of A and C, or a combination of A, B, and C. As used herein, a list using the term "one or more of ..." includes any single item in the list or a combination of items in the list. For example, one or more of A, B, and C includes only A, only B, only C, a combination of A and B, a combination of B and C, a combination of A and C, or a combination of A, B, and C. As used herein, a list using the term "one of ..." includes one and only one of any single item in the list. For example, "one of A, B, and C" includes only A, only B, or only C, and does not include a combination of A, B, and C. As used herein, "a member selected from A, B, and C" includes one and only one of A, B, or C, and does not include a combination of A, B, and C. As used herein, "a member selected from A, B and C and combinations thereof" includes only A, only B, only C, a combination of A and B, a combination of B and C, a combination of A and C, or a combination of A, B and C.

[0032] In addition, the features, structures or characteristics described herein may be combined in any suitable manner. In the following description, many specific details are provided, such as examples of programming, software modules, user selections, network transactions, database queries, database structures, hardware modules, hardware circuits, hardware chips, etc., to provide a comprehensive understanding of the present disclosure. However, those skilled in the relevant art will recognize that the disclosed methods and apparatus may be practiced without one or more of the specific details, or may be practiced using other methods, components, materials, etc. In other cases, well-known structures, materials or operations are not shown or described in detail to avoid confusing aspects of the present disclosure.

[0033] The following is a description of various aspects of the disclosed method and apparatus with reference to schematic flow charts and / or schematic block diagrams of methods, apparatuses, systems, and program products. It will be understood that each block of the schematic flow charts and / or schematic block diagrams and the combination of blocks in the schematic flow charts and / or schematic block diagrams can be implemented by code. The code can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine, so that instructions executed by a processor of a computer or other programmable data processing device can create a component for implementing the function / action specified in the schematic flow charts and / or schematic block diagrams.

[0034] The code may also be stored in a storage device that can instruct a computer, other programmable data processing apparatus, or other device to work in a specific manner so that the instructions stored in the storage device produce an article of manufacture that includes instructions for implementing the functions / actions specified in the schematic flowchart and / or schematic block diagram.

[0035] The code may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are executed on the computer, other programmable apparatus, or other device, thereby producing a computer-implemented process, so that the code executed on the computer or other programmable apparatus provides a process for implementing the functions / actions specified in the schematic flowchart and / or schematic block diagram.

[0036] The schematic flow charts and / or schematic block diagrams in the figure illustrate the possible implementation architectures, functions and operations of the device, system, method and program product. In this regard, each block in the schematic flow chart and / or schematic block diagram can represent a code module, segment or portion, which includes one or more executable instructions for implementing the code of (multiple) specified logical functions.

[0037] It should also be noted that in some alternative implementations, the functions shown in the blocks may not appear in the order shown in the figures. For example, two blocks shown in succession may in fact be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order, depending on the functions involved. Other steps and methods are contemplated that are equivalent in function, logic or effect to one or more blocks or portions thereof of the illustrated figures.

[0038] The description of the elements in each figure can refer to the elements in the subsequent figures. The same numbers represent the same elements in all figures.

[0039] Figure 1 An embodiment of a wireless communication system 100 for implementing interaction and interoperation of analysis functions in a wireless communication network is depicted. In one embodiment, the wireless communication system 100 includes a remote unit 102 and a network unit 104. Although Figure 1 A specific number of remote units 102 and network units 104 are depicted in the wireless communication system 100, but those skilled in the art will recognize that any number of remote units 102 and network units 104 may be included in the wireless communication system 100. The remote unit 102 may be a user equipment device 300, a consumer 210, or an analysis consumer 810, 910, 1010 as described herein. The network unit 104 may include a network node 400, a consumer 210, an analysis consumer 810, 910, 1010, a receiving side analysis function 820, 920, an analysis function 870, an inter-plane analysis function 940, a centralized server 950, other data sources 960, and an ADAES 1020 as described herein.

[0040] In one embodiment, the remote unit 102 may include a computing device such as a desktop computer, a laptop computer, a personal digital assistant (PDA), a tablet computer, a smart phone, a smart TV (e.g., a TV connected to the Internet), a set-top box, a game console, a security system (including a security camera), a vehicle computer, a network device (e.g., a router, a switch, a modem), an aircraft, a drone, etc. In some embodiments, the remote unit 102 includes a wearable device such as a smart watch, a fitness band, an optical head-mounted display, etc. In addition, the remote unit 102 may be referred to as a subscriber unit, a mobile station, a mobile station, a user, a terminal, a mobile terminal, a fixed terminal, a subscriber station, a UE, a user terminal, a device, or other terms used in the art. The remote unit 102 may communicate directly with one or more of the network units 104 via UL communication signals. In some embodiments, the remote unit 102 may communicate directly with other remote units 102 via sidelink communication.

[0041] The network elements 104 may be distributed over a geographic area. In some embodiments, the network elements 104 may also be referred to as access points, access terminals, base stations, base stations, node Bs, eNBs, gNBs, home node Bs, relay nodes, devices, core networks, air servers, radio access nodes, APs, NRs, network entities, access and mobility management functions (AMFs), unified data management functions (UDMs), unified data repositories (UDRs), UDM / UDRs, policy control functions (PCFs), radio access networks (RANs), network slice selection functions (NSSFs), or other terms used in the art. The network elements 104 are typically part of a radio access network that includes one or more controllers that are communicatively coupled to one or more corresponding network elements 104. The radio access network is typically communicatively coupled to one or more core networks that may be coupled to other networks, such as the Internet and a public switched telephone network, among others. These and other elements of the radio access network and the core network are not shown, but are generally well known to those of ordinary skill in the art.

[0042] In one implementation, the wireless communication system 100 complies with the New Radio (NR) protocol standardized in 3GPP, wherein the network unit 104 transmits on the downlink (DL) using an orthogonal frequency division multiple access (OFDM) modulation scheme, and the remote unit 102 transmits on the uplink (UL) using a single carrier frequency division multiple access (SC-FDMA) scheme or an OFDM scheme. More generally, however, the wireless communication system 100 may implement some other open or proprietary communication protocol, such as WiMAX, IEEE 802.11 variants, GSM, GPRS, UMTS, LTE variants, CDMA2000, ZigBee, Sigfoxx, etc. The present disclosure is not intended to be limited to any particular wireless communication system architecture or protocol implementation.

[0043] The network unit 104 can serve a number of remote units 102 within a service area (eg, a cell or cell sector) via wireless communication links. The network unit 104 sends DL communication signals to serve the remote units 102 in the time, frequency, and / or spatial domains.

[0044] Data analytics in 3GPP are used in the control plane, management plane, and application support plane. In the control plane, the network data analysis function (NWDAF) mainly focuses on (multiple) UEs, sessions, interactions with applications and services, while the management data analysis (MDA) in the management plane focuses on resource management and network optimization. In addition, in the application support plane, the application data analysis support server (ADAES) focuses on application server / session analysis and edge analysis.

