Method and apparatus for enforcing valid confidence levels

Abstract

The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. According to an embodiment of the disclosure, a method performed by a first entity may include receiving, from a second entity, a message associated with at least one expected user equipment behaviour parameter, identifying whether at least one of confidence level or accuracy level of the at least one expected UE behaviour parameter is out of range and transmitting, to the second entity, an error message based on the identification.

Description

METHOD AND APPARATUS FOR ENFORCING VALID CONFIDENCE LEVELSThe present disclosure relates to a wireless communication, and more specifically related to a method and an apparatus for enforcing valid confidence levels.5G mobile communication technologies define broad frequency bands such that high transmission rates and new services are possible, and can be implemented not only in "Sub 6GHz" bands such as 3.5GHz, but also in "Above 6GHz" bands referred to as mmWave including 28GHz and 39GHz. In addition, it has been considered to implement 6G mobile communication technologies (referred to as Beyond 5G systems) in terahertz bands (for example, 95GHz to 3THz bands) in order to accomplish transmission rates fifty times faster than 5G mobile communication technologies and ultra-low latencies one-tenth of 5G mobile communication technologies.At the beginning of the development of 5G mobile communication technologies, in order to support services and to satisfy performance requirements in connection with enhanced Mobile BroadBand (eMBB), Ultra Reliable Low Latency Communications (URLLC), and massive Machine-Type Communications (mMTC), there has been ongoing standardization regarding beamforming and massive MIMO for mitigating radio-wave path loss and increasing radio-wave transmission distances in mmWave, supporting numerologies (for example, operating multiple subcarrier spacings) for efficiently utilizing mmWave resources and dynamic operation of slot formats, initial access technologies for supporting multi-beam transmission and broadbands, definition and operation of BWP (BandWidth Part), new channel coding methods such as a LDPC (Low Density Parity Check) code for large amount of data transmission and a polar code for highly reliable transmission of control information, L2 pre-processing, and network slicing for providing a dedicated network specialized to a specific service.Currently, there are ongoing discussions regarding improvement and performance enhancement of initial 5G mobile communication technologies in view of services to be supported by 5G mobile communication technologies, and there has been physical layer standardization regarding technologies such as V2X (Vehicle-to-everything) for aiding driving determination by autonomous vehicles based on information regarding positions and states of vehicles transmitted by the vehicles and for enhancing user convenience, NR-U (New Radio Unlicensed) aimed at system operations conforming to various regulation-related requirements in unlicensed bands, NR UE Power Saving, Non-Terrestrial Network (NTN) which is UE-satellite direct communication for providing coverage in an area in which communication with terrestrial networks is unavailable, and positioning.Moreover, there has been ongoing standardization in air interface architecture / protocol regarding technologies such as Industrial Internet of Things (IIoT) for supporting new services through interworking and convergence with other industries, IAB (Integrated Access and Backhaul) for providing a node for network service area expansion by supporting a wireless backhaul link and an access link in an integrated manner, mobility enhancement including conditional handover and DAPS (Dual Active Protocol Stack) handover, and two-step random access for simplifying random access procedures (2-step RACH for NR). There also has been ongoing standardization in system architecture / service regarding a 5G baseline architecture (for example, service based architecture or service based interface) for combining Network Functions Virtualization (NFV) and Software-Defined Networking (SDN) technologies, and Mobile Edge Computing (MEC) for receiving services based on UE positions.As 5G mobile communication systems are commercialized, connected devices that have been exponentially increasing will be connected to communication networks, and it is accordingly expected that enhanced functions and performances of 5G mobile communication systems and integrated operations of connected devices will be necessary. To this end, new research is scheduled in connection with eXtended Reality (XR) for efficiently supporting AR (Augmented Reality), VR (Virtual Reality), MR (Mixed Reality) and the like, 5G performance improvement and complexity reduction by utilizing Artificial Intelligence (AI) and Machine Learning (ML), AI service support, metaverse service support, and drone communication.Furthermore, such development of 5G mobile communication systems will serve as a basis for developing not only new waveforms for providing coverage in terahertz bands of 6G mobile communication technologies, multi-antenna transmission technologies such as Full Dimensional MIMO (FD-MIMO), array antennas and large-scale antennas, metamaterial-based lenses and antennas for improving coverage of terahertz band signals, high-dimensional space multiplexing technology using OAM (Orbital Angular Momentum), and RIS (Reconfigurable Intelligent Surface), but also full-duplex technology for increasing frequency efficiency of 6G mobile communication technologies and improving system networks, AI-based communication technology for implementing system optimization by utilizing satellites and AI (Artificial Intelligence) from the design stage and internalizing end-to-end AI support functions, and next-generation distributed computing technology for implementing services at levels of complexity exceeding the limit of UE operation capability by utilizing ultra-high-performance communication and computing resources.According to an embodiment of the disclosure, a method performed by a first entity may include receiving, from a second entity, a message associated with at least one expected user equipment behaviour parameter.According to an embodiment of the disclosure, the method may include identifying whether at least one of confidence level or accuracy level of the at least one expected UE behaviour parameter is out of range.According to an embodiment of the disclosure, the method may include transmitting, to the second entity, an error message based on the identification.According to an embodiment of the disclosure, a first entity may include a transceiver; and a processor coupled with the transceiver.According to an embodiment of the disclosure, wherein the processor is configured to receive, from a second entity, a message associated with at least one expected user equipment (UE) behaviour parameter.According to an embodiment of the disclosure, wherein the processor is configured to identify whether at least one of confidence level or accuracy level of the at least one expected UE behaviour parameter is out of range.According to an embodiment of the disclosure, wherein the processor is configured to transmit, to the second entity, an error message based on the identification.According to an embodiment of the disclosure, a method performed by a second entity may include transmitting, to a first entity, a message associated with at least one expected user equipment (UE) behaviour parameter.According to an embodiment of the disclosure, the method may include receiving, from the first entity, an error message based on the identification, at the first entity, that at least one of a confidence level or an accuracy level is out of range.According to an embodiment of the disclosure, a second entity may include a transceiver; and a processor coupled with the transceiver.According to an embodiment of the disclosure, wherein the processor is configured to transmit, to a first entity, a message associated with at least one expected user equipment (UE) behaviour parameter.According to an embodiment of the disclosure, wherein the processor is configured to receive, from the first entity, an error message based on the identification, at the first entity, that at least one of a confidence level or an accuracy level is out of range.Figure 1 is a flow chart illustrating a method of providing confidence level along with expected User Equipment behaviour parameters.Figure 2 illustrates NF service consumer updates subscription data.Figure 3 illustrates a method of enforcing valid confidence levels according to an embodiment of the disclosure.Figure 4 illustrates various hardware components of the first entity, according to the embodiments as disclosed herein.Figure 5 illustrates various hardware components of the second entity, according to the embodiments as disclosed herein.The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. Also, the various embodiments described herein are not necessarily mutually exclusive, as some embodiments can be combined with one or more other embodiments to form new embodiments. The term "or" as used herein, refers to a non-exclusive or, unless otherwise indicated. