WO2025091985A1

WO2025091985A1 - Support ai task in rrc_inactive state

Info

Publication number: WO2025091985A1
Application number: PCT/CN2024/102396
Authority: WO
Inventors: Mingzeng Dai; Congchi ZHANG; Lianhai WU
Original assignee: Lenovo Beijing Ltd
Current assignee: Lenovo Beijing Ltd
Priority date: 2024-06-28
Filing date: 2024-06-28
Publication date: 2025-05-08
Anticipated expiration: 2026-12-28

Abstract

Various aspects of the present disclosure relate to support of at least one AI task associated with an RRC_INACTIVE state. In one aspect, a UE receives configuration information for at least one AI task associated with an RRC_INACTIVE state from a network entity. In turn, the UE performs an operation related to the at least one AI task based on the configuration information.

Description

SUPPORT AI TASK IN RRC_INACTIVE STATE

TECHNICAL FIELD

The present disclosure relates to wireless communications, and more specifically to user equipment (UE) , network entity and methods supporting at least one artificial intelligence (AI) task in a radio resource control (RRC) _INACTIVE state.

BACKGROUND

A wireless communications system may include one or multiple network communication devices, such as base stations, which may be otherwise known as an eNodeB (eNB) , a next-generation NodeB (gNB) , or other suitable terminology. Each network communication devices, such as a base station may support wireless communications for one or multiple user communication devices, which may be otherwise known as user equipment (UE) , or other suitable terminology. The wireless communications system may support wireless communications with one or multiple user communication devices by utilizing resources of the wireless communication system (e.g., time resources (e.g., symbols, slots, subframes, frames, or the like) or frequency resources (e.g., subcarriers, carriers) . Additionally, the wireless communications system may support wireless communications across various radio access technologies including third generation (3G) radio access technology, fourth generation (4G) radio access technology, fifth generation (5G) radio access technology, among other suitable radio access technologies beyond 5G (e.g., sixth generation (6G) ) .

The 5G system supports a protocol data unit (PDU) connectivity service, i.e., a service that provides exchange of PDUs between a UE and a data network identified by a data network name (DNN) . The PDU connectivity service is supported via PDU sessions that are established upon request from the UE. A PDU session is terminated or anchored at a user plane function (UPF) . In case of mobility, the UE moves from a source gNB to a target gNB, path switch procedure is performed to switch downlink (DL) data transmission path from one path between the UPF and the source gNB to another path between the UPF and the target gNB.

A concept of 6G AI-as-a-Service (AIaaS) is discussing to support 6G native AI: the new 6G mobile network provides ubiquitous intelligent services. 6G AIaaS is to build distributed, efficient, energy-saving and secure AI services (including AI model training, reasoning, deployment, etc. ) and open ecology through the connection, computing, data, model and other resources and functions of the network (including 6G core network, 6G wireless access network and 6G terminal) . AIaaS is also called as network AI service. AI service refers to the provision of AI technology, AI traffic or AI resource to the served party. Typical 6G AIaaS services include that 6G network provides users with large-scale distributed model training, inference, generation, optimization and other AI services. The service objects can be end users, third-party users, and network operation maintenance. An AI task is to enable a network AI service that will involve the coordination and deployment of computing power, connections, AI algorithms, and data among multiple devices.

SUMMARY

The present disclosure relates to UE, network entity and methods that support at least one AI task in an RRC_INACTIVE state. With the UE, network entity and methods, an operation related to the at least one AI task may be performed based on configuration information for at least one AI task associated with the RRC_INACTIVE state.

Some implementations of a UE described herein may include a processor and a transceiver coupled to the processor, wherein the processor is configured to: receive configuration information for at least one AI task associated with an RRC_INACTIVE state via the transceiver from a network entity; and perform an operation related to the at least one AI task based on the configuration information.

In some implementations, the configuration information comprises at least one of the following: an indication indicating whether an AI task among the at least one AI task is to be continued or to be performed in the RRC_INACTIVE state, at least one condition for starting or stopping the AI task in the RRC_INACTIVE state, at least one condition for resuming or suspending the AI task in the RRC_INACTIVE state, a valid area of the AI task, information about a further network entity initiating the AI task, a priority of the AI task, or valid time of the AI task.

In some implementations, the at least one condition for starting or stopping the AI task in the RRC_INACTIVE state indicates at least one of the following: starting the AI task based on determining that measured quality of a serving cell or a serving beam is equal to or higher than a first threshold; or stopping the AI task based on determining that the measured quality of the serving cell or the serving beam is lower than the first threshold.

In some implementations, the at least one condition for resuming or suspending the AI task in the RRC_INACTIVE state indicates at least one of the following: resuming the AI task based on determining that measured quality of a serving cell or a serving beam is equal to or higher than a first threshold; or suspending the AI task based on determining that the measured quality of the serving cell or the serving beam is lower than the first threshold.

In some implementations, the at least one condition for starting or stopping the AI task in the RRC_INACTIVE state indicates at least one of the following: starting the AI task based on determining that a computing resource or power of the UE is equal to or higher than a second threshold; or stopping the AI task based on determining that the computing resource or power of the UE is lower than the second threshold.

In some implementations, the at least one condition for resuming or suspending the AI task in the RRC_INACTIVE state indicates at least one of the following: resuming the AI task based on determining that a computing resource or power of the UE is equal to or higher than a second threshold; or suspending the AI task based on determining that the computing resource or power of the UE is lower than the second threshold.

In some implementations, the at least one condition for starting or stopping the AI task in the RRC_INACTIVE state indicates at least one of the following: starting the AI task based on determining that a moving speed of the UE is lower than a third threshold; or stopping the AI task based on determining that the moving speed of the UE is equal to or higher than the third threshold.

In some implementations, the at least one condition for resuming or suspending the AI task in the RRC_INACTIVE state indicates at least one of the following: resuming the AI task based on determining that a moving speed of the UE is lower than a third threshold; or suspending the AI task based on determining that the moving speed of the UE is equal to or higher than the third threshold.

In some implementations, the valid area of the AI task is indicated by one of the following: a list of cells, a radio access network (RAN) notification area, or an area in which the AI task should not be performed.

In some implementations, the at least one AI task comprises multiple AI tasks. In such implementations, the processor is configured to perform the operation related to the at least one AI task by: performing the operation related to the at least one AI task in a decreasing order of at least one priority of the at least one AI task.

In some implementations, the processor is configured to receive the configuration information for the at least one AI task by: receiving, via the transceiver from the network entity, an RRC Release message comprising the configuration information.

In some implementations, the processor is configured to perform the operation related to the at least one AI task by: triggering an RRC state transition from the RRC_INACTIVE state to an RRC_CONNECTED state based on determining one of the following: an AI task among the at least one AI task becomes applicable or available, the AI task is complete, valid time of the AI task has been elapsed, a timer defining the valid time of the AI task expires, or the UE moves to a cell that is not in a valid area of the AI task.

In some implementations, the processor is configured to perform the operation related to the at least one AI task by: receiving, via the transceiver from the network entity or a further network entity, at least one access control parameter for an access category related to the at least one AI task; and performing, based on the at least one access control parameter, access barring check for the access category related to the at least one AI task.

In some implementations, the at least one access control parameter for the access category related to the at least one AI task comprises at least one of the following: access barring factor which represents a probability that an access attempt would be allowed during the access barring check, access barring time which indicates average time before a new access attempt is to be performed after the access attempt was barred at the access barring check for the access category, or access baring for access identity which indicates whether the access attempt is allowed for each access identity.

In some implementations, the processor is configured to perform the access barring check by: drawing a random number uniformly distributed in a range of zero to one; determining whether the random number is lower than a value indicated by an access barring factor for the access category among the at least one access control parameter; based on determining that the random number is lower than a value indicated by the access barring factor, considering access attempt as allowed; and based on determining that the random number is equal to or higher than the value indicated by the access barring factor, considering the access attempt as barred.

In some implementations, the access category related to the at least one AI task comprises a first access category which is associated with a first type of access attempt, wherein the first type of access attempt is related to one of the following: signaling transmission for the at least one AI task originated from a non-access stratum (NAS) or dedicated AI/machine learning (ML) layer of the UE, or data transmission for the at least one AI task originated from the NAS or dedicated AI/ML layer of the UE.

