Coordinating cross-domain and specific domain management data analytics

Abstract

The present invention provides apparatuses, methods, computer programs, computer program products and computer-readable media for coordinating cross- domain and specific domain management data analytics. An apparatus for use in a cross-domain analytics data producer, comprisesat least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to perform: receiving a cross-domain request for cross-domain data analytics from a cross-domain analytics data consumer, the cross-domain request being directed to at least two different specific domains; decomposing the cross-domain request into domain specific requests for domain specific data analytics for each of the at least two different specific domains; sending a domain specific request for supported capability of each specific domain to a domain specific analytics data producer of each of the specific domains; receiving a domain specific response about the supported capability of each specific domain from the domain specific analytics data producer of each of the specific domains; determining based on the domain specific response, whether the cross-domain data analytics is feasible; if it is determined, that the cross-domain data analytics is feasible, sending domain specific requests for domain specific data analytics to each of the different specific domains; receiving domain specific reports for the domain specific data analytics from each of the different specific domains; aggregating the received domain specific reports and generating a cross-domain report for the requested cross-domain data analytics; and forwarding the cross-domain report for the requested cross-domain data analytics to the cross-domain analytics data consumer.

Description

[0001] Title

[0002] COORDINATING CROSS-DOMAIN AND SPECIFIC DOMAIN MANAGEMENT DATA

[0003] ANALYTICS

[0004] Field of the invention

[0005] Various example embodiments relate to apparatuses, methods, systems, computer programs, computer program products and computer-readable media for coordinating cross-domain and specific domain management data analytics.

[0006] Abbreviations

[0007] 3GPP 3rdGeneration Partnership Project

[0008] 5GC Fifth Generation Core network

[0009] Al Artificial Intelligence

[0010] AF Application Function

[0011] AMF Access and Mobility Management Function

[0012] CN Core Network

[0013] E2E End-to-End

[0014] HW Hardware

[0015] KPI Key Performance Indicator

[0016] MDA Management Data Analytics

[0017] MDA MnS MDA Management service

[0018] MDAF Management Data Analytics Function

[0019] MDAS Management Data Analytics Service

[0020] MDT Minimization of Drive Tests

[0021] ML Machine Learning

[0022] MnF Management Function

[0023] NE Network Element

[0024] NF Network Function

[0025] NWDAF Network Data Analytics Function

[0026] QoE Quality of Experience

[0027] RAN Radio Access Network R.CEF resource control connection establishment failure

[0028] RLF Radio Link Failure

[0029] SON Self Organizing Networks

[0030] SW Software

[0031] UE User Equipment

[0032] Background

[0033] The present invention generally relates to coordinating cross-domain and specific domain management data analytics.

[0034] As described in document TS28.104, Management Data Analytics (MDA), as a key enabler of automation and intelligence, is considered a foundational capability for mobile networks and services management and orchestration.

[0035] The MDA provides a capability of processing and analyzing data related to network and service events and status including e.g. performance measurements, KPIs, Trace / MDT / RLF / RCEF reports, QoE reports, alarms, configuration data, network analytics data, and service experience data from AFs, etc. to provide analytics output, i.e. statistics or predictions, root cause analysis issues, and may also include recommendations to enable necessary actions for network and service operations. The MDA output is provided by the MDAS (Management Data analytics Service) producer to the corresponding consumer(s) that requested the analytics.

[0036] The MDA can identify ongoing issues impacting the performance of the network and services, and help to identify in advance potential issues that may cause potential failure and / or performance degradation. The MDA can also assist to predict the network and service demand to enable the timely resource provisioning and deployments, which would allow fast time-to-market network and service deployments.

[0037] Management Data Analytics Service (MDAS), the services exposed by the MDA, can be consumed by various consumers, including for instance MnFs (i.e. MnS producers / consumers for network and service management), NFs (e.g. NWDAF), SON functions, network and service optimization tools / functions, SLS assurance functions, human operators, and AFs, etc.

[0038] A management function (MDAF) may play the roles of MDA MnS producer, MDA MnS consumer, other MnS consumer, NWDAF consumer and LMF service consumer, and may also interact with other non-3GPP management systems.

[0039] Analytics output from the MDA internal business logic are made available by the management functions (MDAFs) playing the role of MDA MnS producers to the authorized consumers, (including but not limited to other management functions, network functions / entities, NWDAF, SON functions, optimization tools and human operators).

[0040] The MDA MnS producer provides analytics data for management purposes based on input data related to different types of NFs or entities in the network, e.g. data reported from gNB and / or specific core network function(s). Depending on the use case and when needed, the MDA MnS producer may use the analytics results produced by NWDAF as input.

[0041] Management Data Analytics Function (MDAF) may act as 3GPP domain-specific (e.g. RAN or CN) or as 3GPP cross-domain MDA MnS producer.

[0042] Fig. 1 (cf. TS28.104) illustrates the example of coordination between NWDAF, gNB and MDA MnS producer(s) for data analytics purpose.

[0043] As described in TS28.104, any authorized MnS consumers get access to MDA reports by interacting with MDA MnS producers. These scenarios include but are not limited to the following:

[0044] The NWDAF, leveraging MDA reports (e.g. for control purposes and other 5GC NFs), interacts with MDA MnS producers.

[0045] The gNB may consume the MDA MnS for RAN control purpose.

[0046] The 3GPP cross-domain MDA MnS Producer may consume (acting as Domain MDA MnS consumer) MDA MnS provided by domain-specific (RAN and / or CN) MDA MnS producer(s) and produce MDA MnS that may be consumed by 3GPP crossdomain MDA MnS consumer(s).

[0047] The management function (MDAF) playing the role of domain MDA MnS producer may interact with 5GC and RAN MnSs and NFs to receive analytics inputs per MDA capability, including:

[0048] The ON Domain MDA MnS producer may consume the service provided by NWDAF and other 5GC NFs for MDA purpose.

[0049] The RAN Domain MDA MnS producer may consume the MnS provided by / for gNB for MDA purpose.

[0050] The management function (MDAF) playing the role of 3GPP cross-domain MDA MnS producer consumes 5GC domain MDA, RAN domain MDA, 5GC MnS and RAN MnS to receive analytics inputs per each MDA use case / capability including:

[0051] The cross-domain MDA MnS producer may consume the MDA MnS provided by RAN and / or CN domains.

[0052] The cross-domain MDA MnS producer may consume MnS provided by RAN and / or CN domains, and produce MDA MnS that may be consumed by 3GPP crossdomain MDA MnS consumer(s).

[0053] That is, as described in TS28.104, a cross-domain Management Data Analytics Function (MDAF) is introduced as a management function playing the role of MDA MnS producer consuming 5GC domain MDA services, RAN domain MDA services, etc. A cross-domain MDA may base its analysis on the outputs from one or multiple single-domain MDA including analytics output and other input data (e.g. PM, alarm notifications, etc.). It is mainly introduced for E2E use cases detailed in clause 7 of TS28.104.

[0054] • Service experience analysis: consists in analyzing the end users service experience compared to the expected service e.g., priorities of SLA related attributes such as latency, throughput, and maximum number of users

[0055] • Network slice throughput analysis: network slice throughput related issues analysis and identification of the corresponding root cause(s) to assist throughput assurance. • Network slice traffic prediction: traffic load predictions per constituent network function instances (can be used for better resource provisioning of the network slice)

[0056] • E2E latency analysis: E2E latency analysis in relation with network capability and network configurations.

[0057] • Network slice load analysis: Analyze and identify network performance degradation (using measurements and KPI) due to load issues, e.g. radio resource utilization.

[0058] In the case of a cross-domain service, the cross-domain MDA receives MDA requests for cross-domain analytics from the cross-domain MDA MnS consumer, e.g., network operator. Subsequently, the cross-domain MDA requests the domain-specific MDAs (e.g., RAN, 5GC) to provide the corresponding domainspecific analytics using their domain-specific data and share the MDA analytics reports back to the cross-domain MDA (depending on the reporting characteristics selected in the request). However, other than the generic MDA analytics request / re port, no other mechanisms / capabilities exist for the interaction between cross-domain MDA and domain-specific MDA.

[0059] Various examples of embodiments described in the subject disclosure provide certain advantages, for example in the form of one or more improvements that are either explicitly described herein or otherwise apparent to a person skilled in the art from the subject disclosure. Hence, at least some examples of embodiments of the subject disclosure aim to provide (or otherwise contribute to) at least part of the aforementioned advantages and improvements.

[0060] Various aspects of examples of embodiments of the subject disclosure are set forth in the claims and pertain to methods, apparatuses and computer program products in the context of UE context handling for simplified baseline mobility.

[0061] At least some of aforementioned advantages and improvements may be achieved through the methods, apparatuses and non-transitory storage media as specified in the claims. Further advantages and improvements may be achieved through the methods, apparatuses and non-transitory storage media set forth in respective dependent claims.