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein can be practiced and to further enable those skilled in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.The following description of examples of the present disclosure, with reference to the accompanying drawings, is provided to assist in a comprehensive understanding of the present invention, as defined by the claims. The description includes various specific details to assist in that understanding but these are to be regarded as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the examples described herein can be made.Reference throughout this specification to "an aspect", "another aspect" or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the disclosure. Thus, appearances of the phrase "in an embodiment", "in another embodiment", and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.The same or similar components may be designated by the same or similar reference numerals, although they may be illustrated in different drawings.Detailed descriptions of techniques, structures, constructions, functions or processes known in the art may be omitted for clarity and conciseness, and to avoid obscuring the subject matter of the present disclosure.The terms and words used herein are not limited to the bibliographical or standard meanings, but, are merely used to enable a clear and consistent understanding of the examples disclosed herein.Throughout the description and claims, the words "comprise", "contain" and "include", and variations thereof, for example "comprising", "containing" and "including", means "including but not limited to", and is not intended to (and does not) exclude other features, elements, components, integers, steps, processes, functions, characteristics, and the like.Throughout the description and claims, the singular form, for example "a", "an" and "the", encompasses the plural unless the context otherwise requires. For example, reference to "an object" includes reference to one or more of such objects.Before undertaking the detailed description below, it may be advantageous to set forth definitions of certain words and phrases used throughout the present disclosure. The term "couple" and the derivatives thereof refer to any direct or indirect communication between two or more elements, whether or not those elements are in physical contact with each other. The terms "transmit", "receive", and "communicate" as well as the derivatives thereof encompass both direct and indirect communication. The terms "include" and "comprise", and the derivatives thereof refer to inclusion without limitation. The term "or" is an inclusive term meaning "and / or". The phrase "associated with," as well as derivatives thereof, refer to include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, have a relationship to or with, or the like. The term "controller" refers to any device, system, or part thereof that controls at least one operation. Such a controller may be implemented in hardware or a combination of hardware and software and / or firmware. The functionality associated with any particular controller may be centralized or distributed, whether locally or remotely. The phrase "at least one of," when used with a list of items, means that different combinations of one or more of the listed items may be used, and only one item in the list may be needed. For example, "at least one of A, B, and C" includes any of the following combinations: A, B, C, A and B, A and C, B and C, and A and B and C, and any variations thereof. Similarly, the term "set" means one or more. Accordingly, the set of items may be a single item or a collection of two or more items.It should be appreciated that the blocks in each flowchart and combinations of the flowcharts may be performed by one or more computer programs which include computer-executable instructions. The entirety of the one or more computer programs may be stored in a single memory or the one or more computer programs may be divided with different portions stored in different multiple memories.Any of the functions or operations described herein can be processed by one processor or a combination of processors. The one processor or the combination of processors is circuitry performing processing and includes circuitry like an application processor (AP), a communication processor (CP), a graphical processing unit (GPU), a neural processing unit (NPU), a microprocessor unit (MPU), a system on chip (SoC), an IC, or the like.As is traditional in the field, embodiments may be described and illustrated in terms of blocks which carry out a described function or functions.　These blocks, which may be referred to herein as managers, units, modules, hardware components or the like, are physically implemented by analog and / or digital circuits such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hardwired circuits and the like, and may optionally be driven by firmware and software. The circuits may, for example, be embodied in one or more semiconductor chips, or on substrate supports such as printed circuit boards and the like.　The circuits constituting a block may be implemented by dedicated hardware, or by a processor (e.g., one or more programmed microprocessors and associated circuitry), or by a combination of dedicated hardware to perform some functions of the block and a processor to perform other functions of the block.　Each block of the embodiments may be physically separated into two or more interacting and discrete blocks without departing from the scope of the disclosure.　Likewise, the blocks of the embodiments may be physically combined into more complex blocks without departing from the scope of the disclosure.The accompanying drawings are used to help easily understand various technical features and it should be understood that the embodiments presented herein are not limited by the accompanying drawings. As such, the present disclosure should be construed to extend to any alterations, equivalents and substitutes in addition to those which are particularly set out in the accompanying drawings. Although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are generally only used to distinguish one element from another.Throughout the description and claims, language in the general form of "X for Y" (where Y is some action, process, function, activity or step and X is some means for carrying out that action, process, function, activity or step) encompasses means X adapted, configured or arranged specifically, but not necessarily exclusively, to do Y.Features, elements, components, integers, steps, processes, functions, characteristics, and the like, described in conjunction with a particular aspect, embodiment, example or claim are to be understood to be applicable to any other aspect, embodiment, example or claim disclosed herein unless incompatible therewith.The following examples are applicable to, and use terminology associated with, 3GPP 5G. However, the skilled person will appreciate that the techniques disclosed herein are not limited to these examples or to 3GPP 5G, and may be applied in any suitable system or standard, for example one or more existing and / or future generation wireless communication systems or standards. The skilled person will appreciate that the techniques disclosed herein may be applied in any existing or future releases of 3GPP 5G NR or any other relevant standard.For example, the functionality of the various network entities and other features disclosed herein may be applied to corresponding or equivalent entities or features in other communication systems or standards. Corresponding or equivalent entities or features may be regarded as entities or features that perform the same or similar role, function, operation or purpose within the network. For example, the functionality of a node in the examples below may be applied to any other suitable type of entity performing functions of a network node.The skilled person will appreciate that the present invention is not limited to the specific examples disclosed herein. For example:- The techniques disclosed herein are not limited to 3GPP 5G.- One or more entities in the examples disclosed herein may be replaced with one or more alternative entities performing equivalent or corresponding functions, processes or operations.- One or more of the messages in the examples disclosed herein may be replaced with one or more alternative messages, signals or other type of information carriers that communicate equivalent or corresponding information.- One or more further elements, entities and / or messages may be added to the examples disclosed herein.- One or more non-essential elements, entities and / or messages may be omitted in certain examples.- The functions, processes or operations of a particular entity in one example may be divided between two or more separate entities in an alternative example.- The functions, processes or operations of two or more separate entities in one example may be performed by a single entity in an alternative example.- Information carried by a particular message in one example may be carried by two or more separate messages in an alternative example.- Information carried by two or more separate messages in one example may be carried by a single message in an alternative example.- The order in which operations are performed may be modified, if possible, in alternative examples.