[0045] These analyses can complement each other. For example, the service experience analysis ID (3GPP TS23.288 v17.5.0) in the NWDAF relies on RAN performance analysis, or the slice load level analysis ID (3GPP TS23.288 v17.5.0) relies on network slice throughput and network slice service prediction (3GPP TS28.104 v17.0.1), which can be provided from the MDA. Similarly, MDA analyses such as SLS analysis (3GPP TS28.104 v17.0.1) require quality of experience (QoE) or UE mobility analysis (3GPP TS23.288 v17.5.0). Another example is the derivation of application layer performance analysis (3GPP TR23.700-36 v0.4.0), which takes NWDAF and MDAF analyses related to quality of service (QoS) and PM data as input.

[0046] Figure 2 The functional overview and interaction of MDA and NWDAF are shown. The figure illustrates how the Management Data Analysis Function (MDA Function) interacts with the Network Data Analysis Function (NWDAF) and exchanges data as input and output via the Service Based Architecture (SBA) and Service Based Management Architecture (SBMA).

[0047] The Service Based Architecture (SBA) enables NWDAF to: (i) subscribe to MDA Management Service (MnS) producers (MDA functions that generate analytics), and (ii) provide NWDAF analytics outputs to MDA MnS consumers (which may be management functions that include MDA functions that generate analytics). The Service Based Management Architecture (SBMA) enables: (i) MDA MnS producers to provide analytics to NWDAF, and (ii) MDA MnS consumers to subscribe to NWDAF.

[0048] Figure 2 An MDA MnS consumer 210, an MDA function 220, another MDA MnS producer 230, a MnS producer 235, an NWDAF 240, an LMF 250, and a non-3GPP management system 260 are shown. Each of the MDA MnS consumer 210, another MDA MnS producer 230, a MnS producer 235, an NWDAF 240, an LMF 250, and a non-3GPP management system 260 communicates with the MDA function 220 via a respective interface. The MDA function 220 includes an MDA internal business logic 225.

[0049] When a consumer of NWDAF or MDA makes a request, it specifies certain requirements regarding when the analysis report should be provided, including the area of ​​interest, target UE or network object (e.g., NF), time schedule, event conditions (e.g., when NF load exceeds a given threshold), etc.

[0050] The provision of analytics can rely on the output of other analytics services or analytics functions from different technical domains, known as inter-plane analytics or cross-domain analytics. The terms inter-plane, cross-domain, and opposite-plane are used interchangeably in this document.

[0051] Inter-plane analysis may be defined as a first analysis service that requires input from a second analysis service, where the first analysis service and / or the second analysis service is a NWDAF, MDAS, ADAES service or a combination thereof. In the context of this document, inter-plane analysis is considered to reside within a single PLMN and is used without roaming considerations.

[0052] If inter-plane analysis is required, i.e., when an NWDAF analysis ID request depends on an MDA output or vice versa, the consumer request at the receiving analysis function should introduce a subsequent subscription to the appropriate inter-plane analysis counterpart function. However, there is currently no method for automatically performing this operation. The requirements of the analysis request are only explicitly stated by the consumer and cannot be derived based on the analysis request after it is received by the analysis function. A typical example is as follows:

[0053] NWDAF analysis ID = "Network Performance" (3GPP TS23.288v17.5.0) relies on: (i) OAM statistics of RAN status (up / down) which can be obtained from MDA analysis ID = "CoverageAnalytics.CoverageProblemAnalysis" (3GPP TS28.104v17.0.1), and (ii) load (i.e., radio resource utilization) which can be obtained from MDA analysis ID = "SLSAnalysis.NetworkSliceTrafficAnalysisNetwork" (3GPP TS28.104v170.1).

[0054] MDA analysis ID = "MDAAssistedFaultManagement.FailurePrediction" (3GPPTS28.104v17.0.1) depends on NWDAF analysis ID = "Service Experience" (3GPP TS23.288v17.5.0) to obtain control plane analysis insights.

[0055] The receiving analysis function cannot issue subsequent requests based on the initial request received from the consumer because there are two main gaps: (i) deriving the analysis requirements in order to formulate a new analysis request to the analysis function on the other side, and (ii) identifying the appropriate analysis function on the other side that is responsible for providing the supplemental analysis.

[0056] These two processes are interrelated because the choice of a planar analysis function will affect (ie, introduce upper limits) capabilities related to the requirements for deriving new analysis requests for that opposing planar analysis function (eg, region of interest or time schedule).

[0057] Another example of considering inter-plane analysis of the application support plane involves the following analysis services provided by ADAE (as described in 3GPP TR 23.700-36v0.4.0). As shown in Table 1 below, some application layer analysis services use NWDAF analysis or MDAF analysis as input. In addition, the consumer of such analysis from ADAES can also be NWDAF (for example, for DN performance analysis, NWDAF can receive statistics from ADAES (acting as AF) instead of receiving raw service experience data).

[0058] The use cases listed below require inter-plane or cross-domain analytics interactions and raise some issues related to the coordination required between analytics functions to ensure that consumer requirements are met for a given area of ​​interest or UE and time frame.

[0059] This document defines a solution that tends to facilitate configuration and coordination of input parameters for requesting inter-plane analysis services to ensure that consumer requirements are met. In addition, certain arrangements presented herein facilitate selection of appropriate inter-plane analysis functions to provide input to the analysis service. In addition, a solution is provided that tends to coordinate parameters for inter-plane analysis services, such as timing and coverage parameters, etc.

[0060]

[0061] Table 1: Application data analysis support analysis services

[0062] Figure 3A user equipment device 300 is depicted that can be used to implement the methods described herein. The user equipment device 300 is used to implement one or more of the solutions described herein. The user equipment device 300 conforms to one or more of the user equipment devices described in the embodiments herein. The user equipment device 300 can be a remote unit 102, other data source 960, ADAES 1020, consumer 210, or analysis consumer 810, 910, 1010 as described herein. The user equipment device 300 includes a processor 305, a memory 310, an input device 315, an output device 320, and a transceiver 325.

[0063] The input device 315 and the output device 320 may be combined into a single device, such as a touch screen. In some implementations, the user equipment apparatus 300 does not include any input device 315 and / or output device 320. The user equipment apparatus 300 may include one or more of a processor 305, a memory 310, and a transceiver 325, and may not include an input device 315 and / or an output device 320.