In some implementations, the first access category is associated with one of the following: an AI task among the at least one AI task becomes applicable or available, the AI task is complete, valid time of the AI task has been elapsed, or a timer defining the valid time of the AI task expires.

In some implementations, the access category related to the at least one AI task comprises a second access category which is associated with a second type of access attempt, wherein the second type of access attempt is related to the following: data transmission for the at least one AI task originated from a non-access stratum (NAS) or dedicated AI/machine learning (ML) layer of the UE.

In some implementations, the second access category is associated with results of the at least one AI task are to be transmitted.

In some implementations, the processor is configured to perform the operation related to the at least one AI task by: transmitting, via the transceiver to the network entity, a cause for an RRC state transition from the RRC_INACTIVE state to an RRC_CONNECTED state, wherein the cause is related to the at least one AI task.

In some implementations, the processor is configured to transmit the cause for the RRC state transition in one of the following: an RRC Resume Request message, an RRC Resume Complete message, or a UE Assistance Information message.

In some implementations, the cause indicates one of the following: an AI task among the at least one AI task becomes applicable or available, the AI task is complete, valid time of the AI task has been elapsed, a timer defining the valid time of the AI task expires, the RRC state transition is initiated by AI or ML purpose, the RRC state transition is initiated by mobile originated AI or ML purpose, or the RRC state transition is initiated by mobile terminated AI or ML purpose.

In some implementations, the processor is configured to perform the operation related to the at least one AI task by: performing a cell reselection procedure to reselect a first cell in a valid area of an AI task among the at least one AI task.

In some implementations, the processor is configured to perform the cell reselection procedure by: starting measurements for reselection of the first cell in the valid area of the AI task based on at least one threshold.

In some implementations, the at least one threshold comprises at least one of the following: a first threshold for receiving level, or a second threshold for quality level.

In some implementations, the processor is configured to perform the cell reselection procedure by: determining at least one cell in the valid area of the AI task and a serving cell of the UE as candidate cells for ranking of cells, wherein the at least one cell in the valid area of the AI task comprises the first cell.

In some implementations, the processor is configured to perform the cell reselection procedure by: updating an R value for each of the at least one cell in the valid area of the AI task with an offset applied to the at least one cell.

In some implementations, the processor is configured to perform the operation related to the at least one AI task by: based on determining that the UE moves to a cell that is out of a valid area of an AI task among the at least one AI task, performing one of the following: suspending the AI task and resuming the AI task when moving back to a cell in the valid area of the AI task; or releasing the AI task.

Some implementations of a network entity described herein may include a processor and a transceiver coupled to the processor, wherein the processor is configured to: determine configuration information for at least one AI task associated with an RRC_INACTIVE state; and transmit the configuration information via the transceiver to a UE.

In some implementations, the valid area of the AI task is indicated by one of the following: a list of cells, a RAN notification area, or an area in which the AI task should not be performed.

In some implementations, the processor is configured to transmit the configuration information for the at least one AI task by: transmitting, via the transceiver to the UE, an RRC Release message comprising the configuration information.

In some implementations, the processor is further configured to: transmit, via the transceiver to the UE, at least one access control parameter for an access category related to the at least one AI task.

In some implementations, the access category related to the at least one AI task comprises a first access category which is associated with a first type of access attempt, wherein the first type of access attempt is related to one of the following: signaling transmission for the at least one AI task originated from a NAS or dedicated AI/ML layer of the UE, or data transmission for the at least one AI task originated from the NAS or dedicated AI/ML layer of the UE.

In some implementations, the access category related to the at least one AI task comprises a second access category which is associated with a second type of access attempt, wherein the second type of access attempt is related to the following: data transmission for the at least one AI task originated from a NAS or dedicated AI/ML layer of the UE.

In some implementations, the processor is further configured to: receive, via the transceiver from the UE, a cause for an RRC state transition from the RRC_INACTIVE state to an RRC_CONNECTED state, wherein the cause is related to the at least one AI task.

In some implementations, the processor is configured to receive the cause for the RRC state transition in one of the following: an RRC Resume Request message, an RRC Resume Complete message, or a UE Assistance Information message.

In some implementations, the processor is further configured to: transmit, via the transceiver to the UE, on at least one threshold for starting measurements for reselection of a first cell in a valid area of an AI task based on at least one threshold.

Some implementations of a method described herein may include: receiving configuration information for at least one AI task associated with an RRC_INACTIVE state from a network entity; and performing an operation related to the at least one AI task based on the configuration information.

Some implementations of a method described herein may include: determining configuration information for at least one AI task associated with an RRC_INACTIVE state; and transmitting the configuration information via the transceiver to a UE.

Some implementations of a processor described herein may include at least one memory and a controller coupled with the at least one memory and configured to cause the controller to: receive configuration information for at least one AI task associated with an RRC_INACTIVE state via the transceiver from a network entity; and perform an operation related to the at least one AI task based on the configuration information.

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

Fig. 1 illustrates an example of a wireless communications system that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure;

Fig. 2 illustrates a signaling diagram illustrating an example process that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure;

Fig. 3 illustrates a signaling diagram illustrating an example process that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure;

Fig. 4 illustrates a signaling diagram illustrating an example process that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure;

Fig. 5 illustrates a flowchart of a method for access barring check in accordance with aspects of the present disclosure;

Fig. 6 illustrates an example of a device that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure;

Fig. 7 illustrates an example of a processor that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure; and

Figs. 8 and 9 illustrate a flowchart of a method that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure.

DETAILED DESCRIPTION

Principles of the present disclosure will now be described with reference to some 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 may be implemented in various manners other than the ones described below.

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.

References in the present disclosure to “one embodiment, ” “an example embodiment, ” “an embodiment, ” “some embodiments, ” and the like indicate that the embodiment (s) 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 do not necessarily refer to the same embodiment (s) . Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted 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.

It shall be understood that although the terms “first” and “second” or the like 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 element. For example, a first element could also be termed as a second element, and similarly, a second element could also be termed as a first element, without departing from the scope of embodiments. As used herein, the term “and/or” includes any and all combinations of one or more of the listed terms.

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 described above, an AI task is to enable a network AI service that will involve the coordination and deployment of computing power, connections, AI algorithms, and data among multiple devices. So far supporting AI tasks associated with an RRC_INACTIVE state has not been discussed. To support AI tasks associated with the RRC_INACTIVE state, there is a need to study how to configure at least one AI task to be performed in the RRC_INACTIVE state.

In view of the above, the present disclosure provides a solution that supports at least one AI task in an RRC_INACTIVE state. In this solution, a UE receives configuration information for at least one AI task associated with an RRC_INACTIVE state from a network entity. In turn, the UE performs an operation related to the at least one AI task based on the configuration information. With this solution, an operation related to the at least one AI task may be performed based on configuration information for at least one AI task associated with the RRC_INACTIVE state.

Aspects of the present disclosure are described in the context of a wireless communications system.

Fig. 1 illustrates an example of a wireless communications system 100 that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure. The wireless communications system 100 may include one at least one of network entities 102 (also referred to as network equipment (NE) ) , one or more terminal devices or UEs 104, a core network 106, and a packet data network 108. The wireless communications system 100 may support various radio access technologies. In some implementations, the wires communications system 100 may be a 6G network. In some implementations, the wireless communications system 100 may be a 4G network, such as an LTE network or an LTE-advanced (LTE-A) network. In some other implementations, the wireless communications system 100 may be a 5G network, such as an NR network. In other implementations, the wireless communications system 100 may be a combination of a 4G network and a 5G network, or other suitable radio access technology including institute of electrical and electronics engineers (IEEE) 802.11 (Wi-Fi) , IEEE 802.16 (WiMAX) , IEEE 802.20. The wireless communications system 100 may support radio access technologies beyond 5G. Additionally, the wireless communications system 100 may support technologies, such as time division multiple access (TDMA) , frequency division multiple access (FDMA) , or code division multiple access (CDMA) , etc.