- The transmission of information between network entities is not limited to the specific form, type and / or order of messages described in relation to the examples disclosed herein.According to an embodiment of the disclosure, 3GPP means 3rd Generation Partnership Project.According to an embodiment of the disclosure, 5G means 5th Generation.According to an embodiment of the disclosure, 5GC means 5G Core.According to an embodiment of the disclosure, AF means Application Function.According to an embodiment of the disclosure, AMF means Access and Mobility Management Function.According to an embodiment of the disclosure, AI means Artificial Intelligence.According to an embodiment of the disclosure, DL means Downlink.According to an embodiment of the disclosure, gNB means base station.According to an embodiment of the disclosure, HSS means Home Subscriber Server.According to an embodiment of the disclosure, ID means Identity and / or Identification.According to an embodiment of the disclosure, ML means Machine Learning.According to an embodiment of the disclosure, NEF means Network Element Function.According to an embodiment of the disclosure, NF means Network Function.According to an embodiment of the disclosure, NR means New Radio.According to an embodiment of the disclosure, QoS means Quality of Service.According to an embodiment of the disclosure, RAN means Radio Access Network.According to an embodiment of the disclosure, SCEF means Service Capability Exposure Function.According to an embodiment of the disclosure, SMF means Session Management Function.According to an embodiment of the disclosure, TS means Technical Specification.According to an embodiment of the disclosure, UDM means Unified Data Management.According to an embodiment of the disclosure, UDR means User Data Repository.According to an embodiment of the disclosure, UE means User Equipment.According to an embodiment of the disclosure, UL means Uplink.According to an embodiment of the disclosure, UPF means User Plane Function.According to an embodiment of the disclosure, Uu means Air interface between terminal and base station / access point.Artificial Intelligence (AI) / Machine Learning (ML) is being used in a range of application domains across industry sectors. In mobile communications systems, mobile devices (e.g. smartphones, automotive, robots) are increasingly replacing conventional algorithms (e.g. speech recognition, image recognition, video processing) with AI / ML models to enable applications. The 5G system can at least support three types of AI / ML operations, TS 22.261 [1]:- AI / ML operation splitting between AI / ML endpoints- AI / ML model / data distribution and sharing over 5G system- Distributed / Federated Learning over 5G systemAs outlined in clause 4.15.6 of TS 23.502 [2], provisioning capability allows an external party to provision the information, such as expected UE behaviour and service specific parameters to 5G network functions. For example, the expected UE behavioural information consists of information on expected UE movement and communication characteristics. Provisioned data can be used by the other NFs. The Expected UE Behaviour parameters characterise the foreseen behaviour of a UE or a group of UEs.As part of AIML work, 3GPP SA2 has introduced confidence levels that are provided with the Expected UE Behavior parameters. The following is from section 4.15.6.2 in [1] and refers to Figure 1, also from [1]:Figure 1 is a flow chart illustrating a method of providing confidence level along with expected User Equipment behaviour parameters.In step 0, NF subscribes to UDM notifications of UE and / or Group Subscription data updates. In the UDM subscription, the NF may request to be notified about expected UE behaviour parameter(s) in Table 4.15.6.3-1 or Application-Specific Expected UE Behaviour parameter(s) in Table 4.15.6.3f-1 that may have been externally provisioned by an AF.NOTE　1: The NF can subscribe to Group Subscription data from UDM in this step　and be notified of Group Subscription data updates in step　7 using the Shared Data feature defined in TS　29.503

[0052] .NOTE　2: The external parameters in Table 4.15.6.3-1 may be provisioned by an AF hosting an AI / ML based application.If an expected UE behaviour parameter subscription is provided by the NF, the subscription may include a threshold indicating that certain confidence and / or accuracy levels must be met for the parameter(s) to be notified by UDM to the NF. Meeting the threshold condition may mean that the confidence / accuracy level of a parameter is equal to a certain threshold, or less than a certain threshold, or greater than a certain threshold, or less than or equal to a certain threshold, or greater than or equal to a certain threshold. The threshold may be in the form of a range (e.g. minimum value to maximum value, where each may be inclusive or exclusive) or a specific value.NOTE　3: The threshold may be used to e.g. prevent certain Expected UE Behaviour parameters from being notified without certain minimum level of confidence / accuracy.NOTE　4: Confidence level indicates a probability assertion for the associated Expected UE Behaviour parameter and accuracy level indicates the performance of the estimator (e.g. AI / ML model) used for the prediction.In step 0b, [Conditional, on using NWDAF-assisted values] the AF may subscribe to NWDAF via NEF in order to learn the UE mobility analytics and / or UE Communication analytics for a UE or group of UEs by applying the procedure specified in clause　6.1.1.2 of TS　23.288

[0050] . The Analytics ID is set to any of the values specified in clause　6.7.1 of TS　23.288

[0050] .In step 0c, [Conditional, on using NWDAF-assisted values] AF validates the received data and derives any of the Expected UE behaviour parameters defined in clause　4.15.6.3 for a UE or group of UEs.In step 1, the AF provides one or more parameter(s) to be created or updated, or deleted in a Nnef_ParameterProvision_Create or Nnef_ParameterProvision_Update or Nnef_ParameterProvision_Delete Request to the NEF. The parameters(s) may include corresponding confidence and / or accuracy levels.The AF provides target UE identifier (e.g. GPSI or External Group ID) as described in clause　5.2.6.4. The Transaction Reference ID identifies the transaction request between NEF and AF. For the case of Nnef_ParameterProvision_Create, The NEF assigns a Transaction Reference ID to the Nnef_ParameterProvision_Create request.NEF checks whether the requestor is allowed to perform the requested service operation by checking requestor's identifier (i.e. AF Identifier).NOTE　5: When multiple AF parameter provisioning requests with different values of the same Expected UE Behavior parameters are recieved from different AFs, the network behaviour is unspecified.For a Create request associated with a 5G VN group, the External Group ID identifies the 5G VN Group.The payload of the Nnef_ParameterProvision_Update Request includes one or more of the following parameters:- Expected UE Behaviour parameters (see clause　4.15.6.3); or- Network Configuration parameters (see clause　4.15.6.3a); or- 5G VN group data (i.e. 5G VN configuration parameters) (see clause　4.15.6.3b), or- 5G VN group membership management parameters (see clause　4.15.6.3c); or- Location Privacy Indication parameters of the "LCS privacy" Data Subset of the Subscription Data (see clause　5.2.3.3.1 and clause　7.1 of TS　23.273

[0051] ); or- MTC Provider Information; or- AF provided ECS Address Configuration Information (see clause　4.15.6.3d); or- DNN and S-NSSAI specific Group Parameters (see clause　4.15.6.3e); or- Application-Specific Expected UE Behaviour parameters (see clause　4.15.6.3f).The AF may request to delete 5G VN configuration by sending Nnef_ParameterProvision_Delete to the NEF.In step 2, if the AF is authorised by the NEF to provision the parameters, the NEF requests to create, update and store, or delete the provisioned parameters as part of the subscriber data via Nudm_ParameterProvision_Create, Nudm_ParameterProvision_Update or Nudm_ParameterProvision_Delete Request message, the message includes the provisioned data and NEF reference ID and optionally MTC Provider Information.If the AF is not authorised to provision the parameters, then the NEF continues in step　6 indicating the reason to failure in Nnef_ParameterProvision_Create / Update / Delete Response message. Step　7 does not apply in this case.If the NEF did not receive DNN and / or S-NSSAI from the AF and such information is configured as needed within 5GC, the NEF determines the DNN and / or S-NSSAI from the AF Identifier.If the AF provides the DNN and S-NSSAI specific Group Parameters, the AF shall indicate the External Group ID, targeted DNN and S-NSSAI in the request.If the AF provides the service area in the form of geographical information, the NEF maps the geographical information to the list of TAs.NOTE　6: For non-roaming case and no authorisation or validation by the UDM required and if the request is not associated with a 5G VN group, the NEF can directly forward the external parameter to the UDR via Nudr_DM_Update Request message. And in this case, the UDR responds to NEF via Nudr_DM_Update Response message.In step 3, UDM may read from UDR, by means of Nudr_DM_Query, corresponding subscription information in order to validate required data updates and authorize these changes for this subscriber or Group for the corresponding AF.Based on local configuration, UDM may determine if there is any requirement in terms of threshold conditions that need to be met by the provisioned parameter before storing the parameter in UDR. If satisfied, UDM may proceed seamlessly. If not satisfied, step　5 is triggered as a failed procedure and a related cause value is provided, e.g. "confidence level not sufficient". In that case step　4 is skipped.In step 4, If the AF is authorised by the UDM to provision the parameters for this subscriber, the UDM resolves the GPSI to SUPI and requests to create, update or delete the provisioned parameters as part of the subscriber data via Nudr_DM_Create / Update / Delete Request message, the message includes the provisioned data.If a new 5G VN group is created, the UDM shall assign a unique Internal Group ID for the 5G VN group and include the newly assigned Internal Group ID in the Nudr_DM_Create Request message. If the list of 5G VN group members is changed or if 5G VN group data has changed, the UDM updates the UE and / or Group subscription data according to the AF / NEF request.When the service area is configured or updated for a group, the UDM authorises the request.If the Default QoS is configured or updated for a group, the UDM authorises the request and uses such Default QoS to set 5GS Subscribed QoS profile in Session Management Subscription data