Applicable ai / ML functionality reporting

Abstract

Example embodiments of the present disclosure relate to applicable artificial intelligence (AI) / machine learning (ML) functionality reporting In an aspect, a terminal device receives, from a network device, a first message for configuring applicable AI / ML functionality reporting, and the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority. The terminal device transmits, to the network device, based on the first message, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

Description

APPLICABLE AI / ML FUNCTIONALITY REPORTINGCROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims priority from India Provisional Application No. 202441060522, filed August 9, 2024, which is hereby incorporated by reference in its entirety.FIELD

[0002] Example embodiments of the present disclosure generally relate to the field of communications, and in particular, to devices, methods, apparatuses and a computer readable storage medium for applicable artificial intelligence (Al) / machine learning (ML) functionality reporting.BACKGROUND

[0003] A communication network can be seen as a facility that enables communications between two or more communication devices, or provides communication devices access to a data network. A mobile or wireless communication network is one example of a communication network. A communication device may be provided with a service by an application server.

[0004] Such communication networks operate in according with standards such as those provided by 3GPP (Third Generation Partnership Project) or ETSI (European Telecommunications Standards Institute). Examples of standards are the so-called 5G (5th Generation) standards, 6G (6th Generation) standards or other standards provided by 3GPP.SUMMARY

[0005] In general, example embodiments of the present disclosure provide a solution for applicable Al / ML functionality reporting.

[0006] In a first aspect, there is provided a terminal device. The terminal device comprises at least one processor and at least one memory storing instructions that, when executed by the at least one processor, cause the terminal device at least to receive, from a network device, a first message for configuring applicable Al / ML functionality reporting. The first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority. The terminal device is further caused to transmit, to the network device, based on the first message, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

[0007] In a second aspect, there is provided a network device. The network device comprises at least one processor and at least one memory storing instructions that, when executed by the at least one processor, cause the network device at least to transmit, to a terminal device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting. The first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a secondset of one or more applicable AI / ML functionalities to be reported without priority. The network device is further caused to receive, from the terminal device, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

[0008] In a third aspect, there is provided method. The method comprises receiving, from a network device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, and the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority; and transmitting, to the network device, based on the first message, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

[0009] In a fourth aspect, there is provided method. The method comprises transmitting, to a terminal device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, and the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority; and receiving, from the terminal device, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

[0010] In a fifth aspect, there is provided an apparatus. The apparatus comprises means for receiving, from a network device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, and the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority; and means for transmitting, to the network device, based on the first message, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

[0011] In a sixth aspect, there is provided an apparatus. The apparatus comprises means for transmitting, to a terminal device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, and the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority; and means for receiving, from the terminal device, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

[0012] In a seventh aspect, there is provided a non-transitory computer readable medium comprising program instructions for causing an apparatus to perform at least the method according to any one of the third aspect to fourth aspect.

[0013] In an eighth aspect, there is provided a computer program comprising instructions, which, when executed by an apparatus, cause the apparatus at least to perform at least the method according to according to any one of the third aspect to fourth aspect.

[0014] In a ninth aspect, there is provided a terminal device. The terminal device comprises receivingcircuitry configured to receive, from a network device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, and the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority; and transmitting circuitry configured to transmit, to the network device, based on the first message, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

[0015] In a tenth aspect, there is provided a network device. The network device comprises transmitting circuitry configured to transmitting, to a terminal device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, and the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority; and receiving circuitry configured to receive, from the terminal device, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

[0016] It is to be understood that the summary section is not intended to identify key or essential features of embodiments of the present disclosure, nor is it intended to be used to limit the scope of the present disclosure. Other features of the present disclosure will become easily comprehensible through the following description.BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Some example embodiments will now be described with reference to the accompanying drawings, in which:

[0018] FIG. 1A illustrates an example of a network environment in which example embodiments of the present disclosure can be implemented;

[0019] FIG. 1 B illustrates two beam management (BM) cases related to some embodiments of the present disclosure;

[0020] FIG. 10 illustrates an example of proactive reporting for applicable functionality related to some embodiments of the present disclosure;

[0021] FIG. 1 D illustrates an example of reactive reporting for applicable functionality related to some embodiments of the present disclosure;

[0022] FIG. 1 E illustrates an example of UE Assistance Information related to some embodiments of the present disclosure;

[0023] FIG. 1 F an example of RRC reconfiguration related to some embodiments of the present disclosure;

[0024] FIG. 2 illustrates a flow chart of method according to some embodiments of the present disclosure;

[0025] FIG. 3 illustrates a process for applicable functionality reporting with priority using RRCReconfigurationComplete according to some embodiments of the present disclosure;

[0026] FIG. 4 illustrates a process for applicable functionality reporting with priority using urgent UAI message according to some embodiments of the present disclosure;

[0027] FIG. 5 illustrates a process for applicable functionality reporting with priority using urgent UAI message piggybacking RRCReconfigurationComplete according to some embodiments of the present disclosure;

[0028] FIG. 6 illustrates a process for no applicable functionality reporting with priority using empty container in RRCReconfigurationComplete according to some embodiments of the present disclosure;

[0029] FIG. 7 illustrates Sample ASN.1 message structures according to some embodiments of the present disclosure;

[0030] FIG. 8 illustrates applicability UE Assistance Information according to some embodiments of the present disclosure;

[0031] FIG. 9 illustrates a flowchart of a method implemented at a terminal device in accordance with some example embodiments of the present disclosure;

[0032] FIG. 10 illustrates a flowchart of a method implemented at a network device in accordance with some example embodiments of the present disclosure;

[0033] FIG. 11 illustrates simplified block diagram of a device that is suitable for implementing some example embodiments of the present disclosure; and

[0034] FIG. 12 illustrates a block diagram of an example of a computer readable medium in accordance with some example embodiments of the present disclosure.

[0035] Throughout the drawings, the same or similar reference numerals represent the same or similar elements.DETAILED DESCRIPTION

[0036] Principles of the present disclosure will now be described with reference to some example embodiments. It is to be understood that these embodiments are described only for the purpose of illustration and help those skilled in the art to understand and implement the present disclosure, without suggesting any limitation as to the scope of the disclosure. The disclosure described herein can be implemented in various manners other than the ones described below.

[0037] In the following description and claims, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skills in the art to which this disclosure belongs.

[0038] References in the present disclosure to “one embodiment,” “an embodiment,” “an example embodiment,” and the like indicate that the embodiment described may include a particular feature, structure, or characteristic, but it is not necessary that every embodiment includes the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it issubmitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.

[0039] It shall be understood that although the terms “first” and “second” etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and similarly, a second element could be termed a first element, without departing from the scope of example embodiments. As used herein, the term “and / or” includes any and all combinations of one or more of the listed terms.

[0040] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises”, “comprising”, “has”, “having”, “includes” and / or “including”, when used herein, specify the presence of stated features, elements, and / or components etc., but do not preclude the presence or addition of one or more other features, elements, components and / or combinations thereof. As used herein, “at least one of the following: ” and “at least one of ” and similar wording, where the list of two or more elements are joined by “and” or “or”, mean at least any one of the elements, or at least any two or more of the elements, or at least all the elements.

[0041] As used in this application, the term “circuitry” may refer to one or more or all of the following:(a) hardware-only circuits (such as in analog and / or digital circuits) and(b) combinations of hardware circuits and software, such as (as applicable):(i) a combination of analog and / or digital hardware circuit(s) with software (e.g., firmware); and(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(c) hardware circuit(s) and or processor(s), such as a microprocessor(s) or a portion of a microprocessor(s), that requires software (for example, firmware) for operation, but the software may not be present when it is not needed for operation.