[0062] According to an aspect of various example embodiments there is provided an apparatus for use in a cross-domain analytics data producer, comprising, at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to perform: receiving a cross-domain request for cross-domain data analytics from a cross-domain analytics data consumer, the cross-domain request being directed to at least two different specific domains; decomposing the cross-domain request into domain specific requests for domain specific data analytics for each of the at least two different specific domains; sending a domain specific request for supported capability of each specific domain to a domain specific analytics data producer of each of the specific domains; receiving a domain specific response about the supported capability of each specific domain from the domain specific analytics data producer of each of the specific domains; determining based on the domain specific response, whether the crossdomain data analytics is feasible; if it is determined, that the cross-domain data analytics is feasible, sending domain specific requests for domain specific data analytics to each of the different specific domains; receiving domain specific reports for the domain specific data analytics from each of the different specific domains; aggregating the received domain specific reports and generating a crossdomain report for the requested cross-domain data analytics; and forwarding the cross-domain report for the requested cross-domain data analytics to the cross-domain analytics data consumer. According to another aspect of various example embodiments there is provided an apparatus for use in a cross-domain analytics data consumer, comprising, at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to perform: sending a cross-domain request for cross-domain data analytics to a crossdomain analytics data producer, the cross-domain request being directed to at least two different specific domains and including information on a specific use case; receiving, from the cross-domain analytics data producer, a causal analysis for the specific use case, the causal analysis including at least one of the following: information on a specific issue; information on a source area of the specific issue; information on a cause of the specific issue; information on a source of the specific issue within the source area; information on an association of the determined source of the specific issue and the determined cause of the specific issue and information on priority of them based on the magnitude of the problem caused by the issue; or information on an optimized guidance in order to solve the specific issue; identifying and preparing actions to be performed based on the causal analysis for the specific use case and the optimized guidance; and performing the identified and prepared actions on a network element or network function of the specific domains.

[0063] According to another aspect of various example embodiments there is provided an apparatus for use in a cross-domain analytics data producer, comprising, means for receiving a cross-domain request for cross-domain data analytics from a cross-domain analytics data consumer, the cross-domain request being directed to at least two different specific domains; means for decomposing the cross-domain request into domain specific requests for domain specific data analytics for each of the at least two different specific domains; means for sending a domain specific request for supported capability of each specific domain to a domain specific analytics data producer of each of the specific domains; means for receiving a domain specific response about the supported capability of each specific domain from the domain specific analytics data producer of each of the specific domains; means for determining based on the domain specific response, whether the cross-domain data analytics is feasible; means for sending, if it is determined, that the cross-domain data analytics is feasible, domain specific requests for domain specific data analytics to each of the different specific domains; means for receiving domain specific reports for the domain specific data analytics from each of the different specific domains; means for aggregating the received domain specific reports and generating a cross-domain report for the requested cross-domain data analytics; and means for forwarding the cross-domain report for the requested crossdomain data analytics to the cross-domain analytics data consumer.

[0064] According to another aspect of various example embodiments there is provided an apparatus for use in a cross-domain analytics data consumer, comprising: means for sending a cross-domain request for cross-domain data analytics to a cross-domain analytics data producer, the cross-domain request being directed to at least two different specific domains and including information on a specific use case; means for receiving, from the cross-domain analytics data producer, a causal analysis for the specific use case, the causal analysis including at least one of the following: information on a specific issue; information on a source area of the specific issue; information on a cause of the specific issue; information on a source of the specific issue within the source area; information on an association of the determined source of the specific issue and the determined cause of the specific issue and information on priority of them based on the magnitude of the problem caused by the issue; or information on an optimized guidance in order to solve the specific issue; means for identifying and preparing actions to be performed based on the causal analysis for the specific use case and the optimized guidance; and means for performing the identified and prepared actions on a network element or network function of the specific domains.

[0065] According to another aspect of various example embodiments there is provided a method for use in a cross-domain analytics data producer, comprising: receiving a cross-domain request for cross-domain data analytics from a cross-domain analytics data consumer, the cross-domain request being directed to at least two different specific domains; decomposing the cross-domain request into domain specific requests for domain specific data analytics for each of the at least two different specific domains; sending a domain specific request for supported capability of each specific domain to a domain specific analytics data producer of each of the specific domains; receiving a domain specific response about the supported capability of each specific domain from the domain specific analytics data producer of each of the specific domains; determining based on the domain specific response, whether the crossdomain data analytics is feasible; if it is determined, that the cross-domain data analytics is feasible, sending domain specific requests for domain specific data analytics to each of the different specific domains; receiving domain specific reports for the domain specific data analytics from each of the different specific domains; aggregating the received domain specific reports and generating a crossdomain report for the requested cross-domain data analytics; and forwarding the cross-domain report for the requested cross-domain data analytics to the cross-domain analytics data consumer. According to another aspect of various example embodiments there is provided a method for use in a cross-domain analytics data consumer, comprising: sending a cross-domain request for cross-domain data analytics to a crossdomain analytics data producer, the cross-domain request being directed to at least two different specific domains and including information on a specific use case; receiving, from the cross-domain analytics data producer, a causal analysis for the specific use case, the causal analysis including at least one of the following: information on a specific issue; information on a source area of the specific issue; information on a cause of the specific issue; information on a source of the specific issue within the source area; information on an association of the determined source of the specific issue and the determined cause of the specific issue and information on priority of them based on the magnitude of the problem caused by the issue; or information on an optimized guidance in order to solve the specific issue; identifying and preparing actions to be performed based on the causal analysis for the specific use case and the optimized guidance; and performing the identified and prepared actions on a network element or network function of the specific domains.

[0066] According to another aspect of the present invention there is provided a computer program product comprising software code portions adapted to produce steps of any of the methods as described above when loaded into the memory of a computer.

[0067] According to a still further aspect of the invention there is provided a computer program product as defined above, wherein the computer program product comprises a computer-readable medium on which the software code portions are stored. According to a still further aspect of the invention there is provided a computer program product as defined above, wherein the computer program product is directly loadable into the internal memory of the computer and / or transmittable via a network by means of at least one of upload, download and push procedures.

[0068] According to an aspect of various example embodiments there is provided a computer readable medium storing a computer program as set out above.

[0069] According to an exemplary aspect, there is provided a computer program product comprising computer-executable computer program code which, when the program is run on a computer (e.g. a computer of an apparatus according to any one of the aforementioned apparatus-related exemplary aspects of the present disclosure), is configured to cause the computer to carry out the method according to any one of the aforementioned method-related exemplary aspects of the present disclosure.

[0070] Such computer program product may comprise (or be embodied) a (tangible) computer-readable (storage) medium or the like on which the computerexecutable computer program code is stored, and / or the program may be directly loadable into an internal memory of the computer or a processor thereof.

[0071] Further aspects and features of the present invention are set out in the dependent claims.

[0072] Brief Description of the Drawings

[0073] These and other objects, features, details and advantages will become more fully apparent from the following detailed description of various aspects / embodiments which is to be taken in conjunction with the appended drawings, in which:

[0074] Fig. 1 is a diagram illustrating an example of coordination between NWDAF, gNB and MDA MnS producer(s) for data analytics purpose. Fig. 2 is a diagram illustrating an example of procedures required for requesting a cross-domain analytics by a cross-domain MnS consumer.

[0075] Fig. 3 is a diagram illustrating an example of a procedure for requesting a causal analysis, reporting of causal analysis and the optimized guidance from crossdomain analytics producer to domain specific analytics producer.

[0076] Fig. 4 is a flowchart illustrating an example of a method according to some example embodiments of the invention;

[0077] Fig. 5 is a flowchart illustrating another example of a method according to some example embodiments of the invention;

[0078] Fig. 6 is a block diagram illustrating another example of an apparatus according to some example embodiments of the invention;

[0079] Fig. 7 is a block diagram illustrating another example of an apparatus according to some example embodiments of the invention;

[0080] Fig. 8 is a block diagram illustrating another example of an apparatus according to some example embodiments of the invention;

[0081] Fig. 9 is a block diagram illustrating another example of an apparatus according to some example embodiments of the invention.

[0082] Detailed description

[0083] The present disclosure is described herein with reference to particular non-limiting examples and to what are presently considered to be conceivable embodiments. A person skilled in the art will appreciate that the disclosure is by no means limited to these examples, and may be more broadly applied.

[0084] It is to be noted that the following description of the present disclosure and its embodiments mainly refers to specifications being used as non-limiting examples for certain exemplary network configurations and deployments. Namely, the present disclosure and its embodiments are mainly described in relation to 3GPP specifications being used as non-limiting examples for certain exemplary network configurations and deployments. As such, the description of example embodiments given herein specifically refers to terminology, which is directly related thereto. Such terminology is only used in the context of the presented non-limiting examples, and does naturally not limit the disclosure in any way. Rather, any other communication or communication related system deployment, etc. may also be utilized as long as compliant with the features described herein.

[0085] Hereinafter, various embodiments and implementations of the present disclosure and its aspects or embodiments are described using several variants and / or alternatives. It is generally noted that, according to certain needs and constraints, all of the described variants and / or alternatives may be provided alone or in any conceivable combination (also including combinations of individual features of the various variants and / or alternatives).

[0086] According to some example embodiments of the present invention, there is introduced a method for coordinating cross-domain and specific domain management data analytics.

[0087] As mentioned above, other than the generic MDA analytics request / re port, no other mechanisms / capabilities exist for the interaction between cross-domain MDA and domain-specific MDA, i.e., the following are not supported:

[0088] • A mechanism to decompose cross-domain MDA analytics request into domain-specific MDA analytics requests.

[0089] • A mechanism for cross-domain MDA to discover domain-specific MDA capabilities.

[0090] • A mechanism for cross-domain MDA to aggregate multiple domain-specific MDA reports into a single cross-domain MDA report.

[0091] • A mechanism for cross-domain MDA to send analytics feedback to domainspecific MDAs which may be useful if cross-domain analytics is related to some predictions using AI / ML models. • A mechanism for cross-domain MDA to perform causal analysis on the identified problems depending on the use case.