for each UE within the group. The 5GS Subscribed QoS profile in Session Management Subscription data will be considered by SMF as described in clause　5.7.2.7 of TS　23.501.UDR stores the provisioned data as part of the UE and / or Group subscription data and responds with Nudr_DM_Create / Update / Delete Response message.If the Maximum Group Data Rate is configured or updated for a 5G VN group, the UDM authorises the request and the Maximum Group Data Rate is applied as described in clause　5.29.2 of TS　23.501.When the 5G VN group data (as described in clause　4.15.6.3b) or 5G VN group membership is updated, the UDR notifies to the subscribed PCF by sending Nudr_DM_Notify as defined in clause　4.16.12.2.If the AF is not authorised to provision the parameters, then the UDM continues in step　5 indicating the reason to failure in Nudm_ParameterProvision_Update Response message and step　7 is not executed.The UDM classifies the received parameters (i.e. Expected UE Behaviour parameters or Suggested Number of Downlink Packets or the 5G VN configuration parameters or DNN and S-NSSAI specific Group Parameters or Location Privacy Indication parameters or ECS Address Configuration Information), into AMF associated and SMF associated parameters. The UDM may use the AF Identifier received from the NEF in step　2 to relate the received parameter with a particular subscribed DNN and / or S-NSSAI. The UDM stores the SMF-Associated parameters under corresponding Session Management Subscription data type.Each parameter or parameter set may be associated with a validity time. The validity time is stored at the UDM / UDR and in each of the NFs, to which parameters are provisioned (e.g. in AMF or SMF). Upon expiration of the validity time, each node deletes the parameters autonomously without explicit signalling.If the ECS Address Configuration Information is provided to any UE in AF request, the UDM shall make use of the shared data mechanism defined in TS　29.503

[0052] and notify all NFs (SMFs) that have subscribed to receiving such shared data change notifications.In step 5, UDM responds the request with Nudm_ParameterProvision_Create / Update / Delete Response. If the procedure failed, the cause value indicates the reason.In step 6, NEF responds the request with Nnef_ParameterProvision_Create / Update / Delete Response. If the procedure failed, the cause value indicates the reason.In step 7, [Conditional this step occurs only after successful step　4] UDM notifies the subscribed Network Function (e.g. AMF) of the updated UE and / or Group subscription data via Nudm_SDM_Notification Notify message.a) If the NF is AMF, the UDM performs Nudm_SDM_Notification (SUPI or Internal Group Identifier, AMF-Associated Expected UE Behaviour parameters, Subscribed Periodic Registration Timer, subscribed Active Time, 5G VN group data or DNN and S-NSSAI specific Group Parameters, etc.) service operation. If the AMF receives confidence and / or accuracy levels along the Expected UE behaviour parameter(s), the AMF may use the associated confidence level and / or accuracy level when handling the expected UE behaviour parameter(s). The AMF uses the received parameters to derive the appropriate UE configuration of the NAS parameters and to derive Core Network assisted RAN parameters. The AMF may determine a Registration area based on parameters Stationary indication or Expected UE Moving Trajectory.If the AMF obtains service area for a group the AMF configures the DNN for the group as LADN DNN and applies the LADN per DNN and S-NSSAI taking into account the service area for the group as described in clause　5.20b.2 of TS　23.501　[2].b) If the NF is SMF, the UDM performs Nudm_SDM_Notification (SUPI or Internal Group Identifier, SMF-Associated Expected UE Behaviour parameter set, DNN / S-NSSAI, Suggested Number of Downlink Packets, 5G VN group data, etc.) service operation.The SMF stores the received parameters and associates them with a PDU Session based on the DNN and S-NSSAI included in the message from UDM.If the SMF receives confidence and / or accuracy levels along the Expected UE behaviour parameter(s), the SMF may use the associated confidence level and / or accuracy level when handling the expected UE behaviour parameter(s). The SMF may use the parameters as follows:SMF configures the UPF accordingly. The SMF can use the Scheduled Communication Type parameter or Suggested Number of Downlink Packets parameter to configure the UPF with how many downlink packets to buffer. The SMF may use Communication duration time parameter and / or Expected Inactivity Time parameter and / or Battery Indication parameter combined with their confidence / accuracy levels to set the inactivity timer for a PDU Session. The SMF then waits for a UP inactivity report to be received from UPF. Based on the received UP inactivity report, the SMF may determine to deactivate the corresponding UP connection associated to the PDU Session of a single UE or determine a collective pattern of deactivating UP connections for multiple UEs (e.g. for a group of UEs receiving application AI / ML traffic during FL operation) and perform CN-initiated selective deactivation of UP connection of an existing PDU Session.The SMF may derive SMF derived CN assisted RAN information for the PDU Session. The SMF provides the SMF derived CN assisted RAN information to the AMF as described in PDU Session establishment procedure or PDU Session modification procedure.NOTE　7: The NEF (in NOTE 1) or the UDM (in step　3) can also update the corresponding UDR data via Nudr_DM_Create / Delete as appropriate.NOTE　8: The change of AF provided ECS configuration information is not meant to apply immediately: the UDM interface to the SMF can refer to Shared Data for the Subscription provided ECS configuration information.NOTE　9: Specification details of confidence and accuracy levels are left to Stage　3 work.As can be seen, the AF can provide confidence level and / or accuracy level which is associated with specific parameters.The following is from section 4.15.6.3 of [2]:These Expected UE Behaviour parameters characterise the foreseen behaviour of a UE or a group of UEs. Sets of these parameters may be provided via the NEF to be stored as part of the subscriber data. Each parameter within the Expected UE Behaviour shall have an associated validity time. The validity time indicates when the Expected UE Behaviour parameter expires and shall be deleted by the related NFs. The validity time may be set to indicate that the particular Expected UE Behaviour parameter has no expiration time. When the validity time expires, the related NFs delete their local copy of the associated Expected UE Behaviour parameter(s).In addition, each parameter within the Expected UE Behaviour may have a confidence and / or accuracy level associated with it. The confidence level indicates a probability assertion for the associated Expected UE Behaviour parameter and the accuracy level indicates the performance of the estimator (e.g. AI / ML model) used for the prediction. The provision procedure of the Expected UE Behaviour is realized by external parameter provision procedure defined in clause　4.15.6.2.The Expected UE Behaviour parameters stored as AMF-Associated Expected UE Behaviour parameters which is per UE level and SMF-Associated Expected UE Behaviour parameters which is per PDU session level in UDM. AMF retrieves the AMF-Associated Expected UE Behaviour parameters from UDM which may related to both PDU session(s) and SMS transmission. SMF retrieves the SMF-Associated Expected UE Behaviour parameters from UDM for the specific PDU session. AMF and SMF uses the Expected UE Behaviour parameters as described in clause　5.4.6.2 of TS　23.501.The Expected UE Moving Trajectory and the Expected Time and Day of Week in Trajectory may be used by the AMF. All other parameters may be used by the AMF and by the SMF.The Scheduled Communication Type and the Traffic Profile should not be used by the AMF to release the UE when NAS Release Assistance Information from the UE is available.In the case of NB-IoT UEs, the parameters may be forwarded to the RAN to allow optimisation of Uu resource allocation for NB-IoT UE differentiation.From the above, the "confidence level indicates a probability assertion for the associated Expected UE Behaviour parameter and the accuracy level indicates the performance of the estimator (e.g. AI / ML model) used for the prediction".Section 5.6.2.2.2 of TS 29.503 [3] describes and explains overall interaction between the NF service consumer and the UDM, referring to Figure 2 (also from [3]):Figure 2 illustrates NF service consumer updates subscription data.Figure 2 shows a scenario where the NF service consumer (e.g. NEF, AMF) sends a request to the UDM to update a UE's subscription data (see 3GPP TS 23.502 [3] figure 4.15.6.2-1 step 2 and also 3GPP TS 23.273