[0042] 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.

[0043] As used herein, the term “cellular network” refers to a network operating in accordance with any suitable radio access technology defined by standards, such as Long Term Evolution (LTE), LTE-Advanced (LTE-A), new radio Wideband Code Division Multiple Access (WCDMA), High-Speed Packet Access (HSPA), Narrow Band Internet of Things (NB-loT) and so on. Furthermore, the communications between a terminal device and a network device of a cellular network may be performed according to any suitable communication protocols, including, but not limited to, the fourth generation (4G), 4.5G, the future fifth generation (5G) communication protocols, and / or any other protocols either currently known or to be developed in the future. Embodiments of the present disclosure may be applied in various cellular networks. Given the rapid development in communications, there will of course also be future type communication technologies and systems with which the present disclosure may be embodied. It should not be seen as limiting the scope of the present disclosure to only the aforementioned system.

[0044] As used herein, the term “network device” refers to any device in a cellular network via which a terminal device accesses a data network and receives services exposed by other network devices of the cellular network. In some examples, a network device may comprise or implement a network function of a 5thgeneration communication system (5GS) (e.g., a core network) of a cellular network. In some examples, the network devices may be located at the RAN of the 5GS. The network device may be part of a satellite, a base station (BS) or an access point (AP), for example, a node B (NodeB or NB), an evolved NodeB (eNodeB or eNB), a NR NB (also referred to as a gNB), a Remote Radio Unit (RRU), a radio header (RH), a remote radio head (RRH), a relay, a low power node such as a femto, a pico node, and so forth, depending on the applied terminology and technology. A gNB may include a centralized unit CU and one or more distributed DUs. Femto and Pico nodes are small base stations with a small coverage area.

[0045] The term “terminal device” refers to a device of a communication system of a cellular network, such as a 5thgeneration communication system (5GS) that may be capable of wireless (e.g., radio) communication with a NR-RAN of the 5GS). By way of example rather than limitation, a terminal device may also be referred to as a wireless communication device, user equipment (UE), a Subscriber Station (SS), a Portable Subscriber Station, a Mobile Station (MS), or an Access Terminal (AT). Examples of a terminal device include, but not limited to, a mobile phone, a cellular phone, a smart phone, voice over IP (VoIP) phones, wireless local loop phones, a tablet, a wearable terminal device, a personal digital assistant (PDA), portable computers, desktop computer, image capture terminal devices such as digital cameras, gaming terminal devices, music storage and playback appliances, vehicle-mounted wireless terminal devices, wireless endpoints, mobile stations, laptop-embedded equipment (LEE), laptop-mounted equipment (LME), USB dongles, smart devices, wireless customer-premises equipment (CPE), an Internet of Things (loT) device, a watch or other wearable, a head-mounted display (HMD), a vehicle, a drone, a medical device and applications (for example, remote surgery), an industrial device and applications (for example, a robot and / or other wireless devices operating in an industrial and / or an automated processing chain contexts), a consumerelectronics device, a device operating on commercial and / or industrial wireless networks, and the like. In the following description, the terms “terminal device”, “communication device”, “terminal”, “user equipment” and “UE” may be used interchangeably.

[0046] Currently, the proactive reporting mechanism is enabled by the UE assistance information allowing the UE to track the changes of applicable functionality and inform the network using the message whereas the reactive reporting mechanism may get enabled by the RRC reconfiguration complete message allowing the UE to return the current state of the applicable functionality and inform the network using the message.

[0047] Neither proactive nor reactive reporting approaches satisfy the following key requirements in applicable functionality reporting. There is no any demand on when the UAI is transmitted by the UE. The delay in UAI reporting does not allow the network to immediately configure the UE for AIML enabled functionalities. The reactive approach requires an explicit reconfiguration message to the UE prompting the UE to return a reconfiguration complete

[0048] I n view of the above, example embodiments of the present disclosure provide a solution for at least one measurement on multiple cells. In the example embodiments of the present disclosure, a terminal device may perform at least one measurement on multiple cells by receiving multiple signals from the multiple cells within a time window to obtain multiple samples for the multiple cells. The terminal device may further process, within the time window, a first sample from a first cell among the multiple cells, and process, outside the time window, at least one other sample from at least one other cell among the multiple cells. In this way, instead of having 2 separate procedures, it is more efficient to define one unified procedure combining the best features of both proactive and reactive reporting.

[0049] This disclosure defines the embodiments to achieve a unified reporting of applicable functionalities allowing the network to take the applicable functionalities for AI / ML enabled functionality into account for UE inference as soon as possible.

[0050] FIG. 1A illustrates an example of a network environment 100a in which example embodiments of the present disclosure can be implemented. The environment 100a may be a part of a communication network and comprise a plurality of terminal devices and network devices, such as a terminal device 110, a network device 120. As an example, the terminal device 110 may be implemented as a User Equipment (UE) or an Access Terminal (AT), and the network device 120 may be implemented as a gNB, or a base station (BS). The network device 120 may transmit various data to the terminal device 110 via network environment 100.

[0051] To transmit data and / or control information, the terminal device 110 may perform communications with the network device 120. A link from the network device 120 to the terminal device 110 is referred to as a downlink (DL), while a link from the terminal device 110 to the network device 120 is referred to as an uplink (UL).

[0052] Although the terminal device 110 and the network device 120 are described in the communicationenvironment 100 of FIG. 1 A, embodiments of the present disclosure may equally apply to any other suitable communication devices in communication with one another. That is, embodiments of the present disclosure are not limited to the exemplary scenarios of FIG. 1 A. In this regard, it is noted that although the terminal device is schematically depicted as a mobile phone and the network device 120 is schematically depicted as a satellite in FIG. 1 , it is understood that these depictions are exemplary in nature without suggesting any limitation. In other embodiments, the terminal device 110 and the network device 120 may be any other communication devices, for example, any other wireless communication devices.

[0053] It is to be understood that the particular number of various communication devices and the particular number of various communication links as shown in FIG. 1 A is for illustration purpose only without suggesting any limitations. The communication environment 100a may include any suitable number of communication devices and any suitable number of communication links for implementing embodiments of the present disclosure. In addition, it should be appreciated that there may be various wireless as well as wireline communications (if needed) among all of the communication devices.

[0054] FIG. 1 B illustrates two beam management (BM) cases 100b related to some embodiments of the present disclosure. For AI / ML enhancements related to beam management, two sub-use cases have been identified, beam prediction in the spatial domain (BM-Case1) and beam prediction in the time domain (BM- Case2).

[0055] The scope of spatial beam prediction (BM-Case1) is to predict the best DL Tx beam and / or DL Tx / Rx beam pairs in different spatial locations. Conversely, time-domain beam predictions (BM-Case2) aim to predict the best DL Tx beam and / or DL Tx / Rx beam pairs beam to use for next time instants. The primary motivation is to support a reduced overhead and lower beam measurements and reporting latency. Based on the evaluation, the benefits and gains were verified based on given metrics, and they could be supported by single-sided models and consider supporting the necessary / recommended LCM components for selected sub use cases.

[0056] FIG. 1 C illustrates an example 100c of proactive reporting for applicable functionality related to some embodiments of the present disclosure. In this example embodiments, at 113, the network device 120 may send UECapabilityEnquiry message to initiate the procedure to a UE 110 reporting its AI / ML supported functionalities. At 115, the UE may send UECapablitylnfonvation message to the network device 120, containing supported functionalities at the UE side.