The network entities 102 may be dispersed throughout a geographic region to form the wireless communications system 100. One or more of the network entities 102 described herein may be or include or may be referred to as a network node, a base station (BS) , a network element, a radio access network (RAN) node, a base transceiver station, an access point, a NodeB, an eNodeB (eNB) , a next-generation NodeB (gNB) , a base station that will be used in 6G, or other suitable terminology. A network entity 102 and a UE 104 may communicate via a communication link 110, which may be a wireless or wired connection. For example, a network entity 102 and a UE 104 may perform wireless communication (e.g., receive signaling, transmit signaling) over a Uu interface. The network entities 102 may be collectively referred to as network entities 102 or individually referred to as a network entity 102.

A network entity 102 may provide a geographic coverage area 112 for which the network entity 102 may support services (e.g., voice, video, packet data, messaging, broadcast, etc. ) for one or more UEs 104 within the geographic coverage area 112. For example, a network entity 102 and a UE 104 may support wireless communication of signals related to services (e.g., voice, video, packet data, messaging, broadcast, etc. ) according to one or multiple radio access technologies. In some implementations, a network entity 102 may be moveable, for example, a satellite associated with a non-terrestrial network. In some implementations, different geographic coverage areas 112 associated with the same or different radio access technologies may overlap, but the different geographic coverage areas 112 may be associated with different network entities 102. Information and signals described herein may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

The one or more UEs 104 may be dispersed throughout a geographic region of the wireless communications system 100. A UE 104 may include or may be referred to as a mobile device, a wireless device, a remote device, a remote unit, a handheld device, or a subscriber device, or some other suitable terminology. In some implementations, the UE 104 may be referred to as a unit, a station, a terminal, or a client, among other examples. Additionally, or alternatively, the UE 104 may be referred to as an internet-of-things (IoT) device, an internet-of-everything (IoE) device, or machine-type communication (MTC) device, among other examples. In some implementations, a UE 104 may be stationary in the wireless communications system 100. In some other implementations, a UE 104 may be mobile in the wireless communications system 100.

The one or more UEs 104 may be devices in different forms or having different capabilities. Some examples of UEs 104 are illustrated in Fig. 1. A UE 104 may be capable of communicating with various types of devices, such as the network entities 102, other UEs 104, or network equipment (e.g., the core network 106, the packet data network 108, a relay device, an integrated access and backhaul (IAB) node, or another network equipment) , as shown in Fig. 1. Additionally, or alternatively, a UE 104 may support communication with other network entities 102 or UEs 104, which may act as relays in the wireless communications system 100.

A UE 104 may also be able to support wireless communication directly with other UEs 104 over a communication link 114. For example, a UE 104 may support wireless communication directly with another UE 104 over a device-to-device (D2D) communication link. In some implementations, such as vehicle-to-vehicle (V2V) deployments, vehicle-to-everything (V2X) deployments, or cellular-V2X deployments, the communication link 114 may be referred to as a sidelink. For example, a UE 104 may support wireless communication directly with another UE 104 over a PC5 interface.

A network entity 102 may support communications with the core network 106, or with another network entity 102, or both. For example, a network entity 102 may interface with the core network 106 through one or more backhaul links 116 (e.g., via an S1, N2, N2, or another network interface) . The network entities 102 may communicate with each other over the backhaul links 116 (e.g., via an X2, Xn, or another network interface) . In some implementations, the network entities 102 may communicate with each other directly (e.g., between the network entities 102) . In some other implementations, the network entities 102 may communicate with each other or indirectly (e.g., via the core network 106) . In some implementations, one or more network entities 102 may include subcomponents, such as an access network entity, which may be an example of an access node controller (ANC) . An ANC may communicate with the one or more UEs 104 through one or more other access network transmission entities, which may be referred to as a radio heads, smart radio heads, or transmission-reception points (TRPs) .

In some implementations, a network entity 102 may be configured in a disaggregated architecture, which may be configured to utilize a protocol stack physically or logically distributed among two or more network entities 102, such as an integrated access backhaul (IAB) network, an open radio access network (O-RAN) (e.g., a network configuration sponsored by the O-RAN Alliance) , or a virtualized RAN (vRAN) (e.g., a cloud RAN (C-RAN) ) . For example, a network entity 102 may include one or more of a central unit (CU) , a distributed unit (DU) , a radio unit (RU) , a RAN intelligent controller (RIC) (e.g., a near-real time RIC (Near-RT RIC) , a non-real time RIC (Non-RT RIC) ) , a service management and orchestration (SMO) system, or any combination thereof.

An RU may also be referred to as a radio head, a smart radio head, a remote radio head (RRH) , a remote radio unit (RRU) , or a transmission reception point (TRP) . One or more components of the network entities 102 in a disaggregated RAN architecture may be co-located, or one or more components of the network entities 102 may be located in distributed locations (e.g., separate physical locations) . In some implementations, one or more network entities 102 of a disaggregated RAN architecture may be implemented as virtual units (e.g., a virtual CU (VCU) , a virtual DU (VDU) , a virtual RU (VRU) ) .

Split of functionality between a CU, a DU, and an RU may be flexible and may support different functionalities depending upon which functions (e.g., network layer functions, protocol layer functions, baseband functions, radio frequency functions, and any combinations thereof) are performed at a CU, a DU, or an RU. For example, a functional split of a protocol stack may be employed between a CU and a DU such that the CU may support one or more layers of the protocol stack and the DU may support one or more different layers of the protocol stack. In some implementations, the CU may host upper protocol layer (e.g., a layer 3 (L3) , a layer 2 (L2) ) functionality and signaling (e.g., radio resource control (RRC) , service data adaption protocol (SDAP) , packet data convergence protocol (PDCP) ) . The CU may be connected to one or more DUs or RUs, and the one or more DUs or RUs may host lower protocol layers, such as a layer 1 (L1) (e.g., physical (PHY) layer) or an L2 (e.g., radio link control (RLC) layer, medium access control (MAC) layer) functionality and signaling, and may each be at least partially controlled by the CU.

Additionally, or alternatively, a functional split of the protocol stack may be employed between a DU and an RU such that the DU may support one or more layers of the protocol stack and the RU may support one or more different layers of the protocol stack. The DU may support one or multiple different cells (e.g., via one or more RUs) . In some implementations, a functional split between a CU and a DU, or between a DU and an RU may be within a protocol layer (e.g., some functions for a protocol layer may be performed by one of a CU, a DU, or an RU, while other functions of the protocol layer are performed by a different one of the CU, the DU, or the RU) .

A CU may be functionally split further into CU control plane (CU-CP) and CU user plane (CU-UP) functions. A CU may be connected to one or more DUs via a midhaul communication link (e.g., F1, F1-c, F1-u) , and a DU may be connected to one or more RUs via a fronthaul communication link (e.g., open fronthaul (FH) interface) . In some implementations, a midhaul communication link or a fronthaul communication link may be implemented in accordance with an interface (e.g., a channel) between layers of a protocol stack supported by respective network entities 102 that are in communication via such communication links.

The core network 106 may support user authentication, access authorization, tracking, connectivity, and other access, routing, or mobility functions. The core network 106 may be an evolved packet core (EPC) , or a 5G core (5GC) , which may include a control plane entity that manages access and mobility (e.g., a mobility management entity (MME) , an access and mobility management functions (AMF) ) and a user plane entity that routes packets or interconnects to external networks (e.g., a serving gateway (S-GW) , a packet data network (PDN) gateway (P-GW) , or a user plane function (UPF) ) . In some implementations, the control plane entity may manage non-access stratum (NAS) functions, such as mobility, authentication, and bearer management (e.g., data bearers, signal bearers, etc. ) for the one or more UEs 104 served by the one or more network entities 102 associated with the core network 106.

The core network 106 may communicate with the packet data network 108 over one or more backhaul links 116 (e.g., via an S1, N2, N2, or another network interface) . The packet data network 108 may include an application server 118. In some implementations, one or more UEs 104 may communicate with the application server 118. A UE 104 may establish a session (e.g., a protocol data unit (PDU) session, or the like) with the core network 106 via a network entity 102. The core network 106 may route traffic (e.g., control information, data, and the like) between the UE 104 and the application server 118 using the established session (e.g., the established PDU session) . The PDU session may be an example of a logical connection between the UE 104 and the core network 106 (e.g., one or more network functions of the core network 106) .