[0038] Figure 6.12.1-1 step 2). The request contains the identifier of the UE's parameter provision data ( ... / {ueId} / pp-data) and the modification instructions. The values ueId shall take are specified in Table 6.5.3.2.2-1.In step 1, the NF service consumer (e.g. NEF, AMF) sends a PATCH request to the resource that represents a UE's modifiable subscription data.If MTC Provider information and / or AF ID are received in the request, the UDM shall check whether the MTC Provider and / or the AF is allowed to perform this operation for the UE; otherwise, the UDM shall skip the MTC provider and / or AF authorization check.In step 2a, the UDM responds with "204 No Content".In step 2b, upon partial success, UDM responds with "200 OK".If the request includes the "Expected UE Behaviour Data" parameters, then, based on local configuration, the UDM may determine if there are any requirements in the UDM with respect to threshold conditions that need to be met by the received parameter before the UDM stores the parameter in, e.g. the UDR. If the threshold criteria is satisfied, the UDM may continue to process the request. If the threshold criteria is not satisfied, UDM may return partial success with a related cause value e.g. "confidence level not sufficient" or "accuracy level not sufficient".In step 2c, if MTC Provider or AF are not allowed to perform this operation for the UE, HTTP status code "403 Forbidden" shall be returned including additional error information in the response body (in the "ProblemDetails" element).NOTE: Upon reception of an update or removal of maximum latency, maximum response time or DL Buffering Suggested Packet Count, UDM may need to adjust the value of active time and / or periodic registration timer and / or DL Buffering Suggested Packet Count and the UDM shall notify AMF and / or SMF if the values are updated (see clause　4.15.6.3a of 3GPP　TS　23.502).On failure, the appropriate HTTP status code indicating the error shall be returned and appropriate additional error information should be returned in the PATCH response body.To summarize, the AF may provide a confidence and / or accuracy level to the network which then may enforce a policy or rule (e.g. based on local configuration or subscription information) to ensure that the level is as required.The above information is presented as background information only to assist with an understanding of the present disclosure. No determination has been made, and no assertion is made, as to whether any of the above might be applicable as prior art with regard to the present invention.It is an aim of certain examples of the present disclosure to address, solve and / or mitigate, at least partly, at least one of the problems and / or disadvantages associated with the related art, for example at least one of the problems and / or disadvantages described herein.It is an aim of certain examples of the present disclosure to provide at least one advantage over the related art, for example at least one of the advantages described herein.The present invention is defined in the independent claims. Advantageous features are defined in the dependent claims.Embodiments or examples disclosed in the description and / or figures falling outside the scope of the claims are to be understood as examples useful for understanding the present invention.Other aspects, advantages, and salient features of the invention will become apparent to those skilled in the art from the following detailed description taken in conjunction with the accompanying drawings.Disclosed herein are solutions to address unexpected or abnormal cases in which the confidence level and / or accuracy level that is provided by an entity is such that the value is not even a possible value. Note that this is to be differentiated from the case that the value provided does not meet the desired threshold as these are unrelated problems.For example, a confidence level may be required to exceed a threshold T and the entity providing the level may provide a value less than T and so this does not meet the minimum value of T. The request may be rejected. Noting that T is a value between 0 and 1 in the case of a probability, or between 0% and 100%.This is not the same as a problem in which the provided level is not valid, e.g. it is negative or more than 100%. The solutions provided herein aim to address the case in which the provided confidence and / or accuracy level is not valid.The entity that provides the confidence level and / or accuracy may be referred to as the "entity providing a metric" or the "entity which provides a metric". This entity may be any of the following: an Application Function (AF), NEF, UDM, or any other core network node or any other external entity. As such the proposals would apply for any node that acts as an entity providing a reliability metric. Although this document would use the example of an AF as the entity providing a confidence level, the proposals herein are not restricted to this node and metric only and as such can apply to any other node and any other reliability metric.The entity which receives a confidence level and / or accuracy is referred to an the "entity receiving a metric" or "the entity which receives a metric". This entity may be any of the following: an NEF, UDM, AMF, SMF, or any other core network node or any other external entity. As such the proposals would apply for any node that acts as an entity providing a reliability metric. Although this document may use the example of an NEF as the entity receiving a confidence level, the proposals herein are not restricted to this node and metric only and as such can apply to any other node and any other reliability metric.Furthermore, the proposals herein will use the example of a confidence level as a way to describe the proposals. However the same proposals would apply to any other metric that may be considered such as an accuracy level, error level, etc. That is, the terms 'metric' or 'reliability metric' as used herein are intended to include a confidence level, an accuracy level, an error level and any other similar metric indicating reliability of data. Furthermore, the metric (e.g. confidence level) may refer to one value or may refer to a range and as such is not limited to one particular value or number only. The proposals would apply regardless of whether the parameter or metric in question reflects a single value or a range.Any entity may take the role of the entity providing a metric or confidence level, and any entity may take the role of the entity receiving a metric or confidence level as described herein. As such the examples used in this document are not to be considered as limitations or restrictions of the proposals but rather descriptions of how the solutions can be used to address the problems.The entity which receives a metric (e.g. confidence level) may verify if the received metric is of a valid type. For example, if the expected metric is a number, or of a numeric type, then the receiving entity may ensure that the metric type is a valid type which matches expected data type e.g. a numeric or a number. For example, a string or character metric would be considered invalid if the metric is expected to be a number or a numeric type. And vice versa, if the expected metric is a string or a character and the received metric is a number, then the metric would be considered as invalid.The entity which receives a metric (e.g. confidence level) may verify if the received metric is from a valid domain where the domain defines, for example, the set of valid values that the metric can take. Note that this would apply to any data type e.g. a string, character, number, etc. For example, if a metric is expected to be a character such that the valid value would be one of the following set {'A', 'B', 'C', 'D'}, then the entity which receives a confidence level (or any metric) may verify and / or ensure that the metric is from the allowed set of values. If this is not the case, the entity which receives the metric or confidence level may consider the confidence level (or metric) to be invalid.The entity which receives the metric (e.g. confidence level) may verify at least one condition such as, but not limited to, the examples or conditions described above. If the entity which receives the metric (e.g. confidence level) determines that the metric is not valid, then the entity may send a message to the source node (e.g. the entity which provided the metric) indicating an error or that the metric is invalid. The entity which reports this error should provide an appropriate cause value to reflect the nature of the problem. For example, a new cause value "Invalid confidence level" may be reported, or "Invalid data type for confidence level" may be reported. The transmitted message may indicate that the received metric is rejected, that the received message including the received message is rejected, and / or that a request included in the received message is rejected. For example, the entity may receive a request message including a metric and may determine if the metric is valid. If the entity determines that the metric is not valid, it may reject the request and may transmit a response message to the entity which provided the metric, wherein the response message may indicate that the request is rejected and may also indicate that the reason for the rejection is that the metric is not valid.Upon detection of an invalid metric, for example as described above, the entity which makes this determination may log the error locally or report it to another entity that may be responsible for monitoring and / or saving such operational errors. The saved information, or error log, may contain other information such as, but not limited to: the entity which sent the confidence level, the time stamp of the error detection, the type of error detected, the address of the sending entity, etc.In an embodiment, when an Application Function provisions the application specific expected UE behaviour parameters along with accuracy and confidence level, using the NEF / SCEF's Communication pattern parameter provisioning service (CpProvisioning API) as specified in 3GPP TS 29.522 and TS 29.122, then the NEF / SCEF shall include the "CONFIDENCE_LEVEL_OUT_OF_RANGE" and / or "ACCURACY_LEVEL_OUT_OF_RANGE" values as application errors in the response message to application function if the confidence and / or accuracy values are not valid respectively (e.g. based on the proposals above). The examples of some application errors are proposed and shown in Table 1 below.Table 2 shows an example error from UDM wherein, when an AF / NEF sends a list of Expected UE Behavior parameters to be provisioned into UE's subscription data. If / when the UDM determines that the associated confidence / accuracy levels