[0057] At 117, the Network device 120 may configure the UE 110 with functionality configurations for evaluation. The network device 120 may configure UE 110 that it is allowed to provide its applicable functionalities.

[0058] At 119, the UE 110 may send applicable functionalities to network device 120 upon functionality configuration and upon change of applicable functionality / condition. At 121 , the network device 120 may send inference activation configuration for one or more of the applicable functionalities to the UE 110. At123, inference or monitoring may be started based on network / UE activation / deactivation.

[0059] FIG. 1 D illustrates an example 10Od of reactive reporting for applicable functionality related to some embodiments of the present disclosure. In this example embodiments, at 125, the network device 120 may send UECapabilityEnquiry message to initiate the procedure to a UE 110 reporting its AI / ML supported functionalities. At 127, UE 110 may send UECapablitylnfonvation message to the network device 120, containing supported functionalities at the UE 110 side.

[0060] At 129, the network device 120 may provide network configurations and initiates UE 110 to report its applicable functionalities. At 131 , the UE 110 may send applicable functionalities to the network device 120.

[0061] At 133, the network device 120 may send updated inference configuration for applicable functionalities reported at 131 to the UE 110. At 135, inference or monitoring based on network, UE activation or deactivation may be started.

[0062] FIG. 1 E illustrates an example 10Oe of UE Assistance Information related to some embodiments of the present disclosure. In this example embodiments, at 137, the UE 110 may inform various internal status to the network device 120 so that network device 120 may assign or control resources in which fits well at specific moment of each connected UE.

[0063] At 139, the UE 110 may transmit UE assistance information (UAI) to the network device 120. The UAI may be a special set of RRC messages (mechanism) and used for power saving (the messages related to the configuration for drx, aggregated bandwidth, MIMO layers), overheating mitigation (overheating assistance information), Measurement (the messages related to relaxation for RLM, BFD, RRM measurement), and others: preference on RRC Status, etc.

[0064] FIG. 1 F illustrates an example 10Of of RRC reconfiguration related to some embodiments of the present disclosure. At 141 , the network device 120 may transmit a RRCReconfiguration message to the terminal device 110. At 143, the terminal device 110 may transmit a RRCReconfigurationComplete message to the network device 120 indicating RRC reconfiguration is successful.

[0065] FIG. 2 illustrates a flowchart of method according to some embodiments of the present disclosure. For the purpose of discussion, the method 200 will be described with reference to FIG. 1A. It would be appreciated that although the process flow 200 has been described referring to FIG. 1A, this process flow 200 may be likewise applied to other similar communication scenarios.

[0066] In the process flow 200, a network device 120 may transmit (205), a first message 202 for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting to a terminal device 110. The first message 202 may indicate (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority.

[0067] In some embodiments, the first set of one or more applicable AI / ML functionalities and the secondset of one or more applicable AI / ML functionalities may be defined based on a list of AI / ML functionalities provided by the network device to the terminal device to assess applicability or non-applicability.

[0068] For example, in an embodiment, the network device 120 may indicate in a RRC reconfiguration message to split the reporting of the applicable functionalities with a) priority and b) follow-on indicator. Priority and follow-on may be defined based on the list of functionalities that network device 120 sends to the terminal device 110 in RRC reconfiguration message which the terminal device 110uses to assess applicability or non-applicability.

[0069] I n some further embodiments, the first message may further indicate that the first set of one or more applicable AI / ML functionalities are to be reported using (i) a first radio resource control (RRC) reconfiguration complete message or (ii) a first user equipment (UE) assistance information (UAI) message to be transmitted upon receiving the first message. For example, additional configuration for priority reporting may use RRC reconfiguration complete message or “immediate” UAI (to be sent by the terminal device 110 immediately upon receiving the RRC reconfiguration message). Follow-on reporting may use separate UAI message.

[0070] The terminal device 110 may then receive (210) the first message for configuring applicable Al) / ML functionality reporting from a network device 120. The terminal device 110 may then transmit (215) a second message 204 including at least one identity (ID) of at least one applicable AI / ML functionality to the network device 120 based on the first message 202.

[0071] In some embodiments, the terminal device 110 may transmit the second message 204 by based on determining that the at least one applicable AI / ML functionality is among the first set of one or more applicable AI / ML functionalities, transmitting a first RRC reconfiguration complete message including the at least one ID of at least one applicable AI / ML functionality.

[0072] In some embodiments, the first RRC reconfiguration complete message includes a container which includes UAI, and the UAI includes the at least one ID of the at least one applicable AI / ML functionality. For example, the network device 120 may configure the terminal device 110 to report the “immediate (urgent)” UAI embedded as a container in RRCReconfigurationComplete in which embedded UAI contains functionality ID (e.g., CSI ReportConfig IDs in case of BM use case) that may be immediately activated.

[0073] In some embodiments, the UAI may further include an indication that the terminal device is to transmit further applicability information for at least one further applicable AI / ML functionality. For example, the follow on indicator may indicate to the network device 120 that there is more “applicability information” concerning applicable functionalities.

[0074] In some further example embodiments, the terminal device may transmit the second message 204 by based on determining that the at least one applicable AI / ML functionality is among the first set of one or more applicable AI / ML functionalities, transmitting a first UAI message including the at least one ID of at least one applicable AI / ML functionality.

[0075] In some example embodiments, the first UAI message may be transmitted immediately uponreceiving the first message. For example, the UAI may be transmitted immediately (before sending RRC reconfiguration complete).

[0076] In some other embodiments, the first UAI message may include an indication that the RRC reconfiguration complete message is to be transmitted after the first UAI message. For example, UAI message may contain an indication to the network device 120 that RRC reconfiguration complete will follow (so network is prepared to receive it later and first process the UAI). In other words, the network device 120 doesn’t have to wait for RRC reconfiguration complete but may receive a UAI after RRC Reconfiguration to reduce the latency on receiving the immediately applicable functionalities.

[0077] In some embodiments, the first UAI message may include the RRC reconfiguration complete message. For example, the UAI may be transmitted immediately and piggyback RRC reconfiguration complete as well in which 2 RRC messages are transmitted together. Alternatively, or additionally, the first UAI message may include an indication that the RRC reconfiguration complete message is not to be transmitted. For example, the UAI may be transmitted immediately and indicates RRC reconfiguration complete will not be transmitted by the UE (UAI reception by network is sufficient) - this requires UAI to contain the RRC transaction ID.

[0078] In some further embodiments, the terminal device 110 may receive, from the network device 120, first configuration information for configuring the terminal device to switch to an applicable AI / ML functionality after receiving the first message 202, based on determining that the applicable AI / ML functionality is an only applicable AI / ML functionality.

[0079] For example, the network device 120 may configure the terminal device 110 to implicitly switch to the available ML functionality after receiving RRCReconfiguration message, if there is a single one. This saves one further DL indication from the network to request the UE to switch and reduces the latency of the inference. In some embodiments, the terminal device 110 may receive, from the network device 120, second configuration information for configuring the terminal device to indicate, through an empty container, that there is no applicable functionality to be reported with priority.

[0080] In some further embodiments, the empty container may be included in a first RRC reconfiguration complete message or a first UAI message to be transmitted upon receiving the first message. For example, the network device 120 may configure the terminal device 110 to report no “immediate (urgent)” applicable functionalities indicated by an empty container (indicating absence) in RRC reconfiguration complete. In some embodiments, the network device 120 may configure the terminal device 110 to report no “immediate” applicable functionalities indicated by an empty container (indicating absence) in “immediate (urgent)” UAI.