In the wireless communications system 100, the network entities 102 and the UEs 104 may use resources of the wireless communications system 100 (e.g., time resources (e.g., symbols, slots, subframes, frames, or the like) or frequency resources (e.g., subcarriers, carriers) ) to perform various operations (e.g., wireless communications) . In some implementations, the network entities 102 and the UEs 104 may support different resource structures. For example, the network entities 102 and the UEs 104 may support different frame structures. In some implementations, such as in 4G, the network entities 102 and the UEs 104 may support a single frame structure. In some other implementations, such as in 5G and among other suitable radio access technologies, the network entities 102 and the UEs 104 may support various frame structures (i.e., multiple frame structures) . The network entities 102 and the UEs 104 may support various frame structures based on one or more numerologies.

One or more numerologies may be supported in the wireless communications system 100, and a numerology may include a subcarrier spacing and a cyclic prefix. A first numerology (e.g., μ=0) may be associated with a first subcarrier spacing (e.g., 15 kHz) and a normal cyclic prefix. In some implementations, the first numerology (e.g., μ=0) associated with the first subcarrier spacing (e.g., 15 kHz) may utilize one slot per subframe. A second numerology (e.g., μ=1) may be associated with a second subcarrier spacing (e.g., 30 kHz) and a normal cyclic prefix. A third numerology (e.g., μ=2) may be associated with a third subcarrier spacing (e.g., 60 kHz) and a normal cyclic prefix or an extended cyclic prefix. A fourth numerology (e.g., μ=3) may be associated with a fourth subcarrier spacing (e.g., 120 kHz) and a normal cyclic prefix. A fifth numerology (e.g., μ=4) may be associated with a fifth subcarrier spacing (e.g., 240 kHz) and a normal cyclic prefix.

A time interval of a resource (e.g., a communication resource) may be organized according to frames (also referred to as radio frames) . Each frame may have a duration, for example, a 10 millisecond (ms) duration. In some implementations, each frame may include multiple subframes. For example, each frame may include 10 subframes, and each subframe may have a duration, for example, a 1 ms duration. In some implementations, each frame may have the same duration. In some implementations, each subframe of a frame may have the same duration.

Additionally or alternatively, a time interval of a resource (e.g., a communication resource) may be organized according to slots. For example, a subframe may include a number (e.g., quantity) of slots. The number of slots in each subframe may also depend on the one or more numerologies supported in the wireless communications system 100. For instance, the first, second, third, fourth, and fifth numerologies (i.e., μ=0, μ=1, μ=2, μ=3, μ=4) associated with respective subcarrier spacings of 15 kHz, 30 kHz, 60 kHz, 120 kHz, and 240 kHz may utilize a single slot per subframe, two slots per subframe, four slots per subframe, eight slots per subframe, and 16 slots per subframe, respectively. Each slot may include a number (e.g., quantity) of symbols (e.g., OFDM symbols) . In some implementations, the number (e.g., quantity) of slots for a subframe may depend on a numerology. For a normal cyclic prefix, a slot may include 14 symbols. For an extended cyclic prefix (e.g., applicable for 60 kHz subcarrier spacing) , a slot may include 12 symbols. The relationship between the number of symbols per slot, the number of slots per subframe, and the number of slots per frame for a normal cyclic prefix and an extended cyclic prefix may depend on a numerology. It should be understood that reference to a first numerology (e.g., μ=0) associated with a first subcarrier spacing (e.g., 15 kHz) may be used interchangeably between subframes and slots.

In the wireless communications system 100, an electromagnetic (EM) spectrum may be split, based on frequency or wavelength, into various classes, frequency bands, frequency channels, etc. By way of example, the wireless communications system 100 may support one or multiple operating frequency bands, such as frequency range designations FR1 (410 MHz –7.125 GHz) , FR2 (24.25 GHz –52.6 GHz) , FR3 (7.125 GHz –24.25 GHz) , FR4 (52.6 GHz –114.25 GHz) , FR4a or FR4-1 (52.6 GHz –71 GHz) , and FR5 (114.25 GHz –300 GHz) . In some implementations, the network entities 102 and the UEs 104 may perform wireless communications over one or more of the operating frequency bands. In some implementations, FR1 may be used by the network entities 102 and the UEs 104, among other equipment or devices for cellular communications traffic (e.g., control information, data) . In some implementations, FR2 may be used by the network entities 102 and the UEs 104, among other equipment or devices for short-range, high data rate capabilities.

FR1 may be associated with one or multiple numerologies (e.g., at least three numerologies) . For example, FR1 may be associated with a first numerology (e.g., μ=0) , which includes 15 kHz subcarrier spacing; a second numerology (e.g., μ=1) , which includes 30 kHz subcarrier spacing; and a third numerology (e.g., μ=2) , which includes 60 kHz subcarrier spacing. FR2 may be associated with one or multiple numerologies (e.g., at least 2 numerologies) . For example, FR2 may be associated with a third numerology (e.g., μ=2) , which includes 60 kHz subcarrier spacing; and a fourth numerology (e.g., μ=3) , which includes 120 kHz subcarrier spacing.

Fig. 2 illustrates a signaling diagram illustrating an example process 200 that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure. The process 200 may involve the UE 104 and the network entity 102 in Fig. 1. For the purpose of discussion, the process 200 will be described with reference to Fig. 1.

As shown in Fig. 2, the network entity 102 determines 210 configuration information for at least one AI task associated with an RRC_INACTIVE state. Hereinafter, the configuration information for at least one AI task associated with the RRC_INACTIVE state is also referred to as AI task configuration information associated with the RRC_INACTIVE state for brevity.

In some implementations, an AI task may be one of the following types:

- data collection in RRC_INACTIVE: the UE 104 may perform data collection in RRC_INACTIVE, e.g., for an AI functionality or for training/inference for an AI task. For example, the UE 104 may collect L1 or L2 or L3 measurement results in RRC_INACTIVE state.

- AI/ML training in RRC_INACTIVE: the UE 104 may perform AI/ML training in RRC_INACTIVE state for an AI task or an AI functionality since AI/ML training does not need data transmission between UE 104 and the network entity 102.

- positioning: the UE 104 may perform UE-based positioning using a UE-sided AI/ML model in RRC_INACTIVE state. For example, the UE 104 in RRC_INACTVE state may collect more fingerprint information and use them to estimate or predict more accurate location information of the UE 104.

- sensing: the UE 104 may perform sensing function in RRC_INACTIVE state. For example, the UE 104 in RRC_INACTVE state may sense surrounding object and use an AI/ML model to predict the object.

Alternatively, in some implementations, an AI task may be only for AI/ML training or inference purpose or for data collection purpose.

In some implementations, an AI task is an AI/ML functionality which means that the AI/ML is used for a specific functionality, such as positioning, sensing, channel state information (CSI) prediction and so on.

In some implementations, the AI task configuration information associated with the RRC_INACTIVE state may comprise at least one identifier (ID) of the at least one AI task. An ID of an AI task may be used to uniquely identify the AI task.

In some implementations, the AI task configuration information associated with the RRC_INACTIVE state may comprise an indication indicating whether an AI task among the at least one AI task is to be continued or to be performed in the RRC_INACTIVE state.

Alternatively or additionally, in some implementations, the AI task configuration information associated with the RRC_INACTIVE state may comprise at least one condition for starting or stopping the AI task in the RRC_INACTIVE state.

In some implementations, the at least one condition for starting or stopping the AI task in the RRC_INACTIVE state may indicate at least one of the following: starting the AI task based on determining that measured quality of a serving cell or a serving beam is equal to or higher than a first threshold; or stopping the AI task based on determining that the measured quality of the serving cell or the serving beam is lower than the first threshold. For example, the measured quality of the serving cell or the serving beam may be reference signal received power (RSRP) of the serving cell or the serving beam. For example, if the RSRP of the serving cell or the serving beam is equal to or higher than the first threshold, the UE 104 may start data collection. If the RSRP of the serving cell or the serving beam is lower than the first threshold, the UE 104 may stop the data collection.

In some implementations, the at least one condition for starting or stopping the AI task in the RRC_INACTIVE state may indicate at least one of the following: starting the AI task based on determining that a computing resource or power of the UE is equal to or higher than a second threshold; or stopping the AI task based on determining that the computing resource or power of the UE is lower than the second threshold.

In some implementations, the at least one condition for starting or stopping the AI task in the RRC_INACTIVE state may indicate at least one of the following: starting the AI task based on determining that a moving speed of the UE is lower than a third threshold; or stopping the AI task based on determining that the moving speed of the UE is equal to or higher than the third threshold.