[0092] • A mechanism for cross-domain MDA to identify the cause-source and the prescriptions to solve the identified problem at the cause-source.

[0093] According to some example embodiments of the present invention, there are proposed new functionalities in the cross-domain MDA framework to facilitate the definition, configuration, measurement, and reporting of cross-domain MDA analytics in multi-vendor and multi-domain environment. Some example embodiments of the present invention introduce new messages / interfaces to support the interactions between cross-domain MDA and the domain-specific MDA to realize cross-domain analytics. The cross-domain MDA producer may support the following operations:

[0094] • Decompose cross-domain MDA analytics request received from the crossdomain MDA consumer into domain-specific MDA analytics requests.

[0095] • Discover the supported analytics capabilities by individual domain-specific MDAs.

[0096] • Based on the above two steps, verify whether the cross-domain MDA analytics can be generated as requested by the cross-domain MDA consumer.

[0097] • Send domain-specific MDA requests to the corresponding domain-specific MDAs.

[0098] • Receive domain-specific MDA reports from the corresponding domainspecific MDAs.

[0099] • Aggregate multiple MDA reports received from domain-specific MDAs into cross-domain MDA report that can be provided to the cross-domain MDA consumer. If the cross-domain MDA analytics is related to some prediction / statistics of a network metric, the cross-domain MDA producer can share the cross-domain MDA report with domain-specific MDA producer. This feedback can be used by domain-specific MDA to fine tune ML model used for their prediction.

[0100] • Perform causal analysis for the identified cross-domain issue for the specific use case.

[0101] • Provide prescriptions for the identified problems across various individual domain MDAs. Additionally, prioritize the different problems identified and provide recommendations to the cross-domain MDA consumer on which problem is causing the most harm to the identified problem.

[0102] Some example embodiments of the present invention also discuss cross-domain causal analysis and prescription to the cross-domain MDA consumer for "service experience analysis" use case in MDA specification as an illustration to the proposed idea.

[0103] Fig. 2 illustrates the procedures required for requesting a cross-domain analytics by a cross-domain MnS consumer, e.g., operator's management system.

[0104] In step S201, a cross-domain MDA MnS consumer 21 requests a cross-domain E2E analytics from a cross-domain MDA MnS producer 22. In the request, the domain associated to analytics can be indicated.

[0105] It is noted that the cross-domain MDA MnS producer 22 may be any MDAF or NWDAF or gNB of any core network function. Further, it is noted that the crossdomain MDA MnS consumer 21 may be any MDAF or NWDAF or gNB of any core network function.

[0106] In step S202, the cross-domain MDA MnS producer decomposes the E2E crossdomain analytics into multiple domain specific MDA analytics depending on the type of the cross-domain MDA analytics requested and the outputs indicated in the request (mDAOutputlEName).

[0107] In steps S203, the cross-domain MDA MnS producer 22 requests to one of each (at least two) domain-specific MDA MnS producers 23, 24 the supported MDA analytics. That is, in a domain specific capability discovery, the cross-domain MDA MnS producer sends a domain specific supported capability request to each domain specific MDA MnS producer, like e.g. the domain specific MDA 1 MnS producer 23 in Fig. 2.

[0108] In step S204, the domain-specific analytics producer responds with the supported MDA analytics. That is, each of the at least two domain specific MDA MnS producers, like e.g. the domain specific MDA 1 MnS producer 23 in Fig. 2, that has received the domain specific supported capability request, sends a domain specific supported capability response to the cross-domain MDA MnS producer 22.

[0109] In a similar manner, in step S205, the cross-domain MDA MnS producer 22 requests to another one of each (at least two) domain-specific MDA MnS producers 23, 24 the supported MDA analytics. That is, in a domain specific capability discovery, the cross-domain MDA MnS producer sends a domain specific supported capability request to each domain specific MDA MnS producer, like e.g. the domain specific MDA 2 MnS producer 24 in Fig. 2.

[0110] In step S206, the domain-specific analytics producer responds with the supported MDA analytics. That is, the other one of the at least two domain specific MDA MnS producers, like e.g. the domain specific MDA 2 MnS producer 24 in Fig. 2, that has received the domain specific supported capability request, sends a domain specific supported capability response to the cross-domain MDA MnS producer 22.

[0111] This is done in a similar manner for all other domain specific MDA MnS producers. The number of the domain specific MDA MnS producers is not limited to two and may be three or more.

[0112] In step S207, the cross-domain MDA MnS producer 22 compiles a feasibility check depending on the different supported domain-specific MDAs and, if the crossdomain analytics are feasible, selects the domain-specific MDA requests to be derived.

[0113] In steps S208 and S210, the cross-domain MDA MnS producer 22 requests domain-specific MDA. That is, the cross-domain MDA MnS producer 22 send a domain specific analytics request to each of the domain specific MDA MnS producers, like e.g. the domain specific MDA 1 MnS producer 23 and the domain specific MDA 2 MnS producer 24 in Fig. 2

[0114] In steps S209 and S211, the domain-specific MDA MnS producers 23, 24 run the MDA analytics and compile the domain-specific MDA report to be sent to cross- domain MDA MnS producer 22 and send the domain specific analytics report to the cross-domain MDA MnS producer 22.

[0115] In step S212, after receiving the different domain-specific MDA reports, the crossdomain MDA MnS producer 22 aggregates the different domain-specific MDA reports into a cross-domain MDA report and complies the cross-domain MDA report.

[0116] In step S213, the cross-domain MDA MnS producer 22 can send the cross-domain MDA report to the respective domain-specific MDA 1 MnS producer 23 as feedback. In step S214, the cross-domain MDA MnS producer 22 can send the cross-domain MDA report to the respective domain-specific MDA 2 MnS producer 24 as feedback.

[0117] In step S215, the cross-domain MDA MnS producer 22 sends a cross-domain MDA report to the cross-domain MDA MnS consumer 21 that has requested the crossdomain E2E analytics.

[0118] In step S216, if the cross-domain MDA analytics is not feasible, the cross-domain MDA MnS producer 22 can report to the consumer 21 some non-feasibility reasons (i.e. specific-domain analytics being not available).

[0119] Fig. 3 illustrates an example of a procedure for requesting a causal analysis, reporting of causal analysis and the optimized guidance from cross-domain analytics producer to domain specific analytics producer.

[0120] In step S301, a cross-domain MDA MnS consumer 21, e.g operator's management system, requests a cross-domain E2E analytics. That is, the cross-domain MDA MnS consumer 21 sends a MDA request for E2E analytics for a specific use case to the cross-domain MDA MnS producer 22.

[0121] In step S302, the cross-domain MDA MnS producer 22 decomposes the E2E crossdomain analytics, performs the domain-specific analytics (request / report), and aggregates the different domain-specific analytics, as described in detail in steps S201 to S212 in Fig. 2. In step S303, the cross-domain MDA MnS producer 22 also performs a causal analysis on cross-domain and domain-specific analytics. The causal analysis and the associated optimized guidance shall be performed for the requested use case. The exact information elements of these shall be different based on different use case.

[0122] According to some example embodiments of the present invention, information on causal analysis and recommendations include at least one of the following:

[0123] 1. Source area of issue (RAN issue, CN issue, TN issue, UE issue, service provider issue, UE application issue, etc.)

[0124] 2. Possible causes: Packet drop, latency etc.

[0125] 3. Possible source: Interface (e.g. Uu, N3, etc.), Entities (e.g. gNB, AMF, etc)

[0126] 4. Mapping of "cause - source" and prioritize them based on the magnitude of the problem caused.

[0127] 5. Optimized guidance

[0128] The optimized guidance may be elaborated based on the causal analysis in order to solve the specific issue.

[0129] In the following, there is illustrated an example of the causal analysis and the optimized guidance for the service experience analysis use case from TS 28.104.

[0130] Causal Analysis for service experience analysis:

[0131] Source area of issue: RAN issue, Core issue

[0132] Primary causes: Packet drop and latency

[0133] Possible source: gNB, N3 interface

[0134] Mapping of cause-source:

[0135] Optimized guidance:

[0136] 1. Load balancing for the affected gNB 2. Perform N3 interface check and upgrade the interface (SW / HW), if needed

[0137] 3. Add more baseband processing for the affected gNB

[0138] Of course, it is to be noted that the above is only mentioned as an example and that the present invention is not limited to the above-mentioned example.

[0139] According to some example embodiment of the present invention, at least one of the following steps S304 to S308 is to be performed.

[0140] In step S304, the cross-domain MDA MnS producer 22 reports the causal analysis for the issues identified.

[0141] In step S305, the cross-domain MDA MnS producer 22 indicates the identified issues in the order of their magnitude.

[0142] In step S306, the cross-domain MDA MnS producer 22 indicates the optimized guidance in the same order of the magnitude of the issue.

[0143] In step S307, the cross-domain MDA MnS consumer 21 identifies and prepares actions to perform based on the causal analysis and optimized guidance.

[0144] In step S308, the cross-domain MDA MnS consumer 21, e.g operator's management system, performs the identified actions on domain NEs / NFs 25.

[0145] In steps S309 and S310, alternatively to steps S307 and S308, the cross-domain MDA MnS producer 22 can be able to prepare actions to perform based on the causal analysis and optimized guidance and then perform these actions on the domain NEs / NFs 25. In such a case, also steps S304 to S306 are optional.

[0146] In the following, there are shown some specific implementation examples of crossdomain analytics according to some example embodiments of the present invention with respect to document TS 28.104. It is of course to be mentioned that the present invention is not limited to these specific implementation examples.