[0081] In some examples, the terminal device 110 may transmit the second message by based on determining that the at least one applicable AI / ML functionality is among the second set of one or more applicable AI / ML functionalities, transmitting a second UAI message or a second RRC reconfiguration complete message including the at least one ID of the at least one applicable AI / ML functionality.

[0082] In some examples, the terminal device 110 may perform a priority check on the first set of one or more applicable AI / ML functionalities based on receiving the first message indicating the first set of one or more applicable AI / ML functionalities to be reported with priority.

[0083] In some further embodiments, the terminal device 110 may start applying the applicable AI / ML functionality based on transmitting the second message 204 including an identity (ID) of an applicable AI / ML functionality reported with priority to the network device 120. In some further embodiments, the first message 202 may be an RRC reconfiguration message, and the second message 204 may be an RRC reconfiguration complete message or an UAI message.

[0084] The network device 120 may then receive (220) the second message 204 including at least one identity (ID) of the at least one applicable AI / ML functionality from the terminal device 110. In some further embodiments, the network device may receive the second message 204 by receiving a first RRC reconfiguration complete message including the at least one ID of at least one applicable AI / ML functionality which is among the first set of one or more applicable AI / ML functionalities.

[0085] In some example embodiments, the network device 120 may receive the second message 204 by receiving a first UAI message including the at least one ID of at least one applicable AI / ML functionality which is among the first set of one or more applicable AI / ML functionalities. In some example embodiments, the network device 120 may transmit first configuration information for configuring the terminal device to switch to an applicable AI / ML functionality to the terminal device 110 after receiving the first message, in the case that the applicable AI / ML functionality is an only applicable AI / ML functionality.

[0086] In some example embodiments, the network device 120 may transmit, to the terminal device 110, second configuration information for configuring the terminal device 110 to indicate, through an empty container, that there is no applicable functionality to be reported with priority. In some other embodiments, the network device 120 may receive the second message 204 by receiving a second UAI message or a second RRC reconfiguration complete message including the at least one ID of the at least one applicable AI / ML functionality which is among the second set of one or more applicable AI / ML functionalities. In this way, a method for unified reporting with multiple signalling allows the network device to configure the terminal device for reporting applicable functionalities.

[0087] FIG. 3 illustrates a process 300 for applicable functionality reporting with priority using RRCReconfigurationComplete according to some embodiments of the present disclosure. It is noted that FIG. 3 can be deemed as a further example of the process flow 200. For example, the UE 310 may be example devices of the terminal device 110, the gNB 320 may be the example devices of the network device 120. It is to be understood that these devices are described only for the purpose of illustration without suggesting any limitation as to the scope of the disclosure. This process will be described in detail as follows.

[0088] At 302, the UE attach procedure may start. At 304, the gNB 320 may transmit an UE capability enquiry to the UE 310. At 306, the UE 310 may report its capability to support beam prediction with featuregroups (UE capabilities) that are associated with beam prediction at the UE side.

[0089] At 308, the gNB 320 may receive UE capability information and determine if beam prediction can be supported. In some embodiments, the gNB 320 may determine NW-additional-condition-l Ds (such as, assjdl , ass_id2, ass_id3 in Figure 3) via RRCReconfiguration which are considered within configured functionalities (e.g., CSI reportConfig 1 , CSIReportConfig2 and CSIReportConfig3 in case of BM use case). In some further embodiments, the gNB 320 may also configure applicability reporting with priority through applicability_reporting_type=urgent_reconf\N\Vn'm RRCReconfiguration.

[0090] The UE 310 may receive RRCReconfiguration considering gNB 320 request on applicability reporting (applicability_reporting_type=urgent_reconf) with priority and it considers associatedjd check of the best applicable model applicable with provided CSI ReportConfigs by the gNB 320 in previous action.

[0091] At 312, the UE 310 may perform priority check of applicable functionalities. At 314, the UE may report RRCReconfigurationComplete including CSIReportConfigID (CSIReportConfig_1 in this example) which may be activated immediately by the gNB 320 (such as, CSIReportConfigl (assjdl) as reported). The UE may disable non-ML CSI ReportConfig autonomously.

[0092] At 316, the UE 310 may perform ML based beam prediction based on reported applicable CSI ReportConfig at 314. At 318, the UE 310 may report up to Top-K predicted CRIs corresponding to configured RS resources.

[0093] At 322, the UE 310 may check applicability of non-prioritized applicable CSI ReportConfigs (e.g., using corresponding associated IDs) applicable CSIReportConfigs in which are not among applicable CSI ReportConfigs with priority (as reported at 314). At 324, the UE may report them using a followed-on UAI message ( CSIReportConfigs I D_2 ) reported using a followed up UAI message.

[0094] FIG. 4 illustrates a process 400 for applicable functionality reporting with priority using urgent UAI message according to some embodiments of the present disclosure. It is noted that FIG. 4 can be deemed as a further example of the process flow 200. For example, the UE 410 may be example devices of the terminal device 110, the gNB 420 may be the example devices of the network device 120. It is to be understood that these devices are described only for the purpose of illustration without suggesting any limitation as to the scope of the disclosure. This process will be described in detail as follows. In this embodiment, the UE 410 sends applicable functionalities with priority in an urgent UAI message

[0095] At 402, the UE attach procedure may start. At 404, the gNB 420 may transmit an UE capability enquiry to the UE 410. At 406, the UE may report its capability on supporting beam prediction with associated feature groups (UE capabilities) that are associated with the beam prediction at the UE side.

[0096] At 408, the gNB 420 may receive UE capability signalling and determines if beam prediction may be supported in certain CGI. In some embodiments, the gNB 420 may determine NW-additional-condition- IDs (such as, assjdl , assjd2, assjd3) via RRCReconfiguration which are considered within configured CSI reportConfig 1, CSIReportConfig2 and CSIReportConfig3. The gNB 420 may also determine applicablereporting with priority through applicability_reporting_type=urgent_UAI within RRCReconfiguration

[0097] The UE 410 may receive RRCReconfiguration considering gNB 420 request on applicability reporting (applicability_reporting_type=urgent_UAI) with priority and it may consider or perform checking of associated Jd of the best applicable model applicable with provided CSI ReportConfigs by the NW in previous action.

[0098] At 412, the UE 410 may perform priority check of applicable functionalities. At 414-416, the UE 410 may report RRCReconfigurationComplete including CSIReportConfigID (CSIReportConfig_1 in this example) which may be activated immediately by the gNB (see config 1 (ass Jd1) as reported in Figure 4). At 418, the UE may disable non-ML CSI ReportConfig autonomously.

[0099] At 422, the UE 410 may perform ML based beam prediction based on reported applicable CSI ReportConfig at 412 and report up to Top-K predicted CRIs corresponding to configured RS resources. At 424-426, the UE 410 may report non-prioritized applicable CSI ReportConfigs (e.g., using corresponding associated IDs) applicable CSI ReportConfigs in which are not among applicable CSI ReportConfigs with priority (as reported at 412) using a followed-on UAI message.