Alternatively or additionally, in some implementations, the AI task configuration information associated with the RRC_INACTIVE state may comprise at least one condition for resuming or suspending the AI task in the RRC_INACTIVE state.

In some implementations, the at least one condition for resuming or suspending the AI task in the RRC_INACTIVE state may indicate at least one of the following: resuming the AI task based on determining that the measured quality of the serving cell or the serving beam is equal to or higher than the first threshold; or suspending the AI task based on determining that the measured quality of the serving cell or the serving beam is lower than the first threshold. For example, the measured quality of the serving cell or the serving beam may be RSRP of the serving cell or the serving beam. For example, if the RSRP of the serving cell or the serving beam is equal to or higher than the first threshold, the UE 104 may resume data collection. If the RSRP of the serving cell or the serving beam is lower than the first threshold, the UE 104 may suspend the data collection.

In some implementations, the at least one condition for resuming or suspending the AI task in the RRC_INACTIVE state may indicate at least one of the following: resuming the AI task based on determining that the computing resource or power of the UE is equal to or higher than the second threshold; or suspending the AI task based on determining that the computing resource or power of the UE is lower than the second threshold.

In some implementations, the at least one condition for resuming or suspending the AI task in the RRC_INACTIVE state may indicate at least one of the following: resuming the AI task based on determining that the moving speed of the UE is lower than the third threshold; or suspending the AI task based on determining that the moving speed of the UE is equal to or higher than the third threshold.

Alternatively or additionally, in some implementations, the AI task configuration information associated with the RRC_INACTIVE state may comprise a valid area of the AI task. The valid area of the AI task may indicate the AI task is only performed within the valid area.

In some implementations, the valid area of the AI task may be indicated by a list of cells.

Alternatively or additionally, in some implementations, the valid area of the AI task may be indicated by a radio access network (RAN) notification area (RNA) . The RNA can cover a single or multiple cells and shall be contained within the CN registration area. The RNA can be a list of cells or a list of RAN areas where a RAN area is a subset of a CN Tracking Area or equal to a CN Tracking Area. A RAN area is specified by one RAN area ID.

Alternatively or additionally, in some implementations, the valid area of the AI task may be indicated by an area in which the AI task should not be performed. It means that the UE 104 should not perform the AI task in the cells of the area and the UE 104 can perform the AI task in the cells out of the area.

Alternatively or additionally, in some implementations, the AI task configuration information associated with the RRC_INACTIVE state may comprise information about a further network entity initiating the AI task. The further network entity may be the same as or different from the network entity 102.

In some implementations, the information about the further network entity initiating the AI task may comprise an ID of a RAN node if the AI task is initiated by the RAN node. Alternatively, the information about the further network entity initiating the AI task may comprise an internet protocol (IP) address of an OAM entity if the AI task is initiated by the OAM entity. Alternatively, the information about the further network entity initiating the AI task may comprise an ID of a CN node if the AI task is initiated by the CN node.

Alternatively or additionally, in some implementations, the AI task configuration information associated with the RRC_INACTIVE state may comprise a priority of the AI task.

In some implementations, the at least one AI task may comprise multiple AI tasks. In other words, the AI task configuration information associated with the RRC_INACTIVE state may comprise configuration information for multiple AI tasks associated with the RRC_INACTIVE state. In such implementations, the UE 104 may perform the operation related to the multiple AI tasks in a decreasing order of priorities of the multiple AI tasks. For example, the UE 104 may prioritize to perform the AI task with higher priority by order in case the resource is limited.

Alternatively or additionally, in some implementations, the AI task configuration information associated with the RRC_INACTIVE state may comprise valid time of the AI task. If the valid time expires, the UE 104 may stop performing the AI task or trigger an RRC state transition procedure to RRC_CONNECTED state.

In turn, the network entity 102 transmits 220 the AI task configuration information associated with the RRC_INACTIVE state to the UE 104.

Upon receiving the AI task configuration information associated with the RRC_INACTIVE state, the UE 104 performs 230 an operation related to the at least one AI task based on the AI task configuration information associated with the RRC_INACTIVE state. Some implementations of the operation related to the at least one AI task will be described with reference to Figs. 3 and 4 later.

With the process 200, an operation related to the at least one AI task may be performed based on configuration information for at least one AI task associated with the RRC_INACTIVE state.

Fig. 3 illustrates a signaling diagram illustrating an example process 300 that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure. The process 300 may be considered as an example implementation of the process 200. The process 300 may involve the UE 104 and the network entity 102 in Fig. 1. For the purpose of discussion, the process 300 will be described with reference to Fig. 1.

As shown in Fig. 3, at 310, the UE 104 is in RRC_CONNECTED state. The UE 104 receives 320 a configuration for at least one AI task from the network entity 102. Hereinafter, the configuration for at least one AI task is also referred to as an AI task configuration for brevity. For example, the UE 104 may receive an RRC Reconfiguration message from the network entity 102. The RRC Reconfiguration message may comprise the AI task configuration.

In some implementations, the AI task configuration may comprise at least one ID of the at least one AI task. An ID of an AI task may be used to uniquely identify the AI task.

Additionally, in some implementations, the AI task configuration may comprise an RRC configuration for the at least one AI task.

In some implementations, an AI task may be one of the following types: data collection in RRC_INACTIVE, AI/ML training in RRC_INACTIVE, positioning or sensing. Alternatively, in some implementations, an AI task may be only for AI/ML training or inference purpose or for data collection purpose.

Upon receiving the AI task configuration, the UE 104 performs 330 the at least one AI task based on the AI task configuration.

In some implementations, if there is no data transmission for the UE 104 anymore, network entity 102 may decide to cause transition of the UE 104 into RRC_INACTIVE state from RRC_CONNECTED state. In such implementations, the network entity 102 transmits 340 the AI task configuration information associated with the RRC_INACTIVE state to the UE 104. For example, the network entity 102 may transmit an RRC Release message to the UE 104. The RRC Release message may comprise the AI task configuration information associated with the RRC_INACTIVE state. Some implementations of the AI task configuration information associated with the RRC_INACTIVE state have been described with reference to Fig. 2. Details of such implementations are omitted for brevity.

In some implementations, the at least one AI task indicated in the AI task configuration information associated with the RRC_INACTIVE state may be the same as or different from the at least one AI task indicated in the AI task configuration. For example, the AI task configuration may indicate AI tasks with IDs #1 and #2, and the AI task configuration information associated with the RRC_INACTIVE state may indicate at least one of the AI tasks with IDs #1 and #2. For another example, the AI task configuration may indicate AI tasks with IDs #1 and #2 while the AI task configuration information associated with the RRC_INACTIVE state may indicate an AI task with ID #3.

Upon receiving the AI task configuration information associated with the RRC_INACTIVE state, the UE 104 performs 350 an operation related to the at least one AI task based on the AI task configuration information associated with the RRC_INACTIVE state.

For example, if the indication in the AI task configuration information associated with the RRC_INACTIVE state indicates an AI task among the at least one AI task is to be continued in the RRC_INACTIVE state, the UE 104 may continue the AI task.

For another example, if the indication in the AI task configuration information associated with the RRC_INACTIVE state indicates the AI task is not to be continued in the RRC_INACTIVE state, the UE 104 may suspend the AI task. For example, the UE 104 may suspend a data radio bearer (DRB) or a computing radio bearer (CRB) of the AI task.

Alternatively or additionally, the UE 104 may prioritize to perform the AI task with higher priority by order in case a computing resource is limited.

Alternatively or additionally, the UE 104 may store the information in the AI task configuration information associated with the RRC_INACTIVE state.

Alternatively or additionally, the UE 104 may start a timer. A length of the timer may be set to the valid time of the AI task indicated in the AI task configuration information associated with the RRC_INACTIVE state.

In some implementations, the RRC Release message may also comprise the AI task configuration as described with respect to the action 320. When UE 104 receives the AI task configuration in the RRC Release message, the UE 104 may perform the at least one AI task in the RRC_INACTIVE state.