are out-of-range, it responds with 403 Forbidden with application-error set as proposed and as shown below:In the example described above, the entity which receives a metricverifies if the received metric is valid (e.g. is of a valid type or has a valid value). In an example, if this is not the case, i.e. if the received metric is not valid, the entity may use a default value instead of rejecting the request from the entity which sent the metric.The entity which receives a metric may be configured to operate based on a default value for a certain metric based on local policies or based on operations and management methods. The entity may be configured with the default value to use when an invalid metric is received. The default value for a metric (e.g. confidence level) may be, as an example 70%. Or in the case of a range, the default range may be 65% to 75%, etc. Or in case a certain ordinal level that may be needed, e.g. low, medium, high, etc, the default level may be low, etc.Alternatively, the entity may use a value for the metric using any of the methods described below:- The entity may use a value based on the past values that were optionally received (and / or used, where optionally the previous values are value that were deemed valid)- For example, the entity may use the average of the previous values- For example, the entity may use the mode of the previous values- For example, the entity may derive a value based on previous values using any other method e.g. weighted average, etc- Any other method may also be defined and used and as such the above is not a restriction but examples of behaviour that can be applied to address the problemAlternatively, if the value received is negative e.g. less than zero, then the entity may round the value to be 0% (zero percent) and hence may use zero. If the value received is more than 100%, then the entity may round the value to be 100% and may hence use 100% as the value.The entity which receives a metric that is deemed to be invalid may use a default value for the metric in question, where the default value may be numeric or ordinal or categorical, or a range, etc, and may then inform the source entity (e.g. from which the metric was received) that a default level has been used and may also indicate the default level which is used. Alternatively, if other methods have been used to determine the value, for example as have been described above (e.g. based on previous used values or based on previous averages or based on the average, etc), then the entity which receives a metric may inform the source entity about the method used to derive the value of the parameter in question and optionally the value which has been derived).The entity which receives a metric that is invalid may also behave as described above in terms of logging the event. The entity may further save or report the default value used.In an embodiment, when an Application Function provisions the application specific expected UE behaviour parameters along with accuracy and confidence level, using the NEF / SCEF's Communication pattern parameter provisioning service (CpProvisioning API) as specified in 3GPP TS 29.522 and TS 29.122, then the NEF / SCEF shall determine the confidence and accuracy values based on the response from UDM (Nudm_ParameterProvision) and HSS. The UDM / HSS or NEF, or any other core network node may behave as described above.Figure 3 illustrates a method of enforcing valid confidence levels according to an embodiment of the disclosure.Figure 3 is an illustrated example which aims to describe how the proposals herein may be used, noting that the figure is not to be considered as a limitation or a restriction but rather as a possible combination of the proposals herein. Note that all the proposals herein may be used in any order or combination.In step 1, a first entity (e.g. a target entity) may receive, from a second entity (e.g. a source entity) a message comprising at least one metric (e.g. confidence level and / or accuracy level). For example, the message may be a request message.In step 2, the first entity may determine if the at least one metric is invalid. For example, as described above, the first entity may determine whether the at least one metric satisfies at least one validity condition. For example, as described above, the first entity may determine whether the at least one metric has a valid type and / or a valid domain.If the first entity determines that the at least one metric is invalid, then the first entity may transmit, to the second entity, a response message in step 3a. The response message may indicate that the at least one metric is invalid. For example, as described above, if the message received from the second entity is a request message, the first entity may reject the request and transmit a response message to the second entity, wherein the response message may indicate that the request is rejected and may also indicate that the reason for the rejection is that the at least one metric is not valid.Alternatively, if the first entity determines that the at least one metric is invalid, then the first entity may determine to use a default value for the at least one invalid metric. For example, as described above, the first entity may be configured with a default value for the, or may derive a default value based on previously received (valid) values of the at least one invalid metric. In step 3b, the first entity may transmit, to the second entity, a response message.The response message may indicate that a default value has been used for the at least one invalid metric. The response message may also indicate that the at least one metric is invalid and / or at least one of the default value used and the method used to derive the default value, as described above. For example, if the message received from the second entity is a request message, the first entity may accept and / or perform the request and transmit a response message to the second entity, wherein the response message indicate that a default value has been used and that the request is accepted and / or successful.In step 4, the determination of the at least one invalid metric and / or error may be logged. For example, the logged information may include at least one of the invalid metric, the default value used, the entity which sent the metric, the time stamp of the error detection, the type of error detected, and the address of the sending entity. The information may be logged at the first entity and / or reported to another entity (e.g. a third entity).Note that the steps shown above are examples and may be omitted and / or occur in different order or combination when possible.The entity which logs the error (as has been proposed earlier) may further report the error (of invalid parameter, etc, and / or the value used which may be as described above) to another network function (NF) although this is not shown. The NF to report to may be known to the target entity e.g. based on pre-configuration, etc.The target entity shown above may be an entity receiving a metric (e.g. confidence level), and the source entity shown above may be an entity providing a metric (e.g. confidence level), or vice versa.Note that although the proposals have been for confidence level or accuracy level, they can apply to any other parameter that is exchanged between any NF as has been listed earlier. Hence the proposals apply to other parameter types in a similar manner.The proposals herein can apply to any system and is not limited to 5G only.According to an embodiment of the disclosure, there is provided a method performed by a first entity in a communication network, the method comprising: receiving, from a second entity in the communication network, a message including at least one reliability metric; and determining if the at least one reliability metric is invalid.According to an embodiment of the disclosure, wherein determining if the at least one the reliability metric is invalid comprises at least one of: determining if the reliability metric is a valid type, and determining if the reliability metric is from a valid domain.According to an embodiment of the disclosure, in response to determining that the at least one reliability metric is invalid: transmitting, to the second entity a response message indicating that the at least one reliability metric is invalid.According to an embodiment of the disclosure, in response to determining that the at least one reliability metric is invalid: determining to use a default value for the at least one invalid reliability metric.According to an embodiment of the disclosure, wherein determining to use the default value for the at least one invalid reliability metric comprises one of: using a predetermined default value for the at least one invalid reliability metric, or deriving a value for the at least one invalid reliability metric based on at least one previously received valid value for the at least one invalid reliability metric.According to an embodiment of the disclosure, further comprising logging the determination of the at least one invalid reliability metric.According to an embodiment of the disclosure, wherein logging the determination of the at least one invalid reliability metric comprises at least one of: logging information related to the invalid reliability metric at the first entity, and transmitting, to a third entity, information related to the invalid reliability metric.According to an embodiment of the disclosure, wherein the at least one reliability metric is at least one of a confidence level indicating a probability assertion for an associated Expected UE Behaviour parameter, and an accuracy level indicating the performance of the estimator (e.g. artificial intelligence / machine learning model) used for the prediction.According to an embodiment