[0147] Any aspects according to some example embodiments of the present invention to be implemented in TS 28.104 are indicated in italic font below.

[0148] As to section 9.3.1 of TS 28.104, a new attribute "supportedCapabilities" (cf. section 9.3.1.2) is added. Additionally, in section 9.3.2.1, regarding the definition of the MDARequest, it is added that "The attribute "requestedMDAOutputs" contains one or multiple "MDAOutputPerMDAType" elements, and each "MDAOutputPerMDAType" element supports filtering of MDA output and the domain in which the analytics is requested for a certain MDA type".

[0149] 9.3.1 MDAFunction

[0150] 9.3.1.1 Definition

[0151] The IOC MDAFunction represents the MDA function which supports one or more MDA capabilities.

[0152] 9.3.1.2 Attributes

[0153] Table 9.3.1.2-1

[0154] 9.3.1.3 Attribute constraints

[0155] None.

[0156] 9.3.1.4 Notifications

[0157] The common notifications defined in clause 9.6 are valid for this IOC, without exceptions or additions.

[0158] 9.3.2 MDARequest

[0159] 9.3.2.1 Definition

[0160] The IOC MDARequest represents the MDA output request created by an MnS consumer.

[0161] The attribute requestedMDAOutputs Contains one or multiple MDAOutputPerMDAType elements, and each MDAOutputPerMDAType element supports filtering of MDA output and the domain in which the analytics is requested for a certain MDA type. 9.3.2.2 Attributes

[0162] Table 9.3.2.2-1

[0163] 9.3.2.3 Attribute constraints

[0164] Table 9.3.2.3-1

[0165] 9.3.2.4 Notifications

[0166] The common notifications defined in clause 9.6 are valid for this IOC, without exceptions or additions.

[0167] In section 9.4 of TS 28.104 regarding the data type definitions, a definition of the "SupportedCapabilities <<datatype>>" (section 9.4.x) and a definition of the domainAnalytics <<choice>> (section 9.4.y) could be added as follows:

[0168] 9.4 Data type definitions

[0169] 9.4.x SupportedCapabilities <<datatype>>

[0170] 9.4.x.1 Definition

[0171] This <<datatype>> represents the capabilities possessed by a MDA Function.

[0172] The capabilities include the type of use cases and the domain in which the MDA function is capable of performing the analytics for the given use case.

[0173] The capabilities on the type of use cases can be represented by the "supportedMDAType" attribute. The domain capability is represented by "supportedDomain" for the given MDA type.

[0174] 9.4.x.2 Attributes

[0175] Table 9.4.X.2-1

[0176] 9.4.x.3 Attribute constraints None.

[0177] 9.4.x.4 Notifications

[0178] The <<IOC>> using this <<dataType>> for one of its attributes, shall be applicable.

[0179] 9.4.y DomainAnalytics <<choice>>

[0180] 9.4.y.l Definition

[0181] This <<choice>> defines whether the MDA functions is capable of performing cross-domain analytics or single domain analytics. The domains applicable for cross-domain analytics are RAN and Core. Accordingly, the choices of this type includes "RAN", "Core" and "Both". This would indicate whether the MDA function is capable of performing cross-domain analytics and single domain analytics. If the MDA function is capable of performing single domain analytics, it indicates the domain that is supported by the MDA function.

[0182] 9.4.y.2 Attributes

[0183] Table 9.4.y.2-1

[0184] 9.4.y.3 Attribute constraints

[0185] None.

[0186] 9.4.y.4 Notifications

[0187] The <<IOC>> using this <<dataType>> for one of its attributes, shall be applicable.

[0188] In the section 9.4.1 regarding the MDAOutputPerMDAType <<dataType>>, the attribute "requestedMDACapabilities" could be added (cf. section 9.4.1.3)

[0189] 9.4.1 MDAOutputPerMDAType <<dataType>>

[0190] 9.4.1.1 Definition

[0191] This <<dataType>> represents the analytics output filters for each MDA type for an MDA request. If only mD Type element is present (i.e. mDAOutputiEFiiters element is not present), then all of the MDA output information elements for this mDAType (see analytics output definitions per MDA capability in clause 8) are requested. if mDAOutputiEFiiters element is present, then only the listed analytics output information elements are requested and shall be reported according to the corresponding threshold.

[0192] 9.4.1.2 Attributes

[0193] Table 9.4.1.2-1

[0194] 9.4.1.3 Attribute constraints

[0195] None.

[0196] 9.4.1.4 Notifications

[0197] The <<IOC>> using this <<dataType>> for one of its attributes, shall be applicable.

[0198] Additionally, as to the attribute definitions and attribute propoerties in section 9.5 of TS 28.104, the attributes "supportedCapabilities", "domainAnalytics", and "requestedMDACapabilities" are defined as follows:

[0199] Table 9.5.1 -1

[0200] Furthermore, in section 8.4.2.1.3 regarding the analytics output, TN issue, UE issue and UE application issue are added to the definition of the information element "serviceExperiencelssueType" and the new information element "servisExperienceCausalAnalysis" is added. This information element contains the causal analysis and the optimized guidance for the identified issues in the causal analysis. 8.4.2.1.3 Analytics output

[0201] The specific information elements of the analytics output for service experience analysis, in addition to the common information elements of the analytics outputs (see clause 8.3), are provided in table 8.4.2.1.3-1.

[0202] Table 8.4.2.1.3-1 : Analytics output for Service experience analysis

[0203] Further, a new definition of the "CausalAnalysisAndRecommendations <<dataType>>" is to be added in section 8.5 of TS 28.104 as follows.

[0204] 8.5.x CausalAnalysisAndRecommendations <<dataType>>

[0205] 8.5.x.1 Definition This data type specifies the causal analysis and the optimal guidance for the specific usecase.

[0206] In section 8.5.x.2, the following information elements are defined: 8.5.x.2 Information elements

[0207] Table 8.5.X.2-1

[0208] In the following, a more general description of example versions of the present invention is made with respect to Figs. 4 to 9. Fig. 4 is a flowchart illustrating an example of a method according to some example versions of the present invention.

[0209] According to example versions of the present invention, the method may be implemented in or may be part of a cross-domain analytics data producer, like a cross-domain MDA MnS producer, or the like. The method comprises receiving, in a step S41, a cross-domain request for cross-domain data analytics from a cross-domain analytics data consumer, the cross-domain request being directed to at least two different specific domains; decomposing, in a step S42, the cross-domain request into domain specific requests for domain specific data analytics for each of the at least two different specific domains; sending, in a step S43, a domain specific request for supported capability of each specific domain to a domain specific analytics data producer of each of the specific domains; receiving, in a step S44, a domain specific response about the supported capability of each specific domain from the domain specific analytics data producer of each of the specific domains; determining, in a step S45, based on the domain specific response, whether the cross-domain data analytics is feasible; if it is determined, that the cross-domain data analytics is feasible, sending, in a step S46, domain specific requests for domain specific data analytics to each of the different specific domains; receiving, in a step S47, domain specific reports for the domain specific data analytics from each of the different specific domains; aggregating, in a step S48, the received domain specific reports and generating a cross-domain report for the requested cross-domain data analytics; and forwarding, in a step S49, the cross-domain report for the requested crossdomain data analytics to the cross-domain analytics data consumer.

[0210] According to some example versions of the present invention, the method further comprises sending a cross-domain feedback based on the cross-domain data analytics to the domain specific analytics data producer of each of the specific domains.

[0211] According to some example versions of the present invention, the cross-domain request for cross-domain data analytics from the cross-domain analytics data consumer includes information on a specific use case; and the method further comprises performing causal analysis for the specific use case based on the crossdomain data analytics and the domain specific data analytics. According to some example versions of the present invention, the causal analysis includes at least one of the following: identifying a specific issue; determining a source area of the specific issue; determining a cause of the specific issue; determining a source of the specific issue within the source area; or mapping the determined source of the specific issue and the determined cause of the specific issue and prioritizing them based on the magnitude of the problem caused by the issue.

[0212] According to some example versions of the present invention, the method further comprises elaborating an optimized guidance based on the causal analysis in order to solve the specific issue.

[0213] According to some example versions of the present invention, the method further comprises identifying and preparing actions to be performed based on the causal analysis for the specific use case and the elaborated optimized guidance; and performing the identified and prepared actions on a network element or network function of the specific domains.

[0214] According to some example versions of the present invention, the method further comprises forwarding the causal analysis and the elaborated optimized guidance for the specific use case to the cross-domain analytics data consumer.

[0215] According to some example versions of the present invention, the method further comprises, if it is determined, that the cross-domain data analytics is not feasible, informing the cross-domain analytics data consumer that the cross-domain data analytics cannot be performed.

[0216] According to some example versions of the present invention, the cross-domain analytics data producer is any management data analytics function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function. Fig. 5 is a flowchart illustrating another example of a method according to some example versions of the present invention.

[0217] According to example versions of the present invention, the method may be implemented in or may be part of a cross-domain analytics data consumer, like a cross-domain MDA MnS consumer, or the like. The method comprises sending, in a step S51, a cross-domain request for cross-domain data analytics to a cross-domain analytics data producer, the cross-domain request being directed to at least two different specific domains and including information on a specific use case; receiving, in a step S52, from the cross-domain analytics data producer, a causal analysis for the specific use case, the causal analysis including at least one of the following: information on a specific issue; information on a source area of the specific issue; information on a cause of the specific issue; information on a source of the specific issue within the source area; information on an association of the determined source of the specific issue and the determined cause of the specific issue and information on priority of them based on the magnitude of the problem caused by the issue; or information on an optimized guidance in order to solve the specific issue; identifying and preparing, in a step S53, actions to be performed based on the causal analysis for the specific use case and the optimized guidance; and performing, in a step S54, the identified and prepared actions on a network element or network function of the specific domains.