[0064] As shown, the transceiver 325 includes at least one transmitter 330 and at least one receiver 335. The transceiver 325 can communicate with one or more cells (or wireless coverage areas) supported by one or more base units. The transceiver 325 can be operable on an unlicensed spectrum. In addition, the transceiver 325 can include multiple UE panels supporting one or more beams. In addition, the transceiver 325 can support at least one network interface 340 and / or application interface 345. (Multiple) application interface 345 can support one or more APIs. (Multiple) network interface 340 can support 3GPP reference points, such as Uu, N1, PC5, etc. As understood by those of ordinary skill in the art, other network interfaces 340 can be supported.

[0065] The processor 305 may include any known controller capable of executing computer-readable instructions and / or capable of performing logical operations. For example, the processor 305 may be a microcontroller, a microprocessor, a central processing unit (CPU), a graphics processing unit (GPU), an auxiliary processing unit, a field programmable gate array (FPGA), or a similar programmable controller. The processor 305 may execute instructions stored in the memory 310 to perform the methods and routines described herein. The processor 305 is communicatively coupled to the memory 310, the input device 315, the output device 320, and the transceiver 325.

[0066] Processor 305 may control user equipment device 300 to implement user equipment device behaviors described herein. Processor 305 may include an application processor (also referred to as a main processor) that manages application domain and operating system (OS) functions and a baseband processor (also referred to as a baseband radio processor) that manages radio functions.

[0067] The memory 310 may be a computer-readable storage medium. The memory 310 may include a volatile computer storage medium. For example, the memory 310 may include a RAM, including a dynamic RAM (DRAM), a synchronous dynamic RAM (SDRAM), and / or a static RAM (SRAM). The memory 310 may include a non-volatile computer storage medium. For example, the memory 310 may include a hard drive, a flash memory, or any other suitable non-volatile computer storage device. The memory 310 may include both volatile and non-volatile computer storage media.

[0068] The memory 310 may store data related to implementing the traffic class field as described herein. The memory 310 may also store program code and related data, such as an operating system or other controller algorithms operating on the device 300.

[0069] Input device 315 may include any known computer input device, including a touchpad, buttons, keyboard, stylus, microphone, etc. Input device 315 may be integrated with output device 320, for example, as a touch screen or similar touch-sensitive display. Input device 315 may include a touch screen so that text can be entered using a virtual keyboard displayed on the touch screen and / or by handwriting on the touch screen. Input device 315 may include two or more different devices, such as a keyboard and a touchpad.

[0070] The output device 320 may be designed to output visual, auditory and / or tactile signals. The output device 320 may include an electronically controllable display or display device capable of outputting visual data to a user. For example, the output device 320 may include, but is not limited to, a liquid crystal display (LCD), a light emitting diode (LED) display, an organic LED (OLED) display, a projector, or a similar display device capable of outputting images, text, etc. to a user. As another non-limiting example, the output device 320 may include a wearable display that is separate from the rest of the user device apparatus 300 but communicatively coupled, such as a smart watch, smart glasses, a head-up display, etc. In addition, the output device 320 may be a component of a smart phone, a personal digital assistant, a television, a desktop computer, a notebook (laptop) computer, a personal computer, a vehicle dashboard, etc.

[0071] Output device 320 may include one or more speakers for producing sound. For example, output device 320 may produce an audible alarm or notification (e.g., a beep or buzzer). Output device 320 may include one or more tactile devices for producing vibration, motion, or other tactile feedback. All or part of output device 320 may be integrated with input device 315. For example, input device 315 and output device 320 may form a touch screen or similar touch-sensitive display. Output device 320 may be located near input device 315.

[0072] The transceiver 325 communicates with one or more network functions of the mobile communication network via one or more access networks. The transceiver 325 operates under the control of the processor 305 to send messages, data and other signals, and also receives messages, data and other signals. For example, the processor 305 can selectively activate the transceiver 325 (or part thereof) at a specific time to send and receive messages.

[0073] The transceiver 325 includes at least one transmitter 330 and at least one receiver 335. One or more transmitters 330 can be used to provide uplink communication signals to a base unit of a wireless communication network. Similarly, one or more receivers 335 can be used to receive downlink communication signals from the base unit. Although only one transmitter 330 and one receiver 335 are shown, the user equipment device 300 can have any suitable number of transmitters 330 and receivers 335. In addition, (multiple) transmitters 330 and (multiple) receivers 335 can be any suitable type of transmitter and receiver. The transceiver 325 may include a first transmitter / receiver pair for communicating with a mobile communication network through a licensed radio spectrum, and a second transmitter / receiver pair for communicating with a mobile communication network through an unlicensed radio spectrum.

[0074] A first transmitter / receiver pair that can be used to communicate with a mobile communication network via a licensed radio spectrum and a second transmitter / receiver pair that can be used to communicate with a mobile communication network via an unlicensed radio spectrum can be combined into a single transceiver unit, such as a single chip that performs functions for use with both licensed and unlicensed radio spectrums. The first transmitter / receiver pair and the second transmitter / receiver pair can share one or more hardware components. For example, some transceivers 325, transmitters 330, and receivers 335 can be implemented as physically independent components that access shared hardware resources and / or software resources, such as a network interface 340.

[0075] One or more transmitters 330 and / or one or more receivers 335 may be implemented and / or integrated into a single hardware component, such as a multi-transceiver chip, a system on chip, an application specific integrated circuit (ASIC), or other types of hardware components. One or more transmitters 330 and / or one or more receivers 335 may be implemented and / or integrated into a multi-chip module. Other components such as a network interface 340 or other hardware components / circuits may be integrated into a single chip with any number of transmitters 330 and / or receivers 335. Transmitters 330 and receivers 335 may be logically arranged as transceivers 325 using one or more common control signals, or may be arranged as modular transmitters 330 and receivers 335 implemented in the same hardware chip or multi-chip module.

[0076] Figure 4 400, which can be used to implement the methods described herein. The network node 400 may include a consumer 210, an analysis consumer 810, 910, 1010, a receiver analysis function 820, 920, an analysis function 870, an inter-plane analysis function 940, a centralized server 950, other data sources 960, or an ADAES 1020 as described herein. The network node 400 includes a processor 405, a memory 410, an input device 415, an output device 420, and a transceiver 425.

[0077] Input device 415 and output device 420 may be combined into a single device. In some implementations, network node 400 does not include any input device 415 and / or output device 420. Network node 400 may include one or more of processor 405, memory 410, and transceiver 425, and may not include input device 415 and / or output device 420.

[0078] As shown, the transceiver 425 includes at least one transmitter 430 and at least one receiver 435. Here, the transceiver 425 communicates with one or more remote units 200. In addition, the transceiver 425 can support at least one network interface 440 and / or application interface 445. (Multiple) application interface 445 can support one or more APIs. (Multiple) network interface 440 can support 3GPP reference points such as Uu, N1, N2 and N3. As understood by those of ordinary skill in the art, other network interfaces 440 can be supported.