[0100] FIG. 5 illustrates a process 500 for applicable functionality reporting with priority using urgent UAI message piggybacking RRCReconfigurationComplete according to some embodiments of the present disclosure. It is noted that FIG. 5 can be deemed as a further example of the process flow 200. For example, the UE 510 may be example devices of the terminal device 110, the gNB 520 may be the example devices of the network device 120. It is to be understood that these devices are described only for the purpose of illustration without suggesting any limitation as to the scope of the disclosure. This process will be described in detail as follows. In this example embodiment, the UE 510 may send applicable functionalities with priority in an urgent UAI message and piggybacks RRCReconfigurationComplete.

[0101] At 502, the UE attach procedure may start. At 504, the gNB 520 may transmit an UE capability enquiry to the UE 510. At 506, the UE 510 may report its capability on supporting beam prediction with associated feature groups (UE capabilities) that are associated with the beam prediction at the UE side.

[0102] At 508, the gNB 520 may receive UE capability signalling and determine if beam prediction can be supported in certain CGI. The gNB 520 may determine NW-additional-condition-IDs (such as, assjdl , ass_id2, and ass_id3) via RRCReconfiguration which are considered within configured CSIreportConfigl, CSI ReportConfig2 and CSI ReportConfig3. The gNB 520 may also determine applicable reporting with priority through applicability_reporting_type=Piggyback_UAI within RRCReconfiguration

[0103] The UE 510 may receive RRCReconfiguration considering the gNB 520 request on applicability reporting (applicability_reporting_type=Piggyback_UAI) with priority. The UE 510 may consider or perform checking of associatedjd of the best applicable model applicable with provided CSIReportConfigs by the gNB 520 in previous action.

[0104] At 512, the UE 510 may perform priority check of applicable functionalities. At 514, the UE 510may report urgent UAI message in including functionality ID which may be activated immediately by the gNB 520 embedded.

[0105] The UE 510 may perform ML based beam prediction based on reported applicable CSI ReportConfig in at 512 and report up to Top-K predicted CRIs corresponding to configured RS resources. The UE 510 may check applicability of non-prioritized applicable CSIReportConfigs (e.g., using corresponding associated IDs).

[0106] At 516, the UE 510 may report non-prioritized applicable CSIReportConfigs (e.g., using corresponding associated IDs) applicable CSIReportConfigs in which are not among applicable CSIReportConfigs with priority (as reported at 514) using a followed-on RRCReconfigurationComplete message.

[0107] At 517, the UE 510 may start applying CSIReportConfigJ (assjd 1 or associated Jd 1) and disable non-ml config. At 518, the UE 510 may transmit beam report associated with CSIReportConfigJ predicted CRI corresponding to RS resources.

[0108] FIG. 6 illustrates a process 600 for no applicable functionality reporting with priority using empty container in RRCReconfigurationComplete according to some embodiments of the present disclosure. It is noted that FIG. 6 can be deemed as a further example of the process flow 200. For example, the UE 610 may be example devices of the terminal device 110, the gNB 620 may be the example devices of the network device 120. It is to be understood that these devices are described only for the purpose of illustration without suggesting any limitation as to the scope of the disclosure. This process will be described in detail as follows. In this example embodiment, the UE 610 may report no applicable functionalities with priority using RRCReconfigComplete.

[0109] At 602, the UE attach procedure may start. At 604, the gNB 620 may transmit an UE capability enquiry to the UE 610. At 606, the UE 610 may report its capability on supporting beam prediction with associated feature groups (UE capabilities) that are associated with the beam prediction at the UE side.

[0110] The gNB 620 may receive UE capability signalling and determines if beam prediction can be supported in certain CGI. At 608, the gNB 620 may determine NW-additional-condition-IDs (such as, assjdl , ass_id2,ass_id3) via RRCReconfiguration which are considered within configured CSIreportConfigl, CSIReportConfig2 and CSIReportConfigs. The gNB 620 may also determine applicable reporting without priority through applicability_reporting_type=no_urgent \N\Vn\n RRCReconfiguration.

[0111] The UE 610 may receive RRCReconfiguration considering gNB 620 request on applicability reporting (applicability_reporting_type=no_urgenf) with no priority after considering or performing of all the associated Jd of the applicable model applicable with provided CSIReportConfigs by the gNB 620 in previous action.

[0112] At 612, the UE 610 may perform priority check of applicable functionalities. At 614, the UE 610 may report RRCReconfigComplete with empty container determining that no associated ID corresponding toapplicable CSI ReportConfig which may be activated immediately by the gNB 620 embedded.

[0113] The UE 610 may perform ML based beam prediction based on reported applicable CSI ReportConfig at 612 and report up to Top-K predicted CRIs corresponding to configured RS resources. The UE 610 may report applicable CSIReportConfigs (e.g., using corresponding associated IDs) applicable CSI ReportConfigs using a followed-on UAI message.

[0114] FIG. 7 illustrates sample ASN.1 message structures 700 according to some embodiments of the present disclosure. The block 702 is the change of the embodiment of the present disclosure to the relevant protocol or specification. FIG. 8 illustrates applicability UE Assistance Information 800 according to some embodiments of the present disclosure. The block 802 is the change of the embodiment of the present disclosure to the relevant protocol or specification.

[0115] FIG. 9 illustrates a flowchart of a method 900 implemented at a terminal device in accordance with some example embodiments of the present disclosure. For the purpose of discussion, the method 900 will be described from the perspective of the terminal device 110 with reference to FIG. 1A.

[0116] At block 902, the terminal device 110 may receive, from a network device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority. At block 904, the terminal device 110 may transmit, to the network device, based on the first message, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

[0117] In some embodiments, the first set of one or more applicable AI / ML functionalities and the second set of one or more applicable AI / ML functionalities are defined based on a list of AI / ML functionalities provided by the network device to the terminal device to assess applicability or non-applicability.

[0118] In some further embodiments, the first message further indicates that the first set of one or more applicable AI / ML functionalities are to be reported using (i) a first radio resource control (RRC) reconfiguration complete message or (ii) a first user equipment (UE) assistance information (UAI) message to be transmitted upon receiving the first message.

[0119] In some example embodiments, the terminal device may transmit the second message by based on determining that the at least one applicable AI / ML functionality is among the first set of one or more applicable AI / ML functionalities, transmitting a first RRC reconfiguration complete message including the at least one ID of at least one applicable AI / ML functionality.

[0120] In some example embodiments, the first RRC reconfiguration complete message includes a container which includes UAI, and the UAI includes the at least one ID of the at least one applicable AI / ML functionality. In some example embodiments, the UAI further includes an indication that the terminal device is to transmit further applicability information for at least one further applicable AI / ML functionality.

[0121] In some other example embodiments, the terminal device may transmit the second message bybased on determining that the at least one applicable AI / ML functionality is among the first set of one or more applicable AI / ML functionalities, transmitting a first UAI message including the at least one ID of at least one applicable AI / ML functionality.

[0122] In some other example embodiments, the first UAI message is transmitted immediately upon receiving the first message. In some other example embodiments, the first UAI message includes an indication that the RRC reconfiguration complete message is to be transmitted after the first UAI message; the first UAI message includes the RRC reconfiguration complete message; or the first UAI message includes an indication that the RRC reconfiguration complete message is not to be transmitted.

[0123] In some example embodiments, the terminal device may receive, from the network device, first configuration information for configuring the terminal device to switch to an applicable AI / ML functionality after receiving the first message, based on determining that the applicable AI / ML functionality is an only applicable AI / ML functionality.

[0124] In some example embodiments, the terminal device may receive, from the network device, second configuration information for configuring the terminal device to indicate, through an empty container, that there is no applicable functionality to be reported with priority. In some example embodiments, the empty container is included in a first RRC reconfiguration complete message or a first UAI message to be transmitted upon receiving the first message.