[0218] According to some example versions of the present invention, the cross-domain analytics data consumer is any management data analytics function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function. Fig. 6 is a block diagram illustrating an example of an apparatus according to some example versions of the present invention.

[0219] In Fig. 6, a block circuit diagram illustrating a configuration of an apparatus 60 is shown, which is configured to implement the above described various aspects of the invention. It is to be noted that the apparatus 60 shown in Fig. 6 may comprise several further elements or functions besides those described herein below, which are omitted herein for the sake of simplicity as they are not essential for understanding the invention. Furthermore, the apparatus may be also another device having a similar function, such as a chipset, a chip, a module etc., which can also be part of an apparatus or attached as a separate element to the apparatus, or the like.

[0220] The apparatus 60 may comprise a processing function or processor 61, such as a CPU or the like, which executes instructions given by programs or the like. The processor 61 may comprise one or more processing portions dedicated to specific processing as described below, or the processing may be run in a single processor. Portions for executing such specific processing may be also provided as discrete elements or within one or further processors or processing portions, such as in one physical processor like a CPU or in several physical entities, for example. Reference sign 62 denotes transceiver or input / output (I / O) units (interfaces) connected to the processor 61. The I / O units 62 may be used for communicating with one or more other network elements, entities, terminals or the like. The I / O units 62 may be a combined unit comprising communication equipment towards several network elements, or may comprise a distributed structure with a plurality of different interfaces for different network elements. The apparatus 60 further comprises at least one memory 63 usable, for example, for storing data and programs to be executed by the processor 61 and / or as a working storage of the processor 61.

[0221] The processor 61 is configured to execute processing related to the abovedescribed aspects.

[0222] In particular, the apparatus 60 may be implemented in or may be part of a crossdomain analytics data producer, like a cross-domain MDA MnS producer, or the like and may be configured to perform processing as described in connection with Fig. 4.

[0223] Thus, according to some example versions of the present invention, there is provided an apparatus 60 for use in a cross-domain analytics data producer, comprising at least one processor 61, and at least one memory 63 storing instructions that, when executed by the at least one processor 61, cause the apparatus 60 at least to perform receiving a cross-domain request for cross-domain data analytics from a cross-domain analytics data consumer, the cross-domain request being directed to at least two different specific domains; decomposing the cross-domain request into domain specific requests for domain specific data analytics for each of the at least two different specific domains; sending a domain specific request for supported capability of each specific domain to a domain specific analytics data producer of each of the specific domains; receiving a domain specific response about the supported capability of each specific domain from the domain specific analytics data producer of each of the specific domains; determining based on the domain specific response, whether the crossdomain data analytics is feasible; if it is determined, that the cross-domain data analytics is feasible, sending domain specific requests for domain specific data analytics to each of the different specific domains; receiving domain specific reports for the domain specific data analytics from each of the different specific domains; aggregating the received domain specific reports and generating a crossdomain report for the requested cross-domain data analytics; and forwarding the cross-domain report for the requested cross-domain data analytics to the cross-domain analytics data consumer.

[0224] According to some example versions of the present invention, the apparatus is further caused to perform : sending a cross-domain feedback based on the cross-domain data analytics to the domain specific analytics data producer of each of the specific domains.

[0225] According to some example versions of the present invention, the cross-domain request for cross-domain data analytics from the cross-domain analytics data consumer includes information on a specific use case; and the apparatus is further caused to perform performing causal analysis for the specific use case based on the cross-domain data analytics and the domain specific data analytics.

[0226] According to some example versions of the present invention, the causal analysis includes at least one of the following: identifying a specific issue; determining a source area of the specific issue; determining a cause of the specific issue; determining a source of the specific issue within the source area; or mapping the determined source of the specific issue and the determined cause of the specific issue and prioritizing them based on the magnitude of the problem caused by the issue.

[0227] According to some example versions of the present invention, the apparatus is further caused to perform elaborating an optimized guidance based on the causal analysis in order to solve the specific issue.

[0228] According to some example versions of the present invention, the apparatus is further caused to perform identifying and preparing actions to be performed based on the causal analysis for the specific use case and the elaborated optimized guidance; and performing the identified and prepared actions on a network element or network function of the specific domains.

[0229] According to some example versions of the present invention, the apparatus is further caused to perform forwarding the causal analysis and the elaborated optimized guidance for the specific use case to the cross-domain analytics data consumer. According to some example versions of the present invention, the apparatus is further caused to perform, if it is determined, that the cross-domain data analytics is not feasible, informing the cross-domain analytics data consumer that the crossdomain data analytics cannot be performed.

[0230] According to some example versions of the present invention, the cross-domain analytics data producer is any Management Data Analytics Function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function.

[0231] Fig. 7 is a block diagram illustrating another example of an apparatus according to some example versions of the present invention.

[0232] In Fig. 7, a block circuit diagram illustrating a configuration of an apparatus 70 is shown, which is configured to implement the above described various aspects of the invention. It is to be noted that the apparatus 70 shown in Fig. 7 may comprise several further elements or functions besides those described herein below, which are omitted herein for the sake of simplicity as they are not essential for understanding the invention. Furthermore, the apparatus may be also another device having a similar function, such as a chipset, a chip, a module etc., which can also be part of an apparatus or attached as a separate element to the apparatus, or the like.

[0233] The apparatus 70 may comprise a processing function or processor 71, such as a CPU or the like, which executes instructions given by programs or the like. The processor 71 may comprise one or more processing portions dedicated to specific processing as described below, or the processing may be run in a single processor. Portions for executing such specific processing may be also provided as discrete elements or within one or further processors or processing portions, such as in one physical processor like a CPU or in several physical entities, for example. Reference sign 72 denotes transceiver or input / output (I / O) units (interfaces) connected to the processor 71. The I / O units 72 may be used for communicating with one or more other network elements, entities, terminals or the like. The I / O units 72 may be a combined unit comprising communication equipment towards several network elements, or may comprise a distributed structure with a plurality of different interfaces for different network elements. The apparatus 70 further comprises at least one memory 73 usable, for example, for storing data and programs to be executed by the processor 71 and / or as a working storage of the processor 71.

[0234] The processor 71 is configured to execute processing related to the abovedescribed aspects.

[0235] In particular, the apparatus 70 may be implemented in or may be part of a crossdomain analytics data consumer, like a cross-domain MDA MnS consumer, or the like and may be configured to perform processing as described in connection with Fig. 5.

[0236] Thus, according to some example versions of the present invention, there is provided an apparatus 70 for use in a cross-domain analytics data consumer, comprising at least one processor 71, and at least one memory 73 storing instructions that, when executed by the at least one processor 71, cause the apparatus 70 at least to perform sending a cross-domain request for cross-domain data analytics to a crossdomain analytics data producer, the cross-domain request being directed to at least two different specific domains and including information on a specific use case; receiving, from the cross-domain analytics data producer, a causal analysis for the specific use case, the causal analysis including at least one of the following: information on a specific issue; information on a source area of the specific issue; information on a cause of the specific issue; information on a source of the specific issue within the source area; information on an association of the determined source of the specific issue and the determined cause of the specific issue and information on priority of them based on the magnitude of the problem caused by the issue; or information on an optimized guidance in order to solve the specific issue; identifying and preparing actions to be performed based on the causal analysis for the specific use case and the optimized guidance; and performing the identified and prepared actions on a network element or network function of the specific domains.

[0237] According to some example versions of the present invention, the cross-domain analytics data consumer is any Management Data Analytics Function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function

[0238] Further, the present invention may be implement by an apparatus for a crossdomain analytics data producer, like a cross-domain MDA MnS producer comprising means for performing the above-described processing, as shown in Fig. 8.

[0239] That is, according to some example versions of the present invention, as shown in Fig. 8, the apparatus for use in a cross-domain analytics data producer comprises means 81 for receiving a cross-domain request for cross-domain data analytics from a cross-domain analytics data consumer, the cross-domain request being directed to at least two different specific domains; means 82 for decomposing the cross-domain request into domain specific requests for domain specific data analytics for each of the at least two different specific domains; means 83 for sending a domain specific request for supported capability of each specific domain to a domain specific analytics data producer of each of the specific domains; means 84 for receiving a domain specific response about the supported capability of each specific domain from the domain specific analytics data producer of each of the specific domains; means 85 for determining based on the domain specific response, whether the cross-domain data analytics is feasible; means 86 for sending, if it is determined, that the cross-domain data analytics is feasible, domain specific requests for domain specific data analytics to each of the different specific domains; means 87 for receiving domain specific reports for the domain specific data analytics from each of the different specific domains; means 88 for aggregating the received domain specific reports and generating a cross-domain report for the requested cross-domain data analytics; and means 89 for forwarding the cross-domain report for the requested crossdomain data analytics to the cross-domain analytics data consumer.

[0240] According to some example versions of the present invention, the apparatus further comprises means for sending a cross-domain feedback based on the crossdomain data analytics to the domain specific analytics data producer of each of the specific domains.

[0241] According to some example versions of the present invention, the cross-domain request for cross-domain data analytics from the cross-domain analytics data consumer includes information on a specific use case; and the apparatus further comprises means for performing causal analysis for the specific use case based on the cross-domain data analytics and the domain specific data analytics.