[0079] The processor 405 may include any known controller capable of executing computer-readable instructions and / or capable of performing logical operations. For example, the processor 405 may be a microcontroller, a microprocessor, a CPU, a GPU, an auxiliary processing unit, an FPGA, or a similar programmable controller. The processor 405 may execute instructions stored in the memory 410 to perform the methods and routines described herein. The processor 405 is communicatively coupled to the memory 410, the input device 415, the output device 420, and the transceiver 425.

[0080] Memory 410 may be a computer-readable storage medium. Memory 410 may include volatile computer storage media. For example, memory 410 may include RAM, including dynamic RAM (DRAM), synchronous dynamic RAM (SDRAM) and / or static RAM (SRAM). Memory 410 may include non-volatile computer storage media. For example, memory 410 may include a hard drive, flash memory, or any other suitable non-volatile computer storage device. Memory 410 may include both volatile and non-volatile computer storage media.

[0081] The memory 410 may store data related to establishing a multipath unicast link and / or mobile operation. For example, as described herein, the memory 410 may store parameters, configurations, resource allocations, policies, etc. The memory 410 may also store program code and related data, such as an operating system or other controller algorithms operating on the network node 400.

[0082] Input device 415 may include any known computer input device, including a touchpad, buttons, keyboard, stylus, microphone, etc. Input device 415 may be integrated with output device 420, for example, as a touch screen or similar touch-sensitive display. Input device 415 may include a touch screen so that text can be entered using a virtual keyboard displayed on the touch screen and / or by handwriting on the touch screen. Input device 415 may include two or more different devices, such as a keyboard and a touchpad.

[0083] Output device 420 can be designed to output visual, auditory and / or tactile signals. Output device 420 may include an electronically controllable display or display device capable of outputting visual data to a user. For example, output device 420 may include, but is not limited to, an LCD display, an LED display, an OLED display, a projector, or a similar display device capable of outputting images, text, etc. to a user. As another non-limiting example, output device 420 may include a wearable display, such as a smart watch, smart glasses, a head-up display, etc., that is separated from the rest of network node 400 but is communicatively coupled. In addition, output device 420 may be a component of a smart phone, a personal digital assistant, a television, a desktop computer, a notebook (laptop) computer, a personal computer, a vehicle dashboard, etc.

[0084] Output device 420 may include one or more speakers for producing sound. For example, output device 420 may produce an audible alarm or notification (e.g., a beep or buzzer). Output device 420 may include one or more tactile devices for producing vibration, motion, or other tactile feedback. All or part of output device 420 may be integrated with input device 415. For example, input device 415 and output device 420 may form a touch screen or similar touch-sensitive display. Output device 420 may be located near input device 415.

[0085] The transceiver 425 includes at least one transmitter 430 and at least one receiver 435. One or more transmitters 430 can be used to communicate with the UE, as described herein. Similarly, one or more receivers 435 can be used to communicate with network functions in the PLMN and / or RAN, as described herein. Although only one transmitter 430 and one receiver 435 are shown, the network node 400 can have any suitable number of transmitters 430 and receivers 435. In addition, the (multiple) transmitters 430 and (multiple) receivers 435 can be any suitable type of transmitter and receiver.

[0086] Therefore, a device is provided, which includes a receiver, a processor and a transmitter. The receiver is arranged to receive a first analysis request from a consumer. The processor is arranged to determine that a counterparty analysis from a counterparty function is required to service the first analysis request. The transmitter is arranged to send the counterparty analysis request to the counterparty function. The receiver is also arranged to receive a response to the counterparty analysis request from the counterparty function. The processor is also arranged to prepare an analysis response using the counterparty analysis. The transmitter is also arranged to send the analysis response to the consumer.

[0087] The device may also be arranged to use self-derived analysis. The analysis response may be prepared using self-derived analysis and counterparty analysis. The self-derived analysis may include analysis derived by the device. The self-derived analysis may include analysis derived by the device using locally available information. The self-derived analysis may be analysis derived in the local domain of the device. The self-derived analysis may include analysis derived by the device based on raw data. Raw data is information provided by a network source based on local measurements.

[0088] Such an apparatus tends to facilitate configuration and coordination of input parameters for requesting inter-plane analysis services to ensure that the requirements of the consumer are met. This can facilitate selection of appropriate inter-plane analysis functions to provide input to the analysis service. In addition, this can provide a solution that tends to coordinate parameters for inter-plane analysis services, such as timing and coverage parameters, etc.

[0089] The processor may be further arranged to determine the attributes required in the counterpart analysis request based on the first analysis request from the consumer.

[0090] The receiver may also be arranged to receive information about the capabilities of the other party's function. The device may be arranged to discover the capabilities of the other party's function. The processor may also be arranged to discover the capabilities of the other party's function from the other party's function or another node. The transmitter may be arranged to send a capability discovery message to the other party's function or another node. The other node may be a centralized server.

[0091] The capabilities may include expected computational latency, communication latency, report sample type, and analysis type. These capabilities complement the state-of-the-art capabilities used, including analysis ID, AI / ML model ID, confidence level, reporting method, area of ​​interest, target UE, network and management object, filter conditions (e.g., threshold crossing). AI / ML models may include artificial intelligence models and / or machine learning models.

[0092] The processor may be arranged to negotiate the analysis request with the consumer.The processor may be further arranged to negotiate the requirements of the first analysis request with the consumer if the selection of the best counterpart function cannot serve the requirements of the first analysis request.

[0093] The device and the counterpart function may reside on different network planes. The device and the counterpart function may reside on the same network plane, but on different domains.

[0094] The counterparty analysis request may include at least one parameter selected from the following group: analysis ID, AI / ML model ID, schedule, report time window, report analysis sample type, confidence level, analysis type, report method, target area, target user, target network object, and report filter condition.

[0095] The first analysis request may include at least one parameter, and the processor may be further arranged to: map the parameter from the first request to the parameter in the other analysis request; derive the parameter relationship; and / or convert one type of parameter to another type of parameter. The mapping may be based on preconfigured information and / or based on parameter matching.

[0096] The processor may also be arranged to convert an attribute type in the first analysis request associated with the target UE into a geographical area. The processor may also be arranged to convert an attribute type associated with the geographical area into any UE identity. The processor may also be arranged to identify a containment relationship between the management service and the counterpart function, and vice versa.

[0097] The processor may be further arranged to calculate a relative schedule for reporting by the counterpart function, the relative schedule calculated taking into account at least one of a processor load in the counterpart function, a memory load in the counterpart function and a communication delay between the counterpart function and the device.

[0098] The processor may also be arranged to derive a format of a machine learning model input by considering at least one of: a reporting time window; an analysis sample; and / or a confidence level. The machine learning (ML) model may include an artificial intelligence (AI) model. The processor may also be arranged to identify the machine learning model and the associated reporting time window, analysis sample, and confidence level.