of the disclosure, wherein the first entity is a unified data management (UDM) entity and the second entity is one of an application function (AF) or network element function (NEF).According to an embodiment of the disclosure, there is provided a network entity configured to operate according to an embodiment of the disclusre.According to an embodiment of the disclosure, there is provided a method performed by a first entity in a communication network, wherein the first entity comprises a unified data management (UDM) or a network element function (NEF), the method comprising: receiving, from a second entity in the communication network, a message including at least one reliability metric of an expected user equipment (UE) behaviour parameter, wherein the reliability metric comprises at least one of a confidence level and an accuracy level; determining if the at least one reliability metric is out of range; and in response to determining that the at least one reliability metric is out of range, transmitting, to the second entity, a message indicating that the at least one reliability metric is out of range.According to an embodiment of the disclosure, wherein determining if the at least one reliability metric is out of range comprises determining if the at least one reliability metric has an invalid value.According to an embodiment of the disclosure, wherein the at least one reliability metric is determined to be out of range if the at least one reliability metric has a value less than zero or greater than one.According to an embodiment of the disclosure, wherein the first entity comprises a UDM; and wherein the message indicating that the at least one reliability metric is out of range includes at least one cause value indicating that the at least one reliability metric is out of range.According to an embodiment of the disclosure, wherein the first entity comprises a UDM and the second entity comprises a NEF or an application function (AF); and wherein the cause value indicates at least one application error, wherein the application error comprises: CONFIDENCE_LEVEL_OUT_OF_RANGE in the case that the confidence level is out of range, or ACCURACY_LEVEL_OUT_OF_RANGE in the case that the accuracy level is out of range.According to an embodiment of the disclosure, wherein the first entity comprises a NEF and the second entity comprises an application function (AF); and wherein the message indicating that the at least one reliability metric is out of range indicates at least one application error, wherein the application error comprises: CONFIDENCE_LEVEL_OUT_OF_RANGE in the case that the confidence level is out of range, or ACCURACY_LEVEL_OUT_OF_RANGE in the case that the accuracy level is out of range.According to an embodiment of the disclosure, in response to determining that the at least one reliability metric is out of range: determining to use a default value for the at least one out-of-range reliability metric.According to an embodiment of the disclosure, wherein determining to use the default value for the at least one out-of-range reliability metric comprises one of: using a predetermined default value for the at least one out-of-range reliability metric, or deriving a value for the at least one out-of-range reliability metric based on at least one previously received valid value for the at least one out-of-range reliability metric.According to an embodiment of the disclosure, logging the determination of the at least one out-of-range reliability metric.According to an embodiment of the disclosure, wherein logging the determination of the at least one out-of-range reliability metric comprises at least one of: logging information related to the out-of-range reliability metric at the first entity, and transmitting, to a third entity, information related to the out-of-range reliability metric.According to an embodiment of the disclosure, there is provided a unified data management (UDM) or a network element function (NEF) configured to operate according to the method of any one of the eleventh to twentieth examples.According to an embodiment of the disclosure may be provided in the form of an apparatus / device / network entity configured to perform one or more defined network functions and / or a method therefor. Such an apparatus / device / network entity may comprise one or more elements, for example one or more of receivers, transmitters, transceivers, processors, controllers, modules, units, and the like, each element configured to perform one or more corresponding processes, operations and / or method steps for implementing the techniques described herein. For example, an operation / function of X may be performed by a module configured to perform X (or an X-module).According to an embodiment of the present disclosure may be provided in the form of a system (e.g. a network) comprising one or more such apparatuses / devices / network entities, and / or a method therefor.It will be appreciated that examples of the present disclosure may be realized in the form of hardware, software or a combination of hardware and software. According to an embodiment of the present disclosure may provide a computer program comprising instructions or code which, when executed, implement a method, system and / or apparatus in accordance with any aspect, claim, example and / or embodiment disclosed herein. According to an embodiment of the present disclosure provide a machine-readable storage storing such a program.Figure 4 illustrates various hardware components of the first entity, according to the embodiments as disclosed herein.According to an embodiment of the disclosure, the first entity(400) may include at least one transceiver(410) and at least one processor(420).According to an embodiment of the disclosure, the first entity(400) may include memory(omitted in figure 4).The processor(420) may include various processing circuitry and / or multiple processors.　 For example, as used herein, including the claims, the term "processor" may include various processing circuitry, including at least one processor, wherein one or more of at least one processor, individually and / or collectively in a distributed manner, may be configured to perform various functions described herein. As used herein, when "a processor", "at least one processor", and "one or more processors" are described as being configured to perform numerous functions, these terms cover situations, for example and without limitation, in which one processor performs some of recited functions and another processor(s) performs other of recited functions, and also situations in which a single processor may perform all recited functions. Additionally, the at least one processor may include a combination of processors performing various of the recited / disclosed functions, e.g., in a distributed manner.　 At least one processor may execute program instructions to achieve or perform various functions.According to an embodiment of the disclosure, the processor(420) may execute at least one instruction stored in the memory to control overall operations of the first entity(400) described above.Figure 5 illustrates various hardware components of the second entity, according to the embodiments as disclosed herein.According to an embodiment of the disclosure, the second entity(500) may include at least one transceiver(510) and at least one processor(520).According to an embodiment of the disclosure, the second entity(500) may include memory(omitted in figure 5).The processor(520) may include various processing circuitry and / or multiple processors.　 For example, as used herein, including the claims, the term "processor" may include various processing circuitry, including at least one processor, wherein one or more of at least one processor, individually and / or collectively in a distributed manner, may be configured to perform various functions described herein. As used herein, when "a processor", "at least one processor", and "one or more processors" are described as being configured to perform numerous functions, these terms cover situations, for example and without limitation, in which one processor performs some of recited functions and another processor(s) performs other of recited functions, and also situations in which a single processor may perform all recited functions. Additionally, the at least one processor may include a combination of processors performing various of the recited / disclosed functions, e.g., in a distributed manner.　 