In some implementations, if the indication in the AI task configuration information associated with the RRC_INACTIVE state indicates an AI task is to be continued in the RRC_INACTIVE state, and if the AI task requires associated radio configuration, e.g., the reference signal configuration related to data collection, positioning or sensing, the radio configuration can be either provided in the suspendConfig information element (IE) within the RRC Release message, or provided in the RRC Reconfiguration message earlier when UE 104 is in the RRC connected state and stored in the UE Inactive AS Context.

Hereinafter, some implementations for performing the operation related to the at least one AI task will be described.

In some implementations, performing the operation related to the at least one AI task may comprise triggering an RRC state transition from the RRC_INACTIVE state to an RRC_CONNECTED state. In other words, performing the operation related to the at least one AI task may comprise requesting resume of a suspended RRC connection.

In some implementations, the UE 104 may initiate the RRC Connection Resume procedure when upper layers or access stratum (AS) of the UE 104 requests resume of a suspended RRC connection. In other words, the UE 104 may initiate the RRC Connection Resume procedure when upper layers or AS of the UE 104 triggers an RRC state transition from the RRC_INACTIVE state to the RRC_CONNECTED state. For example, the upper layer may be NAS layer or a dedicated AI/ML layer above RRC layer and the AS layer is RRC layer. Such implementations will be described with reference to Fig. 4.

Fig. 4 illustrates a signaling diagram illustrating an example process 400 that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure. The process 400 may be considered as an example implementation of the process 200. The process 400 may involve the UE 104 and the network entity 102 in Fig. 1. For the purpose of discussion, the process 400 will be described with reference to Fig. 1.

As shown in Fig. 4, at 410, the UE 104 is in the RRC_INACTIVE state.

In some implementations, the UE 104 may trigger the RRC state transition from the RRC_INACTIVE state to the RRC_CONNECTED state if an AI task among the at least one AI task becomes applicable or available. If an AI task becomes applicable or available, it means that the UE 104 is ready to apply for model inference for the AI task. For an AI task to be applicable, there may be at least one model available within the AI task. If an AI task becomes applicable, it means that it is ready for AI/ML inference under some additional network conditions or UE conditions.

Alternatively, in some implementations, the UE 104 may trigger the RRC state transition from the RRC_INACTIVE state to the RRC_CONNECTED state if the AI task is complete. For example, if the UE 104 has finished the AI task and results of the AI task is available in the UE 104, the UE 104 may trigger the RRC state transition from the RRC_INACTIVE state to the RRC_CONNECTED state.

Alternatively, in some implementations, the UE 104 may trigger the RRC state transition from the RRC_INACTIVE state to the RRC_CONNECTED state if valid time of the AI task has been elapsed. For example, when the valid time of the AI task has been elapsed since the UE 104 received the RRC Release message or since the AI task was started.

Alternatively, in some implementations, the UE 104 may trigger the RRC state transition from the RRC_INACTIVE state to the RRC_CONNECTED state if a timer defining the valid time of the AI task expires. If the timer expires, the UE 104 may stop performing the AI task or trigger the RRC state transition from the RRC_INACTIVE state to RRC_CONNECTED state.

Alternatively, in some implementations, the UE 104 may trigger the RRC state transition from the RRC_INACTIVE state to the RRC_CONNECTED state if the UE 104 moves to a cell that is not in a valid area of the AI task.

In one of the above conditions for triggering the RRC state transition from the RRC_INACTIVE state to the RRC_CONNECTED state is met, the UE 104 initiates the RRC Connection Resume procedure by transmitting 420 an RRC Resume Request message to the network entity 102.

Upon receiving the RRC Resume Request message, the network entity 102 transmits 430 an RRC Resume message to the UE 104.

In turn, the UE 104 transmits 440 an RRC Resume Complete message to the network entity 102.

Then, the UE 104 transmits 450 transmits 450 a UE Assistance Information message to the network entity 102. The UE Assistance Information may indicate AI task status update.

In some implementations, the UE 104 may transmit, to the network entity 102, a cause for an RRC state transition from the RRC_INACTIVE state to an RRC_CONNECTED state. The cause is related to the at least one AI task. Hereinafter, the cause which is related to the at least one AI task is also referred to as an AI task related cause.

In some implementations, the UE 104 may transmit the cause for the RRC state transition in one of the following: an RRC Resume Request message, an RRC Resume Complete message, or a UE Assistance Information message, as shown in Fig. 4.

In some implementations, when the AI task is performed in NAS or dedicated AI/ML layer of the UE 104 and when one of the above events for triggering the RRC state transition is fulfilled, the NAS or dedicated AI/ML layer may also send RRC layer the AI task related “cause” to request the RRC Connection Resume procedure. The AI task related cause may indicate one of the following:

- the AI task becomes applicable or available;

- the AI task is complete;

- the valid time of the AI task has been elapsed; or

- the timer defining the valid time expires.

Alternatively, the AI task related cause may also be a general RRC cause as “AI/ML” which means the RRC state transition is initiated by AI/ML purpose. The general RRC cause may also be “AI/ML MO” or “AI/ML MT” which means the RRC state transition is initiated by mobile originated AI/ML purpose or by mobile terminated AI/ML purpose respectively.

When receiving the AI task related causes, the network entity 102 may perform subsequent actions. When the AI task related cause is “AI task becomes applicable or available” , the network entity 102 may further configure the UE 104 to perform inference of the AI task. When the AI task related cause is “AI task is complete” , the network entity 102 may further configure the UE 104 to report results of the AI task to the network entity 102. For example, the network entity 102 may request the UE 104 to provide the results of the AI task via a UE Information Request message with associated indicator (e.g., “aiTaskOutput” ) , and the UE 104 provides the results of the AI task in the corresponding UE Information Response message. When the AI task related cause is “valid time of the AI task has been elapsed” , the network entity 102 may consider to reconfigure or release the AI task.

In some implementations, when the UE 104 requests resume of a suspended RRC connection, the UE 104 first performs access barring check to determine whether an access attempt is allowed. The UE 104 may perform access barring check for access attempt for the following events:

- the UE 104 is in RRC_INACTIVE state, and a non-access stratum (NAS) or dedicated AI/machine learning (ML) layer of the UE 104 receives one of the following indications for the AI task:

- the AI task becomes applicable or available;

- the AI task is completed;

- the valid time of the AI task has been elapsed or the timer defining the valid time expires; or

- UE 104 moves out of the valid area of the AI task.

When the NAS of the UE 104 detects one of the above events, the NAS or the dedicated AI/ML layer of the UE 104 needs to perform mapping of the kind of request to one or more access identities and one access category and RRC layer of the UE 104 will perform access barring checks for that request based on the determined access identities and access category.

In some implementations, when the UE 104 requests resume of a suspended RRC connection triggered by one of the above events related to the AI task, the UE 104 may determine the access identities as shown in Table 1:

Table 1: Access identities

In some implementations, for each of the access identities 1, 2, 3, 11, 12, 13, 14 and 15 in Table 1, the UE 104 shall check whether the access identity is applicable in the selected public land mobile network (PLMN) if a new PLMN is selected, or otherwise if it is applicable in the RPLMN or equivalent PLMN.

In some implementations, if none of the above access identities is applicable, then access identity 0 is applicable.

In some implementations, at least one access category related to the at least one AI task is introduced. Hereinafter, at least one access category related to the at least one AI task is also referred to as AI task related access category.

In some implementations, the AI task related access category may comprise a first access category. Hereinafter, the first access category is also referred to as an access category X. The access category X is associated with a first type of access attempt.

In some implementations, the first type of access attempt is related to one of the following: signaling transmission for the at least one AI task originated from the NAS or dedicated AI/ML layer of the UE 104, or data transmission for the at least one AI task originated from the NAS or dedicated AI/ML layer of the UE 104.

Alternatively or additionally, in some implementations, the access category X is associated with one of the following:

- an AI task among the at least one AI task becomes applicable or available,

- the AI task is complete,

- valid time of the AI task has been elapsed, or

- a timer defining the valid time of the AI task expires.

In some implementations, the AI task related access category may comprise a second access category. Hereinafter, the second access category is also referred to as an access category Y. The access category Y is associated with a second type of access attempt.

In some implementations, the second type of access attempt is related to the following: data transmission for the at least one AI task originated from the NAS or dedicated AI/ML layer of the UE 104.

In some implementations, the access category Y is associated with results of the at least one AI task are to be transmitted.