[0099] Figure 5 A method 500 in an apparatus is illustrated. The method 500 includes receiving 510 a first analysis request from a consumer, and determining 520 that a counterpart analysis from a counterpart function is needed to service the first analysis request. The method 500 also includes sending 530 the counterpart analysis request to the counterpart function, and receiving 540 a response to the counterpart analysis request from the counterpart function. The method 500 also includes preparing 550 an analysis response using the counterpart analysis, and sending 560 the analysis response to the consumer.

[0100] A central node is also provided comprising a receiver and a transmitter. The receiver is arranged to receive capability information from a plurality of counterpart nodes, the capability information defining the capability of the counterpart nodes to generate counterpart analysis. The receiver is further arranged to receive a request for capability information from a device. The transmitter is arranged to send a capability report in response to the request.

[0101] The centralized node facilitates the device to discover the ability of the other party's functions. The capability report may include capability information of at least one other party node. The capability report may include at least one other party function that meets the capability requirements defined in the request for capability information. The capability may include expected computational delay, communication delay, report sample type, and analysis type. These capabilities complement the latest capabilities used, including analysis ID, AI / ML model ID, confidence level, reporting method, area of ​​interest, target UE, network and management object, and filtering conditions (e.g., threshold crossing). The capability report may carry a set of information or ID related to the other party's analysis function.

[0102] Such a central node tends to facilitate the configuration and coordination of input parameters for requesting inter-plane analysis services to ensure that the requirements of the consumer are met. This can facilitate the selection of appropriate inter-plane analysis functions to provide input to the analysis service. In addition, this can provide a solution that tends to coordinate parameters for inter-plane analysis services, such as timing and coverage parameters, etc.

[0103] Figure 6 A method 600 in a central node is illustrated. The method 600 comprises receiving 610 capability information from a plurality of counterpart nodes, the capability information defining the counterpart node's capability to generate counterpart analysis. The method 600 further comprises receiving 620 a request for capability information from a device; and sending 630 a capability report in response to the request.

[0104] The request for capability information may indicate a specific counterparty analysis function to the central node.The capability report may also carry a set of information or IDs related to the counterparty analysis function.

[0105] There is also provided a counterpart node comprising a transmitter arranged to send capability information to a central node, the capability information defining a capability of the counterpart node to generate a counterpart analysis.

[0106] Figure 7 The method 700 in the counterparty node is illustrated. The method 700 includes sending 710 capability information to the central node, the capability information defining the capability of the counterparty node to generate the counterparty analysis. The counterparty node may send the capability information to the central node periodically or upon an event (e.g., a threshold crossing) or upon determining that the UE begins to move. The counterparty node may send the capability information to the central node in response to a request from the central node. The request from the central node may be triggered by an initialization process. The request from the central node may be sent periodically.

[0107] The solution described herein relates to the case where an analysis service depends on another analysis output (such as from NWDAF, MDAF, ADAES), and an inter-plane analysis needs to be requested once an analysis consumer request is received in the analysis function, i.e., when an NWDAF analysis ID request depends on an MDA output or vice versa. In other words, a method is provided that autonomously issues subsequent analysis requests to the desired inter-plane analysis partner function.

[0108] To accomplish this, the receiving analysis function may analyze and process the consumer request to: (i) automatically formulate subsequent subscription requests for the discovered analysis counterpart functions, and (ii) perform discovery of the appropriate inter-plane analysis counterpart functions as required. The inter-plane analysis ID type selection may be based on the required data input, and the relationship may be pre-configured.

[0109] Figure 8 An inter-plane analysis example is illustrated, showing an analysis consumer requesting analysis from a receiving analysis function residing in a different domain. The different domains can be on a control plane or a management plane or an application support plane. Domain A 805 includes an analysis consumer 810, and a receiving analysis function 820. Domain B 860 includes an analysis function 870.

[0110] The receiving-side analysis function 820 provides processing of inter-plane analysis requests, or in other words, provides inter-plane analysis logic to select and automatically derive requirements or attributes associated with an inter-plane analysis request (which is essentially an automatically issued analysis request) to the corresponding inter-plane analysis function 870.

[0111] Figure 8 Also shown are some key selection capabilities for selecting inter-plane analysis functionality 870, including analysis ID and AI / ML model type (including AI / ML model details) and estimates of communication and processing delays associated with the ability to support specific analysis type results, such as real-time, near real-time, or non-real-time.

[0112] The receiving side analysis function 820 first performs analysis based on the inter-plane analysis logic and processes the requirements of the consumer request. Then, it automatically derives the corresponding requirements or attributes related to the inter-plane analysis request to be issued to the other party's inter-plane analysis function 870, which may include but is not limited to the following examples. Inter-plane logic or process and automatic manner to select and / or derive any of the following attributes: target analysis ID; target AI / ML model type; relative schedule; reporting time window; report analysis sample; confidence level; analysis type; reporting method; area of ​​interest; (multiple) target UEs; network or management objects; filtering conditions; or any combination thereof. These attributes will be discussed in detail in the following paragraphs.

[0113] Target Analysis ID: It refers to the desired inter-plane analysis functional capability, for example, being able to generate UE mobility analysis, NF load analysis, slice throughput analysis, etc. This is automatically selected using a mapping process, for example, based on a preconfigured table, considering the necessary input types. Optionally, the consumer can indicate (for example, explicitly indicating that the following type of AI / ML model needs to be used), or there can be another mapping, for example, based on a preconfigured table, for selecting the desired target AI / ML model type to be used (for example, regression, decision tree, etc.), and in this case, it should also be selected as another inter-plane analysis functional capability.

[0114] Relative schedules: Given the schedule indicated by the consumer, the receiving analysis function should be able to estimate the corresponding schedule (either explicitly calculated or by accessing repository information) by taking into account the upper bound time required to receive responses from other inter-plane analysis functions on which it is dependent. To achieve this, each analysis function may register its capabilities in terms of the upper bound time to prepare analysis results based on the available CPU and storage resources and the current workload in a repository or centralized entity (e.g., a domain name server (DNS)). Alternatively, each analysis function may respond to the requesting inter-plane analysis function with its capabilities in terms of the upper bound time to prepare analysis results based on the available CPU and storage resources and the current workload. Each requesting analysis function needs to estimate the communication delay in receiving analysis from the requesting inter-plane analysis function, which can be achieved, for example, by sending round-trip probe messages to estimate the expected delay.

[0115] Reporting time window: It refers to the expected reporting time window, i.e., indicates the start time and stop time of the analysis results included in the report from the inter-plane analysis function. The start time and stop time depend on the AI / ML model type in the receiving analysis function and can be calculated or pre-configured on the table.