[0125] In some example embodiments, the terminal device may transmit the second message by based on determining that the at least one applicable AI / ML functionality is among the second set of one or more applicable AI / ML functionalities, transmitting a second UAI message or a second RRC reconfiguration complete message including the at least one ID of the at least one applicable AI / ML functionality.

[0126] In some example embodiments, the terminal device may, based on receiving the first message indicating the first set of one or more applicable AI / ML functionalities to be reported with priority, perform a priority check on the first set of one or more applicable AI / ML functionalities.

[0127] In some example embodiments, based on transmitting, to the network device, the second message including an identity (ID) of an applicable AI / ML functionality reported with priority, the terminal device may start applying the applicable AI / ML functionality. In some further embodiments, the first message is an RRC reconfiguration message; or the second message is an RRC reconfiguration complete message or an UAI message.

[0128] FIG. 10 illustrates a flowchart of a method 1000 implemented at a network device in accordance with some example embodiments of the present disclosure. For the purpose of discussion, the method 1000 will be described from the perspective of the network device 120 with reference to FIG. 1A.

[0129] At block 1002, the network device 120 may transmit, to a terminal device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, and the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reportedwith priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority. At block 1004, the network device 120 may receive, from the terminal device, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

[0130] In some example embodiments, the first set of one or more applicable AI / ML functionalities and the second set of one or more applicable AI / ML functionalities are defined based on a list of AI / ML functionalities provided by the network device to the terminal device to assess applicability or non-applicability.

[0131] In some example embodiments, the first message further indicates that the first set of one or more applicable AI / ML functionalities are to be reported using (i) a first radio resource control (RRC) reconfiguration complete message or (ii) a first user equipment (UE) assistance information (UAI) message to be transmitted upon receiving the first message.

[0132] In some example embodiments, the network device may receive the second message by receiving a first RRC reconfiguration complete message including the at least one ID of at least one applicable AI / ML functionality which is among the first set of one or more applicable AI / ML functionalities.

[0133] In some example embodiments, the first RRC reconfiguration complete message includes a container which includes UAI, wherein the UAI includes the at least one ID of the at least one applicable AI / ML functionality.

[0134] In some example embodiments, the UAI further includes an indication that the terminal device is to transmit further applicability information for at least one further applicable AI / ML functionality. In some example embodiments, the network device may receive the second message by receiving a first UAI message including the at least one ID of at least one applicable AI / ML functionality which is among the first set of one or more applicable AI / ML functionalities.

[0135] In some example embodiments, the first UAI message is received immediately after transmitting the first message. In some example embodiments, the first UAI message includes an indication that the RRC reconfiguration complete message is to be transmitted after the first UAI message; the first UAI message includes the RRC reconfiguration complete message; or the first UAI message includes an indication that the RRC reconfiguration complete message is not to be transmitted.

[0136] In some example embodiments, the network device may transmit, to the terminal device, first configuration information for configuring the terminal device to switch to an applicable AI / ML functionality after receiving the first message, in the case that the applicable AI / ML functionality is an only applicable AI / ML functionality.

[0137] In some example embodiments, the network device may transmit, to the terminal device, second configuration information for configuring the terminal device to indicate, through an empty container, that there is no applicable functionality to be reported with priority. In some example embodiments, the empty container is included in a first RRC reconfiguration complete message or a first UAI message to be transmitted upon receiving the first message.

[0138] In some example embodiments, the network device may receive the second message by receiving a second UAI message or a second RRC reconfiguration complete message including the at least one ID of the at least one applicable AI / ML functionality which is among the second set of one or more applicable AI / ML functionalities.

[0139] In some example embodiments, the first message is an RRC reconfiguration message; or the second message is an RRC reconfiguration complete message or an UAI message.

[0140] In some embodiments, an apparatus capable of performing any of the method 900 (for example, the terminal device 110) may comprise means for performing the respective steps of the method 900. The means may be implemented in any suitable form. For example, the means may be implemented in a circuitry or software module.

[0141] In some embodiments, the apparatus comprises means for receiving, from a network device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority. The apparatus comprises means for transmitting, to the network device, based on the first message, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

[0142] In some embodiments, the first set of one or more applicable AI / ML functionalities and the second set of one or more applicable AI / ML functionalities are defined based on a list of AI / ML functionalities provided by the network device to the terminal device to assess applicability or non-applicability.

[0143] In some further embodiments, the first message further indicates that the first set of one or more applicable AI / ML functionalities are to be reported using (i) a first radio resource control (RRC) reconfiguration complete message or (ii) a first user equipment (UE) assistance information (UAI) message to be transmitted upon receiving the first message.

[0144] In some example embodiments, the means for transmitting the second message comprise means for based on determining that the at least one applicable AI / ML functionality is among the first set of one or more applicable AI / ML functionalities, transmitting a first RRC reconfiguration complete message including the at least one ID of at least one applicable AI / ML functionality.

[0145] In some example embodiments, the first RRC reconfiguration complete message includes a container which includes UAI, and the UAI includes the at least one ID of the at least one applicable AI / ML functionality. In some example embodiments, the UAI further includes an indication that the terminal device is to transmit further applicability information for at least one further applicable AI / ML functionality.

[0146] In some other example embodiments, the means for transmitting the second message comprise means for based on determining that the at least one applicable AI / ML functionality is among the first set of one or more applicable AI / ML functionalities, transmitting a first UAI message including the at least one ID of at least one applicable AI / ML functionality.

[0147] In some other example embodiments, the first UAI message is transmitted immediately upon receiving the first message. In some other example embodiments, the first UAI message includes an indication that the RRC reconfiguration complete message is to be transmitted after the first UAI message; the first UAI message includes the RRC reconfiguration complete message; or the first UAI message includes an indication that the RRC reconfiguration complete message is not to be transmitted.

[0148] In some example embodiments, the apparatus comprise means for receiving, from the network device, first configuration information for configuring the terminal device to switch to an applicable AI / ML functionality after receiving the first message, based on determining that the applicable AI / ML functionality is an only applicable AI / ML functionality.

[0149] In some example embodiments, the apparatus comprise means for receiving, from the network device, second configuration information for configuring the terminal device to indicate, through an empty container, that there is no applicable functionality to be reported with priority. In some example embodiments, the empty container is included in a first RRC reconfiguration complete message or a first UAI message to be transmitted upon receiving the first message.

[0150] In some example embodiments, the means for transmitting the second message comprise means for based on determining that the at least one applicable AI / ML functionality is among the second set of one or more applicable AI / ML functionalities, transmitting a second UAI message or a second RRC reconfiguration complete message including the at least one ID of the at least one applicable AI / ML functionality.

[0151] In some example embodiments, the apparatus comprises means for, based on receiving the first message indicating the first set of one or more applicable AI / ML functionalities to be reported with priority, performing a priority check on the first set of one or more applicable AI / ML functionalities.

[0152] In some example embodiments, the apparatus comprises means for, based on transmitting, to the network device, the second message including an identity (ID) of an applicable AI / ML functionality reported with priority, starting applying the applicable AI / ML functionality. In some further embodiments, the first message is an RRC reconfiguration message; or the second message is an RRC reconfiguration complete message or an UAI message.

[0153] In some embodiments, the apparatus further comprises means for performing other steps in some embodiments of the method 900. In some embodiments, the means comprises at least one processor and at least one memory including computer program code, the at least one memory and computer program code configured to, with the at least one processor, cause the performance of the apparatus.