In some implementations, when the NAS or dedicated AI/ML layer of the UE 104 triggers access attempt for the RRC Connection Resume for AI/ML purposes, the NAS or dedicated AI/ML layer of the UE 104 selects one of the AI task related access categories X and Y.

In order to select or determine the access category applicable for the access attempt, the NAS or dedicated AI/ML layer of the UE 104 may check rules in Table 2 and use the access category for which there is a match for access barring check. The access categories X and Y for AI/ML related service are defined. The mapping rules are defined for the AI task related access categories, as shown in Table 2.

Table 2: Mapping table for AI task related access categories

In some implementations, the UE 104 may receive, from the network entity 102 or a further network entity different from the network entity 102, at least one access control parameter for the access category related to the at least one AI task. The UE 104 may perform, based on the at least one access control parameter, access barring check for the access category related to the at least one AI task.

In some implementations, the UE 104 may receive, from the network entity 102 or a further network entity different from the network entity 102, at least one access control parameter for the AI task related access category. In turn, the UE 104 may perform, based on the at least one access control parameter, access barring check for the AI task related access category. For example, the UE 104 may receive access control parameters for the access categories X and Y.

In some implementations, the UE 104 may receive at least one access control parameter for the AI task related access category in system information.

In some implementations, the at least one access control parameter for the AI task related access category may comprise at least one of the following:

- access barring factor which represents a probability that an access attempt would be allowed during the access barring check,

- access barring time which indicates average time before a new access attempt is to be performed after the access attempt was barred at the access barring check for the access category, or

- access baring for access identity which indicates whether the access attempt is allowed for each access identity.

In some implementations, when the UE 104 requests resume of a suspended RRC connection triggered by one of the above events related to the AI task, the UE 104 may perform access barring check as shown in Fig. 5.

Fig. 5 illustrates a flowchart of a method 500 for access barring check in accordance with aspects of the present disclosure. The method 500 may be considered as an example implementation of the action 230 in Fig. 2 or 350 in Fig. 3.

As shown in Fig. 5, at 510, the UE 104 determines whether the selected Access Identities in “access control parameters” is set to zero.

If the selected Access Identities in “access control parameters” is set to zero, the UE 104 considers the access attempt as allowed at 520.

If the selected Access Identities in “access control parameters” is not set to zero, the UE 104 draws or determine, at 530, a random number uniformly distributed in a range of zero to one. The random number is represented by “rand” .

At 540, the UE 104 determines whether the random number “rand” is lower than a value indicated by an access barring factor for the access category X or the access category Y among the at least one access control parameter.

If the random number “rand” is lower than the value indicated by the access barring factor, the UE 104 considers access attempt as allowed at 550.

If the random number “rand” is equal to or higher than the value indicated by the access barring factor, the UE 104 considers the access attempt as barred at 560.

In some implementations, if the access attempt is considered as barred, the UE 104 may draw a random number 'rand' that is uniformly distributed in a range of zero to one. In addition, the UE 104 may start timer Txxx for the access category X or Y with the timer value calculated as follows, using the access barring time included in “access control parameters. For example, the UE 104 may calculate the timer value based on the following:
Txxx = (0.7+ 0.6 *rand) *access barring time (1) .

If timer Txxx is running for the access category, the UE 104 considers the access attempt as barred.

In some implementations, the AI task may impact the mobility procedure of the UE 104 in the RRC_INACTIVE state. In such implementations, the UE 104 may perform a cell reselection procedure to reselect a first cell in a valid area of an AI task among the at least one AI task. For example, at reception of the RRC Release message to transit the UE 104 to the RRC_INACTIVE state, UE 104 shall attempt to camp on a suitable cell (such as the first cell) that is in the valid area of the AI task.

In some implementations, in order to perform the cell reselection procedure, at least one threshold to trigger measurements for reselection of the first cell in the valid area of the AI task is defined and configured for the UE 104. The UE 104 may start the measurements for reselection of the first cell in the valid area of the AI task based on the at least one threshold.

In some implementations, the at least one threshold may comprise at least one of the following: a first threshold for receiving level (such as RSRP) , or a second threshold for quality level (such as RSRQ) . Hereinafter, the first threshold is represented by S_validArea-P, and the second threshold is represented by S_validArea-Q.

In some implementations, when Srxlev <= S_validArea-P and/or Squal <= S_validArea- _Q, the UE 104 starts measurements for cells in the valid area of the AI task. Srxlev and Squal are defined as below:
Srxlev = Q_rxlevmeas – (Q_rxlevmin + Q_{rxlevminoffset} ) –P_compensation -Qoffset_temp (2)
Squal = Q_qualmeas – (Q_qualmin + Q_{qualminoffset}) -Qoffset_temp (3)

Meanings of parameters in equations (2) and (3) are given in Table 3.

Table 3

In some implementations, cell reselection criteria within the valid area of the AI task is introduced. In such implementations, the UE 104 performs cell reselection to the first cell in the valid area of the AI task according to cell-ranking criterion. That is, the UE 104 determines at least one cell in the valid area of the AI task and a serving cell of the UE 104 as candidate cells for ranking of cells. In such implementations, when performing the cell reselection, the UE 104 prioritizes to reselect a cell (such as the first cell) in the valid area of the AI task.

In some implementations, the cell-ranking criterion R_s for a serving cell and R_n for each of at least one cell in the valid area of the AI task are defined as below:
R_s = Q_meas, s+Q_hyst -Qoffset_temp (4)
R_n = Q_meas, n -Qoffset –Qoffset_temp (5)

Meanings of parameters in equations (4) and (5) are given in Table 4.

Table 4

In some implementations, the UE 104 may reselect the new cell (such as the first cell) that is in the valid area of the AI task, only if the following conditions are met:

- the new cell that is in the valid area of the AI task is better than the serving cell according to the cell reselection criteria specified above during a time interval Treselection_RAT;

- more than 1 second has elapsed since the UE 104 camped on the current serving cell.

In some implementations, in order to prioritize to reselect a cell (such as the first cell) in the valid area of the AI task, the UE 104 may perform cell reselection to the cell in the valid area according to cell-ranking criterion by adding an offset to R values for the cells in the valid area. In other words, the UE 104 may update an R value for each of the at least one cell in the valid area of the AI task with an offset applied to the at least one cell. For example, the UE 104 may update the R value for each of the at least one cell in the valid area of the AI task by updating the above equation (5) as below:
R_n = Q_meas, n -Qoffset –Qoffset_temp + Qoffset_area (6)

where the Qoffset_area represents the offset applied to the at least one cell in the valid area of the AI task.

In some implementations, when the UE 104 moves to a cell that is out of a valid area of an AI task among the at least one AI task, the UE 104 may suspend the AI task. When the UE 104 moves back to a cell in the valid area of the AI task, the UE 104 may resume the AI task.

Alternatively, when the UE 104 moves to a cell that is out of a valid area of an AI task among the at least one AI task, the UE 104 may release the AI task.

Fig. 6 illustrates an example of a device 600 that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure. The device 600 may be an example of a network entity 102 or a UE 104 as described herein. The device 600 may support wireless communication with one or more network entities 102, UEs 104, or any combination thereof. The device 600 may include components for bi-directional communications including components for transmitting and receiving communications, such as a processor 602, a memory 604, a transceiver 606, and, optionally, an I/O controller 608. These components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces (e.g., buses) .

The processor 602, the memory 604, the transceiver 606, or various combinations thereof or various components thereof may be examples of means for performing various aspects of the present disclosure as described herein. For example, the processor 602, the memory 604, the transceiver 606, or various combinations or components thereof may support a method for performing one or more of the operations described herein.

In some implementations, the processor 602, the memory 604, the transceiver 606, or various combinations or components thereof may be implemented in hardware (e.g., in communications management circuitry) . The hardware may include a processor, a digital signal processor (DSP) , an application-specific integrated circuit (ASIC) , a field- programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic, discrete hardware components, or any combination thereof configured as or otherwise supporting a means for performing the functions described in the present disclosure. In some implementations, the processor 602 and the memory 604 coupled with the processor 602 may be configured to perform one or more of the functions described herein (e.g., executing, by the processor 602, instructions stored in the memory 604) .