[0242] According to some example versions of the present invention, the means for performing causal analysis includes at least one of the following: means for identifying a specific issue; means for determining a source area of the specific issue; means for determining a cause of the specific issue; means for determining a source of the specific issue within the source area; or means for mapping the determined source of the specific issue and the determined cause of the specific issue and prioritizing them based on the magnitude of the problem caused by the issue.

[0243] According to some example versions of the present invention, the apparatus further comprises means for elaborating an optimized guidance based on the causal analysis in order to solve the specific issue. According to some example versions of the present invention, the apparatus further comprises means for identifying and preparing actions to be performed based on the causal analysis for the specific use case and the elaborated optimized guidance; and means for performing the identified and prepared actions on a network element or network function of the specific domains.

[0244] According to some example versions of the present invention, the apparatus further comprises means for forwarding the causal analysis and the elaborated optimized guidance for the specific use case to the cross-domain analytics data consumer.

[0245] According to some example versions of the present invention, the apparatus further comprises means for, if it is determined, that the cross-domain data analytics is not feasible, informing the cross-domain analytics data consumer that the cross-domain data analytics cannot be performed.

[0246] According to some example versions of the present invention, the cross-domain analytics data producer is any Management Data Analytics Function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function.

[0247] Further, the present invention may be implement by an apparatus for a crossdomain analytics data consumer, like a cross-domain MDA MnS consumer comprising means for performing the above-described processing, as shown in Fig. 9.

[0248] That is, according to some example versions of the present invention, as shown in Fig. 9, the apparatus for use in a cross-domain analytics data consumer comprises means 91 for sending a cross-domain request for cross-domain data analytics to a cross-domain analytics data producer, the cross-domain request being directed to at least two different specific domains and including information on a specific use case; means 92 for receiving, from the cross-domain analytics data producer, a causal analysis for the specific use case, the causal analysis including at least one of the following: information on a specific issue; information on a source area of the specific issue; information on a cause of the specific issue; information on a source of the specific issue within the source area; information on an association of the determined source of the specific issue and the determined cause of the specific issue and information on priority of them based on the magnitude of the problem caused by the issue; or information on an optimized guidance in order to solve the specific issue; means 93 for identifying and preparing actions to be performed based on the causal analysis for the specific use case and the optimized guidance; and means 94 for performing the identified and prepared actions on a network element or network function of the specific domains.

[0249] According to some example versions of the present invention, the cross-domain analytics data consumer is any Management Data Analytics Function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function.

[0250] Additionally, according to some example versions of the present invention, there is provided a computer program product for a computer, including software code portions for, when said product is run on the computer, performing receiving a cross-domain request for cross-domain data analytics from a cross-domain analytics data consumer, the cross-domain request being directed to at least two different specific domains; decomposing the cross-domain request into domain specific requests for domain specific data analytics for each of the at least two different specific domains; sending a domain specific request for supported capability of each specific domain to a domain specific analytics data producer of each of the specific domains; receiving a domain specific response about the supported capability of each specific domain from the domain specific analytics data producer of each of the specific domains; determining based on the domain specific response, whether the crossdomain data analytics is feasible; if it is determined, that the cross-domain data analytics is feasible, sending domain specific requests for domain specific data analytics to each of the different specific domains; receiving domain specific reports for the domain specific data analytics from each of the different specific domains; aggregating the received domain specific reports and generating a crossdomain report for the requested cross-domain data analytics; and forwarding the cross-domain report for the requested cross-domain data analytics to the cross-domain analytics data consumer.

[0251] According to some example versions of the present invention, the computer program product for the computer includes software code portions for, when said product is run on the computer, performing sending a cross-domain feedback based on the cross-domain data analytics to the domain specific analytics data producer of each of the specific domains.

[0252] According to some example versions of the present invention, the cross-domain request for cross-domain data analytics from the cross-domain analytics data consumer includes information on a specific use case; and the computer program product for the computer includes software code portions for, when said product is run on the computer, performing causal analysis for the specific use case based on the cross-domain data analytics and the domain specific data analytics.

[0253] According to some example versions of the present invention, the causal analysis includes at least one of the following: identifying a specific issue; determining a source area of the specific issue; determining a cause of the specific issue; determining a source of the specific issue within the source area; or mapping the determined source of the specific issue and the determined cause of the specific issue and prioritizing them based on the magnitude of the problem caused by the issue. According to some example versions of the present invention, the cross-domain request for cross-domain data analytics from the cross-domain analytics data consumer includes information on a specific use case; and the computer program product for the computer includes software code portions for, when said product is run on the computer, performing: elaborating an optimized guidance based on the causal analysis in order to solve the specific issue.

[0254] According to some example versions of the present invention, the cross-domain request for cross-domain data analytics from the cross-domain analytics data consumer includes information on a specific use case; and the computer program product for the computer includes software code portions for, when said product is run on the computer, performing identifying and preparing actions to be performed based on the causal analysis for the specific use case and the elaborated optimized guidance; and performing the identified and prepared actions on a network element or network function of the specific domains.

[0255] According to some example versions of the present invention, the cross-domain request for cross-domain data analytics from the cross-domain analytics data consumer includes information on a specific use case; and the computer program product for the computer includes software code portions for, when said product is run on the computer, performing forwarding the causal analysis and the elaborated optimized guidance for the specific use case to the cross-domain analytics data consumer.

[0256] According to some example versions of the present invention, the cross-domain request for cross-domain data analytics from the cross-domain analytics data consumer includes information on a specific use case; and the computer program product for the computer includes software code portions for, when said product is run on the computer, performing, if it is determined, that the cross-domain data analytics is not feasible, informing the cross-domain analytics data consumer that the cross-domain data analytics cannot be performed. According to some example versions of the present invention, the cross-domain analytics data producer is any Management Data Analytics Function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function.

[0257] Additionally, according to some example versions of the present invention, there is provided a computer program product for a computer, including software code portions for, when said product is run on the computer, performing sending a cross-domain request for cross-domain data analytics to a crossdomain analytics data producer, the cross-domain request being directed to at least two different specific domains and including information on a specific use case; receiving, from the cross-domain analytics data producer, a causal analysis for the specific use case, the causal analysis including at least one of the following: information on a specific issue; information on a source area of the specific issue; information on a cause of the specific issue; information on a source of the specific issue within the source area; information on an association of the determined source of the specific issue and the determined cause of the specific issue and information on priority of them based on the magnitude of the problem caused by the issue; or information on an optimized guidance in order to solve the specific issue; identifying and preparing actions to be performed based on the causal analysis for the specific use case and the optimized guidance; and performing the identified and prepared actions on a network element or network function of the specific domains.

[0258] According to some example versions of the present invention, the cross-domain analytics data consumer is any Management Data Analytics Function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function. The computer program product may comprise software code portion adapted to produce steps of any of the methods as described above when loaded into the memory of a computer.

[0259] According to some example versions of the present invention, there is provided a computer program product as defined above, wherein the computer program product comprises a computer-readable medium on which the software code portions are stored.

[0260] According to some example versions of the present invention, there is provided a computer program product as defined above, wherein the computer program product is directly loadable into the internal memory of the computer and / or transmittable via a network by means of at least one of upload, download and push procedures.

[0261] According to some example versions of the present invention, there is provided a computer readable medium storing a computer program as set out above.

[0262] According to some example versions of the present invention, there is provided a computer program product comprising computer-executable computer program code which, when the program is run on a computer (e.g. a computer of an apparatus according to any one of the aforementioned apparatus-related exemplary aspects of the present disclosure), is configured to cause the computer to carry out the method according to any one of the aforementioned method- related exemplary aspects of the present disclosure.

[0263] Such computer program product may comprise (or be embodied) a (tangible) computer-readable (storage) medium or the like on which the computerexecutable computer program code is stored, and / or the program may be directly loadable into an internal memory of the computer or a processor thereof.

[0264] Furthermore, the present invention may be implement by an apparatus for use in a cross-domain analytics data producer comprising respective circuitry for performing the above-described processing. That is, according to some example versions of the present invention, there is provided an apparatus for use in a cross-domain analytics data producer, comprising reception circuitry for receiving a cross-domain request for cross-domain data analytics from a cross-domain analytics data consumer, the cross-domain request being directed to at least two different specific domains; decomposition circuitry for decomposing the cross-domain request into domain specific requests for domain specific data analytics for each of the at least two different specific domains; sending circuitry for sending a domain specific request for supported capability of each specific domain to a domain specific analytics data producer of each of the specific domains; reception circuitry for receiving a domain specific response about the supported capability of each specific domain from the domain specific analytics data producer of each of the specific domains; determination circuitry for determining based on the domain specific response, whether the cross-domain data analytics is feasible; sending circuitry for if it is determined, that the cross-domain data analytics is feasible, sending domain specific requests for domain specific data analytics to each of the different specific domains; reception circuitry for receiving domain specific reports for the domain specific data analytics from each of the different specific domains; aggregation circuitry for aggregating the received domain specific reports and generating a cross-domain report for the requested cross-domain data analytics; and forwarding circuitry for forwarding the cross-domain report for the requested cross-domain data analytics to the cross-domain analytics data consumer.

[0265] According to some example versions of the present invention, the apparatus further comprises sending circuitry for sending a cross-domain feedback based on the cross-domain data analytics to the domain specific analytics data producer of each of the specific domains. According to some example versions of the present invention, the cross-domain request for cross-domain data analytics from the cross-domain analytics data consumer includes information on a specific use case; and the apparatus further comprises performing circuitry for performing causal analysis for the specific use case based on the cross-domain data analytics and the domain specific data analytics.