[0116] Report analysis samples: This indicates how the report of the analysis samples should be presented, such as average, min-max, pdf, discrete time-based samples, etc., and depends on the AI / ML model type in the receiving side analysis function. The selection of the AI / ML model type (e.g., based on a preconfigured table) also includes the required sampling.

[0117] Confidence Level: Indicates the expected confidence level (i.e., the confidence in the predicted result based on the current data) required by the receiving analysis function associated with the target analysis ID and the analysis result of the corresponding target AI / ML model type.

[0118] Analysis Type: Considering the type of analysis requested by the consumer, i.e., real-time, near real-time, or non-real-time, the receiving analytics also considers its analysis ID and AI / ML model type requirements and should request the desired analysis type from the selected inter-plane analytics function. The selection should be based on the relevance of the following: (i) customer instructions, (ii) the need for the receiving analytics function to provide its analysis ID and AI / ML model type, (iii) the relative timeline of each candidate inter-plane analytics function, and (iv) the reporting method capabilities associated with the inter-plane analytics function. For example, the real-time analysis type requested by the consumer can only be satisfied if the receiving analytics function analysis ID and AI / ML model type handles real-time data and can receive real-time data from the inter-plane analytics function via stream-based reporting, thereby ensuring real-time data delivery.

[0119] Reporting method: It refers to the way of receiving analysis results from the inter-plane analysis function. For example, MDAF can request NWDAF: (i) on-demand, that is, an immediate one-time request, or (ii) a subscription based on a specified schedule and / or other filtering criteria, for example, if the NF load exceeds a threshold limit. The analysis results are analyzed for both cases using notifications. In another example, NWDAF can request MDAF: (i) when the size / number of outputs is larger, report in a document format (based on a specified schedule and / or other filtering criteria), or (ii) stream-based reporting suitable for real-time data (i.e., once ready, a connection is established and the analysis results are sent immediately), or (iii) if the output data is first maintained in a data storage entity, where the consumer receives a notification to retrieve the data, then report in a notification-based manner (considering the specified schedule or other filtering conditions). The choice of reporting method is related to the type of analysis requested, the relative schedule, and takes into account the amount of data and the recipient of the analysis results.

[0120] Region of Interest: Can be explicitly specified by the consumer, in which case the receiving analysis function maps the same region capability (ie, able to perform analysis in the specified region) and requests to the inter-plane analysis function.

[0121] (Multiple) Target UEs: It refers to different aspects of the control or management or application plane. The control plane focuses on a specific UE ID (Subscription Permanent Identifier SUPI), the management plane considers the average UE in a specific location, and the application plane focuses on the application clients residing in the UE. Specifically, in case the NWDAF requires MDA outputs (e.g., resource utilization prediction) related to UEs or UE groups residing in a specific area, it needs to convert the locations of (multiple) UEs into areas, such as in the form of cells or TAs. If the MDA MnS producer requires NWDAF outputs, it needs to request analysis of any UE in a specific area of ​​interest (i.e., cell or TA). For ADAES, it needs to request analysis of a specific application client within any UE residing in a specific area of ​​interest (i.e., cell or TA).

[0122] Network or Management Object: It refers to NF when requesting inter-plane analysis to the control plane and is discovered based on interaction with NRF, application components and services on the application plane, or refers to MnS when requesting inter-plane analysis to the management plane and relies on interaction with DNS or centralized discovery servers that contain the relationship of the requested IP address to the desired MnS object. The choice in each case can be based on identifying the containment relationship with the help of a repository or other discovery means, such as directly requesting the object relationship.

[0123] Filter conditions: refers to the conditions included in the consumer request, which indicate the reporting triggering criteria. The receiving analysis function needs to identify where the filter conditions should be applied (i.e., matching considering its own and the target analysis function's operational capabilities), and in this case related to the requested inter-plane analysis. For example, when the UE group starts to move towards a neighboring cell, the consumer's request to the MDA can indicate the reporting criteria, such conditions can be easily implemented in the control plane and should be included in the corresponding inter-plane analysis request.

[0124] It should be noted that any combination of the above-mentioned attributes may also assist the receiving analysis function as a criteria for receiving a consumer request to decide whether the inter-plane analysis function should be requested to report the desired analysis results, for example, taking into account the schedule and confidence of the received forecast, or it may alternatively collect the desired raw data from the original inter-plane source and calculate the results locally (for example, if the desired conditions can be met in this way).

[0125] Fig. 9 A flow diagram of an inter-plane analysis request and response method 900 is presented. Fig. 9Shown are analysis consumers 910, receiver analysis functions 920, analysis request processing functions 930, inter-plane analysis functions 940, centralized servers 950, and other data sources 960. Analysis request processing 930 may include inter-plane analysis logic. Centralized servers 950 may include NRFs or DNS.

[0126] Initially, at 980, the inter-plane analysis function 940 registers its capabilities (i.e., support of analysis result calculation delay, analysis type, reporting time window, reporting samples, reporting methods) with a centralized repository such as NRF or DNS. In NRF, the inter-plane analysis function 940 may register all capabilities, while in DNS, only its IP address with minimal other capabilities. Any other repository that can store any number of capabilities that allow hybrid discovery is possible.

[0127] At 981, the analysis consumer 910 issues a request using either: (i) an on-demand request or subscription method if the receiving analysis function 920 is an NWDAF as described in 3GPP TS23.288v17.5.0, or (ii) an MDA request method (i.e., create report job) if the receiving analysis function 920 is an MDAF as described in 3GPP TS28.104v17.0.1.

[0128] At 982, the receiving analysis function 920 uses the analysis request processing component 930 or inter-plane analysis logic (which resides within the same function or alternatively a separate NF) to determine the requirements of the received analysis request to identify the inter-plane attributes (as described above: analysis ID, AI / ML model ID, relative schedule, reporting time window, etc.).

[0129] At 983, the receiver analysis function 920 performs a discovery of the optimal inter-plane analysis function(s) 940. The discovery step can be performed in two different ways.

[0130] (i) In step 983a, the receiving analysis function 920 requests a central repository (e.g., NRF) indicating the desired capabilities of the target inter-plane analysis functions 940 (based on analysis ID, AI / ML model ID, analysis type, load, latency, etc.), and receives a reply in step 983b that suggests a set of inter-plane analysis functions 940 from which to select.

[0131] (ii) Alternatively, the receiving analysis function 920 may request the capabilities of each proposed inter-plane analysis function 940, provided that the corresponding IP address is known or discovered, e.g., via DNS. The receiving analysis function 920 is then able to select the best inter-plane analysis function 940. If, in steps 983a and 983b, the receiving analysis function 920 only receives basic information from a centralized repository, the receiving analysis function 920 may choose to request capabilities from each proposed inter-plane analysis function 940.