At least one processor may execute program instructions to achieve or perform various functions.According to an embodiment of the disclosure, the processor(520) may execute at least one instruction stored in the memory to control overall operations of the second entity(500) described above.According to an embodiment of the disclosure, a method performed by a first entity may include receiving, from a second entity, a message associated with at least one expected user equipment behaviour parameter.According to an embodiment of the disclosure, the method may include identifying whether at least one of confidence level or accuracy level of the at least one expected UE behaviour parameter is out of range.According to an embodiment of the disclosure, the method may include transmitting, to the second entity, an error message based on the identification.According to an embodiment of the disclosure, wherein the error message indicates that the at least one of the confidence level or the accuracy level is out of range.According to an embodiment of the disclosure, the method may include wherein the identifying whether the at least one of the confidence level or the accuracy level is out of range comprises in case that the at least one of value of the confidence level or value of the accuracy level is less than zero or greater than one, identifying that the at least one of the confidence level or the accuracy is out of range.According to an embodiment of the disclosure, the method may include wherein the transmitting of the error message comprises transmitting, to the second entity, the error message based on the identification that the at least one of the confidence level or the accuracy is out of range.According to an embodiment of the disclosure, wherein the error message indicates at least one application error.According to an embodiment of the disclosure, wherein the at least one application error includes at least one of CONFIDENCE_LEVEL_OUT_OF_RANGE or ACCURACY_LEVEL_OUT_OF_RANGE.According to an embodiment of the disclosure, in case that the first entity comprises an Unified Data Management(UDM), the second entity comprises a Network Element Function(NEF) or an application function (AF).According to an embodiment of the disclosure, in case that the first entity comprises the NEF, the second entity comprises the AF.According to an embodiment of the disclosure, a first entity may include a transceiver; and a processor coupled with the transceiver.According to an embodiment of the disclosure, wherein the processor is configured to receive, from a second entity, a message associated with at least one expected user equipment (UE) behaviour parameter.According to an embodiment of the disclosure, wherein the processor is configured to identify whether at least one of confidence level or accuracy level of the at least one expected UE behaviour parameter is out of range.According to an embodiment of the disclosure, wherein the processor is configured to transmit, to the second entity, an error message based on the identification.According to an embodiment of the disclosure, wherein the error message indicates that the at least one of the confidence level or the accuracy level is out of range.According to an embodiment of the disclosure, wherein the processor is configured to in case that the at least one of value of the confidence level or value of the accuracy level is less than zero or greater than one, identify that the at least one of the confidence level or the accuracy is out of range.According to an embodiment of the disclosure, wherein the processor is configured to transmit, to the second entity, the error message based on the identification that the at least one of the confidence level or the accuracy is out of range.According to an embodiment of the disclosure, wherein the error message indicates at least one application error.According to an embodiment of the disclosure, wherein the at least one application error includes at least one of CONFIDENCE_LEVEL_OUT_OF_RANGE or ACCURACY_LEVEL_OUT_OF_RANGE.According to an embodiment of the disclosure, in case that the first entity comprises an Unified Data Management(UDM), the second entity comprises a Network Element Function(NEF) or an application function (AF).According to an embodiment of the disclosure, in case that the first entity comprises the NEF, the second entity comprises the AF.According to an embodiment of the disclosure, a method performed by a second entity may include transmitting, to a first entity, a message associated with at least one expected user equipment (UE) behaviour parameter.According to an embodiment of the disclosure, the method may include receiving, from the first entity, an error message based on the identification, at the first entity, that at least one of a confidence level or an accuracy level is out of range.According to an embodiment of the disclosure, wherein the error message indicates that the at least one of the confidence level or the accuracy level is out of range.According to an embodiment of the disclosure, wherein the error message indicates at least one application error.According to an embodiment of the disclosure, wherein the at least one application error includes at least one of CONFIDENCE_LEVEL_OUT_OF_RANGE or ACCURACY_LEVEL_OUT_OF_RANGE.According to an embodiment of the disclosure, a second entity may include a transceiver; and a processor coupled with the transceiver.According to an embodiment of the disclosure, wherein the processor is configured to transmit, to a first entity, a message associated with at least one expected user equipment (UE) behaviour parameter.According to an embodiment of the disclosure, wherein the processor is configured to receive, from the first entity, an error message based on the identification, at the first entity, that at least one of a confidence level or an accuracy level is out of range.According to an embodiment of the disclosure, wherein the error message indicates that the at least one of the confidence level or the accuracy level is out of range.While the invention has been shown and described with reference to certain examples, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the scope of the invention, as defined by the appended claims.Certain examples of the present disclosure provide one or more techniques as disclosed in the appended annex to the description. The skilled person will appreciate that any of these techniques may be applied in combination with any of the techniques described above and illustrated in the Figures.

Claims

1.A method performed by a first entity in a communication network, the method comprising:receiving, from a second entity, a message associated with at least one expected user equipment (UE) behaviour parameter;identifying whether at least one of confidence level or accuracy level of the at least one expected UE behaviour parameter is out of range; andtransmitting, to the second entity, an error message based on the identification.2.The method of claim 1, wherein the error message indicates that the at least one of the confidence level or the accuracy level is out of range.3.The method of claim 1,wherein the identifying whether the at least one of the confidence level or the accuracy level is out of range comprises in case that the at least one of value of the confidence level or value of the accuracy level is less than zero or greater than one, identifying that the at least one of the confidence level or the accuracy is out of range, andwherein the transmitting of the error message comprises transmitting, to the second entity, the error message based on the identification that the at least one of the confidence level or the accuracy is out of range.4.The method of claim 1,wherein the error message indicates at least one application error; andwherein the at least one application error includes at least one of CONFIDENCE_LEVEL_OUT_OF_RANGE or ACCURACY_LEVEL_OUT_OF_RANGE.5.The method of claim 1,in case that the first entity comprises an Unified Data Management(UDM), the second entity comprises a Network Element Function(NEF) or an application function (AF); andin case that the first entity comprises the NEF, the second entity comprises the AF.6.A method performed by a second entity in a communication network, the method comprising:transmitting, to a first entity, a message associated with at least one expected user equipment (UE) behaviour parameter;receiving, from the first entity, an error message based on the identification, at the first entity, that at least one of a confidence level or an accuracy level is out of range.7.The method of claim 6, wherein the error message indicates that the at least one of the confidence level or the accuracy level is out of range.8.The method of claim 6,wherein the error message indicates at least one application error; andwherein the at least one application error includes at least one of CONFIDENCE_LEVEL_OUT_OF_RANGE or ACCURACY_LEVEL_OUT_OF_RANGE.9.A first entity in a communication network, comprising:a transceiver; anda processor coupled with the transceiver, configured to:receive, from a second entity, a message associated with at least one expected user equipment (UE) behaviour parameter;identify whether at least one of confidence level or accuracy level of the at least one expected UE behaviour parameter is out of range; andtransmit, to the second entity, an error message based on the identification.10.The first entity of claim 9, wherein the error message indicates that the at least one of the confidence level or the accuracy level is out of range.11.The first entity of claim 9, wherein the processor is further configured to:in case that the at least one of value of the confidence level or value of the accuracy level is less than zero or greater than one, identify that the at least one of the confidence level or the accuracy is out of range, andtransmit, to the second entity, the error message based on the identification that the at least one of the confidence level or the accuracy is out of range.12.The first entity of claim 9,wherein the error message indicates at least one application error; andwherein the at least one application error includes at least one of CONFIDENCE_LEVEL_OUT_OF_RANGE or ACCURACY_LEVEL_OUT_OF_RANGE.13.The first entity of claim 9,in case that the first entity comprises an Unified Data Management(UDM), the second entity comprises a Network Element Function(NEF) or an application function (AF); andin case that the first entity comprises the NEF, the second entity comprises the AF.14.A second entity in a communication network, comprising:a transceiver; anda processor coupled with the transceiver, configured to:transmit, to a first entity, a message associated with at least one expected user equipment (UE) behaviour parameter;receive, from the first entity, an error message based on the identification, at the first entity, that at least one of a confidence level or an accuracy level is out of range.15.The second entity of claim 14, wherein the error message indicates that the at least one of the confidence level or the accuracy level is out of range.

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