[0154] In some embodiments, an apparatus capable of performing any of the method 1000 (for example, the network device 120) may comprise means for performing the respective steps of the method 1000. The means may be implemented in any suitable form. For example, the means may be implemented in a circuitry or software module.

[0155] In some embodiments, the apparatus comprises means for transmitting, to a terminal device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, and the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority. In some embodiments, the apparatus comprises means for receiving, from the terminal device, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

[0156] In some example embodiments, the first set of one or more applicable AI / ML functionalities and the second set of one or more applicable AI / ML functionalities are defined based on a list of AI / ML functionalities provided by the network device to the terminal device to assess applicability or non-applicability.

[0157] In some example embodiments, the first message further indicates that the first set of one or more applicable AI / ML functionalities are to be reported using (i) a first radio resource control (RRC) reconfiguration complete message or (ii) a first user equipment (UE) assistance information (UAI) message to be transmitted upon receiving the first message.

[0158] In some example embodiments, the means for receiving the second message comprises means for receiving a first RRC reconfiguration complete message including the at least one ID of at least one applicable AI / ML functionality which is among the first set of one or more applicable AI / ML functionalities.

[0159] In some example embodiments, the first RRC reconfiguration complete message includes a container which includes UAI, and the UAI includes the at least one ID of the at least one applicable AI / ML functionality.

[0160] In some example embodiments, the UAI further includes an indication that the terminal device is to transmit further applicability information for at least one further applicable AI / ML functionality. In some example embodiments, the means for receiving the second message comprises means for receiving a first UAI message including the at least one ID of at least one applicable AI / ML functionality which is among the first set of one or more applicable AI / ML functionalities.

[0161] In some example embodiments, the first UAI message is received immediately after transmitting the first message. In some example embodiments, the first UAI message includes an indication that the RRC reconfiguration complete message is to be transmitted after the first UAI message; the first UAI message includes the RRC reconfiguration complete message; or the first UAI message includes an indication that the RRC reconfiguration complete message is not to be transmitted.

[0162] In some example embodiments, the apparatus further comprises means for transmitting, to the terminal device, first configuration information for configuring the terminal device to switch to an applicable AI / ML functionality after receiving the first message, in the case that the applicable AI / ML functionality is an only applicable AI / ML functionality.

[0163] In some example embodiments, the apparatus further comprises means for transmitting, to the terminal device, second configuration information for configuring the terminal device to indicate, through anempty container, that there is no applicable functionality to be reported with priority. In some example embodiments, the empty container is included in a first RRC reconfiguration complete message or a first U Al message to be transmitted upon receiving the first message.

[0164] In some example embodiments, the means for receiving the second message comprises means for receiving a second UAI message or a second RRC reconfiguration complete message including the at least one ID of the at least one applicable AI / ML functionality which is among the second set of one or more applicable AI / ML functionalities.

[0165] In some example embodiments, the first message is an RRC reconfiguration message; or the second message is an RRC reconfiguration complete message or an UAI message.

[0166] In some embodiments, the apparatus further comprises means for performing other steps in some embodiments of the method 1000. In some embodiments, the means comprises at least one processor and at least one memory including computer program code, the at least one memory and computer program code configured to, with the at least one processor, cause the performance of the apparatus.

[0167] FIG. 11 illustrates simplified block diagram of a device 1100 that is suitable for implementing some example embodiments of the present disclosure. The device 1100 may be provided to implement a communication device, for example, the terminal device 110 and the network device 120 as shown in FIG. 1A. As shown, the device 1100 includes one or more processors 1110, one or more memories 1120 coupled to the processor 1110, and one or more communication modules 1140 coupled to the processor 1110.

[0168] The communication module 1140 is for bidirectional communications. The communication module 1140 has at least one antenna to facilitate communication. The communication interface may represent any interface that is necessary for communication with other network elements.

[0169] The processor 1110 may be of any type suitable to the local technical network and may include one or more of the following: general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and processors based on multicore processor architecture, as non-limiting examples. The device 1100 may have multiple processors, such as an application specific integrated circuit chip that is slaved in time to a clock which synchronizes the main processor.

[0170] The memory 1120 may include one or more non-volatile memories and one or more volatile memories. Examples of the non-volatile memories include, but are not limited to, a Read Only Memory (ROM) 1124, an electrically programmable read only memory (EPROM), a flash memory, a hard disk, a compact disc (CD), a digital video disk (DVD), and other magnetic storage and / or optical storage. Examples of the volatile memories include, but are not limited to, a random access memory (RAM) 1122 and other volatile memories that will not last in the power-down duration.

[0171] A computer program 1130 includes computer executable instructions that are executed by the associated processor 1110. The program 1130 may be stored in the ROM 1124. The processor 1110 may perform any suitable actions and processing by loading the program 1130 into the RAM 1122.

[0172] The embodiments of the present disclosure may be implemented by means of the program 1130 so that the device 1100 may perform any process of the disclosure as discussed with reference to FIG. 2. The embodiments of the present disclosure may also be implemented by hardware or by a combination of software and hardware.

[0173] In some example embodiments, the program 1130 may be tangibly contained in a computer readable medium which may be included in the device 1100 (such as in the memory 1120) or other storage devices that are accessible by the device 1100. The device 1100 may load the program 1130 from the computer readable medium to the RAM 1122 for execution. The computer readable medium may include any types of tangible non-volatile storage, such as ROM, EPROM, a flash memory, a hard disk, CD, DVD, and the like.

[0174] FIG. 12 illustrates a block diagram of an example of a computer readable medium 1200 in accordance with some example embodiments of the present disclosure. The computer readable medium 1200 has the program 1130 stored thereon. It is noted that although the computer readable medium 1200 is depicted in form of CD or DVD in FIG. 12, the computer readable medium 1200 may be in any other form suitable for carry or hold the program 1130.

[0175] Generally, various embodiments of the present disclosure may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. Some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device. While various aspects of embodiments of the present disclosure are illustrated and described as block diagrams, flowcharts, or using some other pictorial representations, it is to be understood that the block, apparatus, system, technique or method described herein may be implemented in, as non-limiting examples, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof.

[0176] The present disclosure also provides at least one computer program product tangibly stored on a non-transitory computer readable storage medium. The computer program product includes computerexecutable instructions, such as those included in program modules, being executed in a device on a target real or virtual processor, to carry out the method 500 or 600 as described above with reference to FIG. 5 or 6. Generally, program modules include routines, programs, libraries, objects, classes, components, data structures, or the like that perform particular tasks or implement particular abstract data types. The functionality of the program modules may be combined or split between program modules as desired in various embodiments. Machine-executable instructions for program modules may be executed within a local or distributed device. In a distributed device, program modules may be located in both local and remote storage media.

[0177] Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may execute entirely on a machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

[0178] In the context of the present disclosure, the computer program codes or related data may be carried by any suitable carrier to enable the device, apparatus or processor to perform various processes and operations as described above. Examples of the carrier include a signal, computer readable medium, and the like.

[0179] The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable medium may include but not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the computer readable storage medium would include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. The term “non- transitory,” as used herein, is a limitation of the medium itself (i.e., tangible, not a signal) as opposed to a limitation on data storage persistency (e.g., RAM vs. ROM).

[0180] Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are contained in the above discussions, these should not be construed as limitations on the scope of the present disclosure, but rather as descriptions of features that may be specific to particular embodiments. Certain features that are described in the context of separate embodiments may also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment may also be implemented in multiple embodiments separately or in any suitable subcombination.