[0266] According to some example versions of the present invention, the causal analysis includes at least one of the following: identifying a specific issue; determining a source area of the specific issue; determining a cause of the specific issue; determining a source of the specific issue within the source area; or mapping the determined source of the specific issue and the determined cause of the specific issue and prioritizing them based on the magnitude of the problem caused by the issue.

[0267] According to some example versions of the present invention, the apparatus further comprises elaborating circuitry for elaborating an optimized guidance based on the causal analysis in order to solve the specific issue.

[0268] According to some example versions of the present invention, the apparatus further comprises identifying and preparing circuitry for identifying and preparing actions to be performed based on the causal analysis for the specific use case and the elaborated optimized guidance; and performing circuitry for performing the identified and prepared actions on a network element or network function of the specific domains.

[0269] According to some example versions of the present invention, the apparatus further comprises forwarding circuitry for forwarding the causal analysis and the elaborated optimized guidance for the specific use case to the cross-domain analytics data consumer. According to some example versions of the present invention, the apparatus further comprises informing circuitry for, if it is determined, that the cross-domain data analytics is not feasible, informing the cross-domain analytics data consumer that the cross-domain data analytics cannot be performed.

[0270] According to some example versions of the present invention, the cross-domain analytics data producer is any Management Data Analytics Function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function.

[0271] Furthermore, the present invention may be implement by an apparatus for use in a cross-domain analytics data consumer comprising respective circuitry for performing the above-described processing.

[0272] That is, according to some example versions of the present invention, there is provided an apparatus for use in a cross-domain analytics data consumer, comprising sending circuitry for sending a cross-domain request for cross-domain data analytics to a cross-domain analytics data producer, the cross-domain request being directed to at least two different specific domains and including information on a specific use case; reception circuitra for receiving, from the cross-domain analytics data producer, a causal analysis for the specific use case, the causal analysis including at least one of the following: information on a specific issue; information on a source area of the specific issue; information on a cause of the specific issue; information on a source of the specific issue within the source area; information on an association of the determined source of the specific issue and the determined cause of the specific issue and information on priority of them based on the magnitude of the problem caused by the issue; or information on an optimized guidance in order to solve the specific issue; identification and preparation circuitry for identifying and preparing actions to be performed based on the causal analysis for the specific use case and the optimized guidance; and performing circuitry for performing the identified and prepared actions on a network element or network function of the specific domains.

[0273] According to some example versions of the present invention, the cross-domain analytics data consumer is any Management Data Analytics Function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function.

[0274] For further details regarding the functions of the apparatuses and the computer programs, reference is made to the above description of the methods according to some example versions of the present invention, as described in connection with Figs. 4 and 5.

[0275] In the foregoing exemplary description of the apparatus, only the units / means that are relevant for understanding the principles of the invention have been described using functional blocks. The apparatus may comprise further units / means that are necessary for its respective operation, respectively. However, a description of these units / means is omitted in this specification. The arrangement of the functional blocks of the appar atus is not to be construed to limit the invention, and the functions may be performed by one block or further split into sub-blocks.

[0276] When in the foregoing description it is stated that the apparatus (or some other means) is configured to perform some function, this is to be construed to be equivalent to a description stating that a (i.e. at least one) processor or corresponding circuitry, potentially in cooperation with computer program code stored in the memory of the respective apparatus, is configured to cause the apparatus to perform at least the thus mentioned function. Also, such function is to be construed to be equivalently implementable by specifically configured circuitry or means for performing the respective function (i.e. the expression "unit configured to" is to be construed to be equivalent to an expression such as "means for"). As used in this application, the term "circuitry" may refer to one or more or all of the following:

[0277] (a) hardware-only circuit implementations (such as implementations in only analog and / or digital circuitry) and

[0278] (b) combinations of hardware circuits and software, such as (as applicable):

[0279] (i) a combination of analog and / or digital hardware circuit(s) with softwa re / f i rm wa re and

[0280] (ii) any portions of hardware processor(s) with software (including digital signal processor(s)), software, and memory(ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions) and

[0281] (c) hardware circuit(s) and or processor(s), such as a microprocessor(s) or a portion of a microprocessor(s), that requires software (e.g., firmware) for operation, but the software may not be present when it is not needed for operation.

[0282] This definition of circuitry applies to all uses of this term in this application, including in any claims. As a further example, as used in this application, the term circuitry also covers an implementation of merely a hardware circuit or processor (or multiple processors) or portion of a hardware circuit or processor and its (or their) accompanying software and / or firmware. The term circuitry also covers, for example and if applicable to the particular claim element, a baseband integrated circuit or processor integrated circuit for a mobile device or a similar integrated circuit in server, a cellular network device, or other computing or network device.

[0283] For the purpose of the present invention as described herein above, it should be noted that

[0284] - method steps likely to be implemented as software code portions and being run using a processor at an apparatus (as examples of devices, apparatuses and / or modules thereof, or as examples of entities including apparatuses and / or modules therefore), are software code independent and can be specified using any known or future developed programming language as long as the functionality defined by the method steps is preserved; - generally, any method step is suitable to be implemented as software or by hardware without changing the idea of the aspects / embodiments and its modification in terms of the functionality implemented;

[0285] - method steps and / or devices, units or means likely to be implemented as hardware components at the above-defined apparatuses, or any module(s) thereof, (e.g., devices carrying out the functions of the apparatuses according to the aspects / embodiments as described above) are hardware independent and can be implemented using any known or future developed hardware technology or any hybrids of these, such as MOS (Metal Oxide Semiconductor), CMOS (Complementary MOS), BiMOS (Bipolar MOS), BiCMOS (Bipolar CMOS), ECL (Emitter Coupled Logic), TTL (Transistor-Transistor Logic), etc., using for example ASIC (Application Specific IC (Integrated Circuit)) components, FPGA (Field- programmable Gate Arrays) components, CPLD (Complex Programmable Logic Device) components, APU (Accelerated Processor Unit), GPU (Graphics Processor Unit) or DSP (Digital Signal Processor) components;

[0286] - devices, units or means (e.g. the above-defined apparatuses, or any one of their respective units / means) can be implemented as individual devices, units or means, but this does not exclude that they are implemented in a distributed fashion throughout the system, as long as the functionality of the device, unit or means is preserved;

[0287] - an apparatus may be represented by a semiconductor chip, a chipset, or a (hardware) module comprising such chip or chipset; this, however, does not exclude the possibility that a functionality of an apparatus or module, instead of being hardware implemented, be implemented as software in a (software) module such as a computer program or a computer program product comprising executable software code portions for execution / being run on a processor;

[0288] - a device may be regarded as an apparatus or as an assembly of more than one apparatus, whether functionally in cooperation with each other or functionally independently of each other but in a same device housing, for example.

[0289] In general, it is to be noted that respective functional blocks or elements according to above-described aspects can be implemented by any known means, either in hardware and / or software, respectively, if it is only adapted to perform the described functions of the respective parts. The mentioned method steps can be realized in individual functional blocks or by individual devices, or one or more of the method steps can be realized in a single functional block or by a single device.

[0290] Generally, any method step is suitable to be implemented as software or by hardware without changing the idea of the present invention. Devices and means can be implemented as individual devices, but this does not exclude that they are implemented in a distributed fashion throughout the system, as long as the functionality of the device is preserved. Such and similar principles are to be considered as known to a skilled person.

[0291] Software in the sense of the present description comprises software code as such comprising code means or portions or a computer program or a computer program product for performing the respective functions, as well as software (or a computer program or a computer program product) embodied on a tangible medium such as a computer-readable (storage) medium having stored thereon a respective data structure or code means / portions or embodied in a signal or in a chip, potentially during processing thereof.

[0292] It is to be noted that the aspects / embodiments and general and specific examples described above are provided for illustrative purposes only and are in no way intended that the present invention is restricted thereto. Rather, it is the intention that all variations and modifications which fall within the scope of the appended claims are covered.

Claims

Claims1. An apparatus for use in a cross-domain analytics data producer, comprising, at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to perform: receiving a cross-domain request for cross-domain data analytics from a cross-domain analytics data consumer, the cross-domain request being directed to at least two different specific domains; decomposing the cross-domain request into domain specific requests for domain specific data analytics for each of the at least two different specific domains; sending a domain specific request for supported capability of each specific domain to a domain specific analytics data producer of each of the specific domains; receiving a domain specific response about the supported capability of each specific domain from the domain specific analytics data producer of each of the specific domains; determining based on the domain specific response, whether the crossdomain data analytics is feasible; if it is determined, that the cross-domain data analytics is feasible, sending domain specific requests for domain specific data analytics to each of the different specific domains; receiving domain specific reports for the domain specific data analytics from each of the different specific domains; aggregating the received domain specific reports and generating a crossdomain report for the requested cross-domain data analytics; and forwarding the cross-domain report for the requested cross-domain data analytics to the cross-domain analytics data consumer.

2. The apparatus according to claim 1, wherein the apparatus is further caused to perform :sending a cross-domain feedback based on the cross-domain data analytics to the domain specific analytics data producer of each of the specific domains.

3. The apparatus according to claim 1 or 2, wherein the cross-domain request for cross-domain data analytics from the crossdomain analytics data consumer includes information on a specific use case; and the apparatus is further caused to perform: performing causal analysis for the specific use case based on the crossdomain data analytics and the domain specific data analytics.