[0132] At 984, if the discovery process does not suggest an inter-plane analysis function 940 that can achieve the desired capabilities, the receiving analysis function 920 can optionally negotiate the requirements of the analysis request with the analysis consumer 910. Negotiation examples can include a change in the desired analysis type, such as from real-time to near real-time because the relative timetable does not allow for the analysis results to be prepared in real time. If a solution cannot be reached in the negotiation step, or the negotiation step is not supported at all, the process terminates in this step.

[0133] At 985 , if the proposed set of inter-plane analysis functions 940 meet the desired capabilities or the negotiation steps help reach a solution, the recipient analysis function 920 selects the best inter-plane analysis function 940 and formats a corresponding inter-plane analysis request.

[0134] At 986 , an inter-plane analysis request is automatically issued to the selected inter-plane analysis function 940 .

[0135] At 987, the inter-plane analysis function 940 responds to provide the desired analysis output results.

[0136] At 988, the receiving analysis function 920 additionally collects raw data from other data sources, which may include NF, MnS, repository functions (e.g., NRF, UDR, URM), data collection entities (e.g., DCCF, MFAF, ADRF, MADCOL, etc.) to calculate consumer request analysis results.

[0137] At 989, the receiving-side analysis function 920 prepares the analysis results, such as formatting and the like.

[0138] At 990 , the recipient analysis function 920 sends an analysis response to the analysis consumer 910 , which provides the requested analysis.

[0139] Typically, the receiving analysis function 920 and the (multiple) inter-plane analysis function 940 reside on different network planes. However, there may also be a situation where the receiving analysis function 920 and the (multiple) inter-plane analysis function 940 reside on the same network plane but on different domains. This may also be the case of an aggregator NWDAF, where a relationship between it and a distributed NWDAF can be established as needed, taking into account the analysis request of the consumer, rather than pre-configuring such a relationship. In this case, the same method can be applied to process and analyze consumer requests to discover and select appropriate distributed NWDAFs.

[0140] Fig.10 An inter-plane analysis method 1000 between ADAES and 3GPP domain analysis (OAM and 5GC) is illustrated. Fig.10 The diagram shows a consumer 1010, an ADAES 1020, a CAPIF 1030, an MDAS 1040, and an NWDAF 1050. The CAPIF 1030 may be a CCF or an NRF. The consumer 1010 may include an AF or a VAL server. According to the method 1000, an inter-plane analysis is performed at the ADAES with 3GPP data analysis (NWDAF and / or MDAS) as input. (Note that MDA, MDAF, and MDAS may be used interchangeably).

[0141] We take the edge load analysis discussed in 3GPP TS23.700-36v0.4.0 as an example, where ADAES uses PM data analysis from OAM and DN performance data analysis from NWDAF as input to derive edge load analysis (among other inputs). Method 1000 focuses on discovering and analyzing service producers (NWDAF 1050, MDAS 1040) and coordinating parameters to ensure that the requirements of inter-plane services are met.

[0142] At 1081, the consumer of the ADAES analytics service sends a subscription request to ADAES and provides the analytics event ID, such as edge performance prediction or statistics, DNN / DNAI, time validity and region of the request, required confidence level, whether inter-plane analysis is required, and AI / ML model type, etc.

[0143] At 1082, ADAES sends a subscription response as an ACK to the consumer.

[0144] At 1083, ADAES maps the analysis event ID to a list of data analysis event identifiers (which can be pre-configured) and interacts with the service repository function (CAPIF CCF, NRF, ADRF, or any other registry at 5GS that can provide a list of analysis functions for the target area and request type).

[0145] Service repository function authorization request (also checks if the end consumer is allowed to consume analytics services directly) and provides the data analytics function ID and address and (optionally) API / service payload information (e.g., payload for NWDAF#1, payload for NWDAF API#x)

[0146] At 1084, ADAES determines the analysis service requirements (time, region, reporting requirements, methods, automatic triggering events / actions, etc.) based on the identified analysis sources to ensure that the inter-plane analysis service requirements are met with the required confidence level. This determination also takes into account the possible communication and processing delays of the analysis inputs, and the possible priority / tier / reliability of the analysis.

[0147] At 1085, ADAES sends a subscription request to the data analytics producer (NWDAF, OAM / MDAS), including the corresponding data analytics event ID and the requirement for data analytics collection. The data analytics producer(s) sends a subscription response as ACK to ADAES.

[0148] At 1086-1089, ADAES collects the reported analytics based on the configuration and derives application / edge layer analytics and provides the output to the consumer. Steps 1086-1089 may be performed in accordance with 3GPP TR 23.700-36 v0.4.0.

[0149] When an analysis function receives a consumer request associated with an analysis ID that is dependent on the output results of another analysis ID from an inter-plane analysis function, i.e., the NWDAF requires the MDAF analysis ID output as input data or vice versa, a method is provided for: (i) identifying the appropriate inter-plane analysis function as analysis is required and determining the expected capabilities based on the capabilities contained in the original consumer request, and (ii) deriving analysis attributes and automatically formulating a new analysis request to the corresponding inter-plane analysis function.

[0150] Therefore, a method is provided to automatically determine attributes to formulate subsequent inter-plane analysis requests. A process is introduced in the analysis function to: (i) map subsequent analysis IDs, AI / ML model IDs, analysis types, reporting methods, regions, filtering, (ii) calculate the relative schedule of reports, (iii) derive AI / ML model inputs, i.e., reporting time windows and analysis samples, (iv) convert one attribute to another, e.g., target UE to region, (v) identify inclusion relationships, e.g., MnS included in NF. Analysis function capabilities can be registered in a repository or directly transferred.

[0151] The proposed processing of the original consumer request to derive the requirements can be implemented within the NWDAF, allowing autonomous inter-plane analysis requests to be issued to the corresponding MDA.

[0152] Alternatively, the processing of the original consumer request to derive the requirements may be implemented within the MDAF, allowing autonomous inter-plane analysis requests to be issued to the corresponding NWDAF.The MDAF may consult the NRF to identify the desired NWDAF.

[0153] Furthermore, the proposed processing of the original consumer request to derive the requirements may be implemented within ADAES to allow autonomous inter-plane analysis requests to be issued to the corresponding MDAS or NWDAF.

[0154] Therefore, a method is provided, which includes processing an original analysis request from a consumer to derive analysis requirements so as to formulate a new analysis request to an analysis function on a counterpart plane. The method may also include identifying an appropriate analysis function on the counterpart plane that is responsible for providing a supplemental analysis. The method may also include negotiating requirements with the consumer if the processing and selection of the best analysis function does not meet its original requirements.

[0155] A method is also provided that allows an analysis function that relies on input from another analysis function to produce its output results to automatically determine the attributes to include in formulating subsequent inter-plane analysis requests based on the original analysis request from the consumer.

[0156] Another analysis function may be an inter-plane analysis function.