[0181] Although the present disclosure has been described in languages specific to structural features and / or methodological acts, it is to be understood that the present disclosure defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims

WHAT IS CLAIMED IS:1 . A terminal device comprising: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the terminal device at least to: receive, from a network device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, wherein the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority; and transmit, to the network device, based on the first message, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

2. The terminal device of claim 1 , wherein the first set of one or more applicable AI / ML functionalities and the second set of one or more applicable AI / ML functionalities are defined based on a list of AI / ML functionalities provided by the network device to the terminal device to assess applicability or nonapplicability.

3. The terminal device of claim 1 or 2, wherein the first message further indicates that the first set of one or more applicable AI / ML functionalities are to be reported using (i) a first radio resource control (RRC) reconfiguration complete message or (ii) a first user equipment (UE) assistance information (UAI) message to be transmitted upon receiving the first message.

4. The terminal device of any of claims 1 -3, wherein the terminal device is caused to transmit the second message by: based on determining that the at least one applicable AI / ML functionality is among the first set of one or more applicable AI / ML functionalities, transmitting a first RRC reconfiguration complete message including the at least one ID of at least one applicable AI / ML functionality.

5. The terminal device of claim 4, wherein the first RRC reconfiguration complete message includes a container which includes UAI, wherein the UAI includes the at least one ID of the at least one applicable AI / ML functionality.

6. The terminal device of claim 5, wherein the UAI further includes an indication that the terminal device is to transmit further applicability information for at least one further applicable AI / ML functionality.

7. The terminal device of any of claims 1 -3, wherein the terminal device is caused to transmit the second message by: based on determining that the at least one applicable AI / ML functionality is among the first set of one or more applicable AI / ML functionalities, transmitting a first UAI message including the at least one ID of at least one applicable AI / ML functionality.

8. The terminal device of claim 7, wherein the first UAI message is transmitted immediately upon receiving the first message.

9. The terminal device of claim 8, wherein: the first UAI message includes an indication that the RRC reconfiguration complete message is to be transmitted after the first UAI message; the first UAI message includes the RRC reconfiguration complete message; or the first UAI message includes an indication that the RRC reconfiguration complete message is not to be transmitted.

10. The terminal device of any of claims 1 -9, wherein the terminal device is further caused to: receive, from the network device, first configuration information for configuring the terminal device to switch to an applicable AI / ML functionality after receiving the first message, based on determining that the applicable AI / ML functionality is an only applicable AI / ML functionality.11 . The terminal device of any of claims 1-10, wherein the terminal device is further caused to: receive, from the network device, second configuration information for configuring the terminal device to indicate, through an empty container, that there is no applicable functionality to be reported with priority.

12. The terminal device of claim 11 , wherein the empty container is included in a first RRC reconfiguration complete message or a first UAI message to be transmitted upon receiving the first message.

13. The terminal device of any of claims 1-12, wherein the terminal device is caused to transmit the second message by: based on determining that the at least one applicable AI / ML functionality is among the second set of one or more applicable AI / ML functionalities, transmitting a second UAI message or a second RRC reconfiguration complete message including the at least one ID of the at least one applicable AI / ML functionality.

14. The terminal device of any of claims 1-13, wherein the terminal device is further caused to: based on receiving the first message indicating the first set of one or more applicable AI / ML functionalities to be reported with priority, perform a priority check on the first set of one or more applicable AI / ML functionalities.

15. The terminal device of claim 14, wherein the terminal device is further caused to: based on transmitting, to the network device, the second message including an identity (ID) of an applicable AI / ML functionality reported with priority, start applying the applicable AI / ML functionality.

16. The terminal device of any of claims 1-15, wherein at least one of the following: the first message is an RRC reconfiguration message; or the second message is an RRC reconfiguration complete message or an UAI message.

17. A network device comprising: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the network device at least to: transmit, to a terminal device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, wherein the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority; and receive, from the terminal device, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

18. The network device of claim 17, wherein the first set of one or more applicable AI / ML functionalities and the second set of one or more applicable AI / ML functionalities are defined based on a list of AI / ML functionalities provided by the network device to the terminal device to assess applicability or nonapplicability.

19. The network device of claim 17 or 18, wherein the first message further indicates that the first set of one or more applicable AI / ML functionalities are to be reported using (i) a first radio resource control (RRC) reconfiguration complete message or (ii) a first user equipment (UE) assistance information (UAI) message to be transmitted upon receiving the first message.

20. The network device of any of claims 17-19, wherein the network device is caused to receive the second message by: receiving a first RRC reconfiguration complete message including the at least one ID of at least one applicable AI / ML functionality which is among the first set of one or more applicable AI / ML functionalities.

21. The network device of claim 20, wherein the first RRC reconfiguration complete message includes a container which includes UAI, wherein the UAI includes the at least one ID of the at least one applicable AI / ML functionality.

22. The network device of claim 21 , wherein the UAI further includes an indication that the terminal device is to transmit further applicability information for at least one further applicable AI / ML functionality.

23. The network device of any of claims 17-19, wherein the network device is caused to receive the second message by: receiving a first UAI message including the at least one ID of at least one applicable AI / ML functionality which is among the first set of one or more applicable AI / ML functionalities.

24. The network device of claim 23, wherein the first UAI message is received immediately after transmitting the first message.

25. The network device of claim 24, wherein: the first UAI message includes an indication that the RRC reconfiguration complete message is to be transmitted after the first UAI message; the first UAI message includes the RRC reconfiguration complete message; or the first UAI message includes an indication that the RRC reconfiguration complete message is not to be transmitted.

26. The network device of any of claims 17-25, wherein the network device is further caused to: transmit, to the terminal device, first configuration information for configuring the terminal device to switch to an applicable AI / ML functionality after receiving the first message, in the case that the applicable AI / ML functionality is an only applicable AI / ML functionality.

27. The network device of any of claims 17-26, wherein the network device is further caused to: transmit, to the terminal device, second configuration information for configuring the terminal device to indicate, through an empty container, that there is no applicable functionality to be reported with priority.

28. The network device of claim 27, wherein the empty container is included in a first RRC reconfiguration complete message or a first U Al message to be transmitted upon receiving the first message.

29. The network device of any of claims 17-28, wherein the network device is caused to receive the second message by: receiving a second UAI message or a second RRC reconfiguration complete message including the at least one ID of the at least one applicable AI / ML functionality which is among the second set of one or more applicable AI / ML functionalities.

30. The network device of any of claims 17-29, wherein at least one of the following: the first message is an RRC reconfiguration message; or the second message is an RRC reconfiguration complete message or an UAI message.

31. A method comprising: receiving, from a network device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, wherein the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority; and transmitting, to the network device, based on the first message, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

32. A method comprising: transmitting, to a terminal device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, wherein the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority; and receiving, from the terminal device, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

33. An apparatus comprising: means for receiving, from a network device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, wherein the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority; andmeans for transmitting, to the network device, based on the first message, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

34. An apparatus comprising: means for transmitting, to a terminal device, a first message for configuring applicable artificial intelligence (Al) / machine learning (ML) functionality reporting, wherein the first message indicates at least one of (i) a first set of one or more applicable AI / ML functionalities to be reported with priority or (ii) a second set of one or more applicable AI / ML functionalities to be reported without priority; and means for receiving, from the terminal device, a second message including at least one identity (ID) of at least one applicable AI / ML functionality.

35. A computer readable medium comprising program instructions for causing an apparatus to perform at least the method of claim 31 or 32.

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