4. The apparatus according to claim 3, wherein the causal analysis includes at least one of the following: identifying a specific issue; determining a source area of the specific issue; determining a cause of the specific issue; determining a source of the specific issue within the source area; or mapping the determined source of the specific issue and the determined cause of the specific issue and prioritizing them based on the magnitude of the problem caused by the issue.

5. The apparatus according to claim 4, wherein the apparatus is further caused to perform : elaborating an optimized guidance based on the causal analysis in order to solve the specific issue.

6. The apparatus according to claim 5, wherein the apparatus is further caused to perform : identifying and preparing actions to be performed based on the causal analysis for the specific use case and the elaborated optimized guidance; and performing the identified and prepared actions on a network element or network function of the specific domains.

7. The apparatus according to claim 5, wherein the apparatus is further caused to perform :forwarding the causal analysis and the elaborated optimized guidance for the specific use case to the cross-domain analytics data consumer.

8. The apparatus according to claim 1, wherein the apparatus is further caused to perform : if it is determined, that the cross-domain data analytics is not feasible, informing the cross-domain analytics data consumer that the cross-domain data analytics cannot be performed.

9. The apparatus according to anyone of claims 1 to 8, wherein the cross-domain analytics data producer is any management data analytics function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function.

10. An apparatus for use in a cross-domain analytics data consumer, comprising, at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to perform: sending a cross-domain request for cross-domain data analytics to a crossdomain analytics data producer, the cross-domain request being directed to at least two different specific domains and including information on a specific use case; receiving, from the cross-domain analytics data producer, a causal analysis for the specific use case, the causal analysis including at least one of the following: information on a specific issue; information on a source area of the specific issue; information on a cause of the specific issue; information on a source of the specific issue within the source area; information on an association of the determined source of the specific issue and the determined cause of the specific issue and information on priority of them based on the magnitude of the problem caused by the issue; or information on an optimized guidance in order to solve the specific issue;identifying and preparing actions to be performed based on the causal analysis for the specific use case and the optimized guidance; and performing the identified and prepared actions on a network element or network function of the specific domains.

11. The apparatus according to claim 10, wherein the cross-domain analytics data consumer is any management data analytics function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function.

12. An apparatus for use in a cross-domain analytics data producer, comprising, means for receiving a cross-domain request for cross-domain data analytics from a cross-domain analytics data consumer, the cross-domain request being directed to at least two different specific domains; means for decomposing the cross-domain request into domain specific requests for domain specific data analytics for each of the at least two different specific domains; means for sending a domain specific request for supported capability of each specific domain to a domain specific analytics data producer of each of the specific domains; means for receiving a domain specific response about the supported capability of each specific domain from the domain specific analytics data producer of each of the specific domains; means for determining based on the domain specific response, whether the cross-domain data analytics is feasible; means for sending, if it is determined, that the cross-domain data analytics is feasible, domain specific requests for domain specific data analytics to each of the different specific domains; means for receiving domain specific reports for the domain specific data analytics from each of the different specific domains; means for aggregating the received domain specific reports and generating a cross-domain report for the requested cross-domain data analytics; and means for forwarding the cross-domain report for the requested crossdomain data analytics to the cross-domain analytics data consumer.

13. The apparatus according to claim 12, further comprising: means for sending a cross-domain feedback based on the cross-domain data analytics to the domain specific analytics data producer of each of the specific domains.

14. The apparatus according to claim 12 or 13, wherein the cross-domain request for cross-domain data analytics from the crossdomain analytics data consumer includes information on a specific use case; and the apparatus further comprising: means for performing causal analysis for the specific use case based on the cross-domain data analytics and the domain specific data analytics.

15. The apparatus according to claim 14, wherein the means for performing causal analysis includes at least one of the following: means for identifying a specific issue; means for determining a source area of the specific issue; means for determining a cause of the specific issue; means for determining a source of the specific issue within the source area; or means for mapping the determined source of the specific issue and the determined cause of the specific issue and prioritizing them based on the magnitude of the problem caused by the issue.

16. The apparatus according to claim 15, further comprising: means for elaborating an optimized guidance based on the causal analysis in order to solve the specific issue.

17. The apparatus according to claim 16, further comprising: means for identifying and preparing actions to be performed based on the causal analysis for the specific use case and the elaborated optimized guidance; andmeans for performing the identified and prepared actions on a network element or network function of the specific domains.

18. The apparatus according to claim 16, further comprising: means for forwarding the causal analysis and the optimized guidance for the specific use case to the cross-domain analytics data consumer.

19. The apparatus according to claim 12, further comprising: means for informing, if it is determined, that the cross-domain data analytics is not feasible, the cross-domain analytics data consumer that the cross-domain data analytics cannot be performed.

20. The apparatus according to anyone of claims 12 to 19, wherein the cross-domain analytics data producer is any management data analytics function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function.

21. An apparatus for use in a cross-domain analytics data consumer, comprising: means for sending a cross-domain request for cross-domain data analytics to a cross-domain analytics data producer, the cross-domain request being directed to at least two different specific domains and including information on a specific use case; means for receiving, from the cross-domain analytics data producer, a causal analysis for the specific use case, the causal analysis including at least one of the following: information on a specific issue; information on a source area of the specific issue; information on a cause of the specific issue; information on a source of the specific issue within the source area; information on an association of the determined source of the specific issue and the determined cause of the specific issue and information on priority of them based on the magnitude of the problem caused by the issue; orinformation on an optimized guidance in order to solve the specific issue; means for identifying and preparing actions to be performed based on the causal analysis for the specific use case and the optimized guidance; and means for performing the identified and prepared actions on a network element or network function of the specific domains.

22. The apparatus according to claim 21, wherein the cross-domain analytics data consumer is any management data analytics function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function.

23. A method for use in a cross-domain analytics data producer, comprising: receiving a cross-domain request for cross-domain data analytics from a cross-domain analytics data consumer, the cross-domain request being directed to at least two different specific domains; decomposing the cross-domain request into domain specific requests for domain specific data analytics for each of the at least two different specific domains; sending a domain specific request for supported capability of each specific domain to a domain specific analytics data producer of each of the specific domains; receiving a domain specific response about the supported capability of each specific domain from the domain specific analytics data producer of each of the specific domains; determining based on the domain specific response, whether the crossdomain data analytics is feasible; if it is determined, that the cross-domain data analytics is feasible, sending domain specific requests for domain specific data analytics to each of the different specific domains; receiving domain specific reports for the domain specific data analytics from each of the different specific domains; aggregating the received domain specific reports and generating a crossdomain report for the requested cross-domain data analytics; andforwarding the cross-domain report for the requested cross-domain data analytics to the cross-domain analytics data consumer.

24. The method according to claim 23, further comprising: sending a cross-domain feedback based on the cross-domain data analytics to the domain specific analytics data producer of each of the specific domains.

25. The method according to claim 23 or 24, wherein the cross-domain request for cross-domain data analytics from the crossdomain analytics data consumer includes information on a specific use case; and the method further comprises: performing causal analysis for the specific use case based on the crossdomain data analytics and the domain specific data analytics;26. The method according to claim 25, wherein the causal analysis includes at least one of the following: identifying a specific issue; determining a source area of the specific issue; determining a cause of the specific issue; determining a source of the specific issue within the source area; or mapping the determined source of the specific issue and the determined cause of the specific issue and prioritizing them based on the magnitude of the problem caused by the issue.

27. The method according to claim 26, further comprising: elaborating an optimized guidance based on the causal analysis in order to solve the specific issue.

28. The method according to claim 27, further comprising: identifying and preparing actions to be performed based on the causal analysis for the specific use case and the elaborated optimized guidance; and performing the identified and prepared actions on a network element or network function of the specific domains.

29. The method according to claim 27, further comprising: forwarding the causal analysis and the elaborated optimized guidance for the specific use case to the cross-domain analytics data consumer.

30. The method according to claim 23, further comprising: if it is determined, that the cross-domain data analytics is not feasible, informing the cross-domain analytics data consumer that the cross-domain data analytics cannot be performed.

31. The method according to any of claims 23 to 30, wherein the cross-domain analytics data producer is any management data analytics function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function.

32. A method for use in a cross-domain analytics data consumer, comprising: sending a cross-domain request for cross-domain data analytics to a crossdomain analytics data producer, the cross-domain request being directed to at least two different specific domains and including information on a specific use case; receiving, from the cross-domain analytics data producer, a causal analysis for the specific use case, the causal analysis including at least one of the following: information on a specific issue; information on a source area of the specific issue; information on a cause of the specific issue; information on a source of the specific issue within the source area; information on an association of the determined source of the specific issue and the determined cause of the specific issue and information on priority of them based on the magnitude of the problem caused by the issue; or information on an optimized guidance in order to solve the specific issue; identifying and preparing actions to be performed based on the causal analysis for the specific use case and the optimized guidance; andperforming the identified and prepared actions on a network element or network function of the specific domains.

33. The method according to claim 32, wherein the cross-domain analytics data consumer is any management data analytics function, MDAF, any network data analytics function, NWDAF, any gNB or any core network function.

34. A computer program product for a computer, including software code portions for performing the steps of any of claims 23 to 33, when said product is run on the computer.

35. The computer program product according to claim 34, wherein the computer program product includes a computer-readable medium on which said software code portions are stored, and / or the computer program product is directly loadable into the internal memory of the computer and / or transmittable via a network by means of at least one of upload, download and push procedures.

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