[0157] The method may allow an analysis function that relies on input from another inter-plane analysis function to produce its output results to automatically identify and select the best inter-plane analysis function.

[0158] This method may enable the analysis function to perform mapping of the following attributes (but not limited to), including analysis ID, AI / ML model ID, analysis type, reporting method, region, filtering from the original consumer request.

[0159] The method may enable the analysis function to perform mapping based on preconfigured information and / or based on parameter matching.

[0160] The method may enable the analysis function to calculate a relative schedule for reporting taking into account CPU and / or memory load and communication delays in the analysis functions between the candidate planes.

[0161] This approach can enable the analysis function to consider the reporting time window and analysis samples to derive the format of AI / ML model input.

[0162] The method may enable the analysis function to convert one attribute type related to a target UE to a geographical area and / or convert one attribute type related to a geographical area to any UE.

[0163] The method may enable the analysis function to identify inclusion relationships between management services and network functions, and vice versa.

[0164] A method is also provided that allows an analysis function that relies on input from another inter-plane analysis function to produce its output results to automatically negotiate consumer requirements in the event that the selection of the best inter-plane analysis function does not meet the consumer's needs.

[0165] A method for providing inter-plane analysis services at a data analysis service producer is also provided, the method comprising: - receiving a first requirement for a first analysis service; - determining a second requirement for deriving an inter-plane analysis for the first analysis service, wherein the requirement includes one or more additional analysis services from one or more analysis functions; - configuring at least one parameter for one or more additional analysis services based on the first requirement and / or the second requirement; - sending at least one parameter to one or more analysis service producers of the one or more additional analysis services.

[0166] It should be noted that the above methods and apparatus illustrate rather than limit the invention, and that those skilled in the art will be able to design many alternative arrangements without departing from the scope of the appended claims. The word "comprising" does not exclude the presence of other elements or steps than those listed in a claim, "a" or "an" does not exclude a plurality, and a single processor or other unit may perform the functions of several units described in a claim. Any reference signs in a claim should not be construed as limiting its scope.

[0167] Furthermore, although examples have been given in the context of specific communication standards, these examples are not intended to limit the communication standards to which the disclosed methods and apparatus may be applied. For example, although specific examples have been given in the context of 3GPP, the principles disclosed herein may also be applied to another wireless communication system, and indeed to any communication system that uses routing rules.

[0168] The method may also be embodied in a set of instructions stored on a computer-readable medium, which when loaded into a computer processor, a digital signal processor (DSP), etc., causes the processor to perform the above-described method.

[0169] The described methods and apparatus may be practiced in other specific forms. The described methods and apparatus are considered in all respects to be illustrative only and not restrictive. Therefore, the scope of the present invention is indicated by the appended claims rather than by the foregoing description. All changes within the meaning and equivalent range of the claims should be included within their scope.

[0170] The following abbreviations are relevant to the scope of this document: AI / ML, artificial intelligence / machine learning; ADRF, analytical data repository function; ADAES, application data analytics support services; CPU, central processing unit; DCCF, data collection coordination function; DN, data network; DNS, domain name server; MADCOL, management data collection, control and discovery; MDA, management data analytics; MFAF, message framework adapter function; MnS, management service; NF, network function; NRF, network repository function; NWDAF, network data analysis function; PLMN, public land mobile network; PM, performance management; QoE, quality of experience; RAN, radio access network; SBA, service-based architecture; SBMA, service-based management architecture; SLS, service level specification; SUPI, subscription permanent identifier; TA, tracking area; UDM, user data manager; UDR, user data repository; UE, user equipment.

Claims

1. A device comprising: a receiver arranged to: receive a first analysis request from a consumer; A processor arranged to: determine that a counterpart analysis from a counterpart function is required to service said first analysis request; a transmitter, arranged to: send a counterpart analysis request to the counterpart function; The receiver is further arranged to: receive a response to the counterpart analysis request from the counterpart function; The processor is further arranged to: prepare an analysis response using the counterparty analysis; The transmitter is further arranged to transmit the analysis response to the consumer. 2 . The apparatus according to claim 1 , wherein the processor is further arranged to determine attributes required in the counterparty analysis request based on the first analysis request from the consumer.

3. The apparatus according to claim 1 or 2, wherein the receiver is further arranged to: receive information about the capability of the counterpart function.

4. An apparatus according to any preceding claim, wherein the processor is arranged to negotiate an analysis requirement with the consumer.

5. The apparatus according to any one of the preceding claims, wherein the apparatus and the counterpart function reside on different network planes.

6. The apparatus according to any one of claims 1 to 4, wherein the apparatus and the counterpart function reside on the same network plane but on different domains.

7. The apparatus according to any one of the preceding claims, wherein the counterparty analysis request comprises at least one parameter selected from the following group: Analysis ID, AI / ML model ID, schedule, Reporting time window, Report analysis sample type, Confidence level, Analysis type, Reporting methods, Target area, Target users, The target network object, and Report filter criteria.

8. An apparatus according to claim 7, wherein the first analysis request includes at least one parameter, and the processor is further arranged to: map parameters from the first request to parameters in the other party's analysis request; derive parameter relationships; and / or convert one type of parameter into another type of parameter.

9. An apparatus according to any one of the preceding claims, wherein the processor is further arranged to: calculate a relative schedule for reporting by the counterpart function, the relative schedule being calculated taking into account at least one of a processor load in the counterpart function, a storage load in the counterpart function, and a communication delay between the counterpart function and the apparatus.

10. An apparatus according to any of the preceding claims, wherein the processor is further arranged to: derive the format of the machine learning model input by considering at least one of the following: the reporting time window; the analysis sample; and / or the confidence level.

11. A method in an apparatus, the method comprising: receiving a first analysis request from a consumer; determining that counterpart analysis from counterpart functionality is required to service the first analysis request; Sending a counterparty analysis request to the counterparty function; receiving a response to the counterparty analysis request from the counterparty function; using said other party's analysis to prepare an analytical response; An analysis response is sent to the consumer.

12. A central node, comprising: a receiver arranged to: receive capability information from a plurality of counterpart nodes, the capability information defining the capability of the counterpart nodes to generate counterpart analysis; The receiver is further arranged to: receive a request for capability information from a device; and A transmitter is arranged to send a capability report in response to the request.

13. A method in a central node, the method comprising: receiving capability information from a plurality of counterpart nodes, the capability information defining capabilities of the counterpart nodes to generate counterpart analytics; receiving a request for capability information from a device; as well as A capability report is sent in response to the request.

14. A counterpart node, comprising a transmitter arranged to: transmit capability information to a central node, the capability information defining a capability of the counterpart node to generate a counterpart analysis.

15. A method in a counterpart node, the method comprising: Capability information is sent to a central node, the capability information defining the counterpart node's capability to generate counterpart analysis.

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