For example, the processor 602 may support wireless communication at the device 600 in accordance with examples as disclosed herein. The processor 602 may be configured to operable to support a means for performing the following: receiving configuration information for at least one AI task associated with an RRC_INACTIVE state from a network entity; and performing an operation related to the at least one AI task based on the configuration information.

Alternatively, in some implementations, the processor 602 may be configured to operable to support a means for performing the following: determining configuration information for at least one AI task associated with an RRC_INACTIVE state; and transmitting the configuration information via the transceiver to a UE.

The processor 602 may include an intelligent hardware device (e.g., a general-purpose processor, a DSP, a CPU, a microcontroller, an ASIC, an FPGA, a programmable logic device, a discrete gate or transistor logic component, a discrete hardware component, or any combination thereof) . In some implementations, the processor 602 may be configured to operate a memory array using a memory controller. In some other implementations, a memory controller may be integrated into the processor 602. The processor 602 may be configured to execute computer-readable instructions stored in a memory (e.g., the memory 604) to cause the device 600 to perform various functions of the present disclosure.

The memory 604 may include random access memory (RAM) and read-only memory (ROM) . The memory 604 may store computer-readable, computer-executable code including instructions that, when executed by the processor 602 cause the device 600 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such as system memory or another type of memory. In some implementations, the code may not be directly executable by the processor 602 but may cause a computer (e.g., when compiled and executed) to perform functions described herein. In some implementations, the memory 604 may include, among other things, a basic I/O system (BIOS) which may control basic hardware or software operation such as the interaction with peripheral components or devices.

The I/O controller 608 may manage input and output signals for the device 600. The I/O controller 608 may also manage peripherals not integrated into the device M02. In some implementations, the I/O controller 608 may represent a physical connection or port to an external peripheral. In some implementations, the I/O controller 608 may utilize an operating system such as or another known operating system. In some implementations, the I/O controller 608 may be implemented as part of a processor, such as the processor 606. In some implementations, a user may interact with the device 600 via the I/O controller 608 or via hardware components controlled by the I/O controller 608.

In some implementations, the device 600 may include a single antenna 610. However, in some other implementations, the device 600 may have more than one antenna 610 (i.e., multiple antennas) , including multiple antenna panels or antenna arrays, which may be capable of concurrently transmitting or receiving multiple wireless transmissions. The transceiver 606 may communicate bi-directionally, via the one or more antennas 610, wired, or wireless links as described herein. For example, the transceiver 606 may represent a wireless transceiver and may communicate bi-directionally with another wireless transceiver. The transceiver 606 may also include a modem to modulate the packets, to provide the modulated packets to one or more antennas 610 for transmission, and to demodulate packets received from the one or more antennas 610. The transceiver 606 may include one or more transmit chains, one or more receive chains, or a combination thereof.

A transmit chain may be configured to generate and transmit signals (e.g., control information, data, packets) . The transmit chain may include at least one modulator for modulating data onto a carrier signal, preparing the signal for transmission over a wireless medium. The at least one modulator may be configured to support one or more techniques such as amplitude modulation (AM) , frequency modulation (FM) , or digital modulation schemes like phase-shift keying (PSK) or quadrature amplitude modulation (QAM) . The transmit chain may also include at least one power amplifier configured to amplify the modulated signal to an appropriate power level suitable for transmission over the wireless medium. The transmit chain may also include one or more antennas 610 for transmitting the amplified signal into the air or wireless medium.

A receive chain may be configured to receive signals (e.g., control information, data, packets) over a wireless medium. For example, the receive chain may include one or more antennas 610 for receive the signal over the air or wireless medium. The receive chain may include at least one amplifier (e.g., a low-noise amplifier (LNA) ) configured to amplify the received signal. The receive chain may include at least one demodulator configured to demodulate the receive signal and obtain the transmitted data by reversing the modulation technique applied during transmission of the signal. The receive chain may include at least one decoder for decoding the processing the demodulated signal to receive the transmitted data.

Fig. 7 illustrates an example of a processor 700 that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure. The processor 700 may be an example of a processor configured to perform various operations in accordance with examples as described herein. The processor 700 may include a controller 702 configured to perform various operations in accordance with examples as described herein. The processor 700 may optionally include at least one memory 704, such as L1/L2/L3 cache. Additionally, or alternatively, the processor 700 may optionally include one or more arithmetic-logic units (ALUs) 706. One or more of these components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces (e.g., buses) .

The processor 700 may be a processor chipset and include a protocol stack (e.g., a software stack) executed by the processor chipset to perform various operations (e.g., receiving, obtaining, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, reading) in accordance with examples as described herein. The processor chipset may include one or more cores, one or more caches (e.g., memory local to or included in the processor chipset (e.g., the processor 700) or other memory (e.g., random access memory (RAM) , read-only memory (ROM) , dynamic RAM (DRAM) , synchronous dynamic RAM (SDRAM) , static RAM (SRAM) , ferroelectric RAM (FeRAM) , magnetic RAM (MRAM) , resistive RAM (RRAM) , flash memory, phase change memory (PCM) , and others) .

The controller 702 may be configured to manage and coordinate various operations (e.g., signaling, receiving, obtaining, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, reading) of the processor 700 to cause the processor 700 to support various operations in accordance with examples as described herein. For example, the controller 702 may operate as a control unit of the processor 700, generating control signals that manage the operation of various components of the processor 700. These control signals include enabling or disabling functional units, selecting data paths, initiating memory access, and coordinating timing of operations.

The controller 702 may be configured to fetch (e.g., obtain, retrieve, receive) instructions from the memory 704 and determine subsequent instruction (s) to be executed to cause the processor 700 to support various operations in accordance with examples as described herein. The controller 702 may be configured to track memory address of instructions associated with the memory 704. The controller 702 may be configured to decode instructions to determine the operation to be performed and the operands involved. For example, the controller 702 may be configured to interpret the instruction and determine control signals to be output to other components of the processor 700 to cause the processor 700 to support various operations in accordance with examples as described herein. Additionally, or alternatively, the controller 702 may be configured to manage flow of data within the processor 700. The controller 702 may be configured to control transfer of data between registers, arithmetic logic units (ALUs) , and other functional units of the processor 700.

The memory 704 may include one or more caches (e.g., memory local to or included in the processor 700 or other memory, such RAM, ROM, DRAM, SDRAM, SRAM, MRAM, flash memory, etc. In some implementation, the memory 704 may reside within or on a processor chipset (e.g., local to the processor 700) . In some other implementations, the memory 704 may reside external to the processor chipset (e.g., remote to the processor 700) .

The memory 704 may store computer-readable, computer-executable code including instructions that, when executed by the processor 700, cause the processor 700 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such as system memory or another type of memory. The controller 702 and/or the processor 700 may be configured to execute computer-readable instructions stored in the memory 704 to cause the processor 700 to perform various functions. For example, the processor 700 and/or the controller 702 may be coupled with or to the memory 704, the processor 700, the controller 702, and the memory 704 may be configured to perform various functions described herein. In some examples, the processor 700 may include multiple processors and the memory 704 may include multiple memories. One or more of the multiple processors may be coupled with one or more of the multiple memories, which may, individually or collectively, be configured to perform various functions herein.

The one or more ALUs 706 may be configured to support various operations in accordance with examples as described herein. In some implementation, the one or more ALUs 706 may reside within or on a processor chipset (e.g., the processor 700) . In some other implementations, the one or more ALUs 706 may reside external to the processor chipset (e.g., the processor 700) . One or more ALUs 706 may perform one or more computations such as addition, subtraction, multiplication, and division on data. For example, one or more ALUs 706 may receive input operands and an operation code, which determines an operation to be executed. One or more ALUs 706 be configured with a variety of logical and arithmetic circuits, including adders, subtractors, shifters, and logic gates, to process and manipulate the data according to the operation. Additionally, or alternatively, the one or more ALUs 706 may support logical operations such as AND, OR, exclusive-OR (XOR) , not-OR (NOR) , and not-AND (NAND) , enabling the one or more ALUs 706 to handle conditional operations, comparisons, and bitwise operations.

The processor 700 may support wireless communication at the device 1000 in accordance with examples as disclosed herein. The processor 700 may be configured to operable to support a means for performing the following: receiving configuration information for at least one AI task associated with an RRC_INACTIVE state from a network entity; and performing an operation related to the at least one AI task based on the configuration information.

Alternatively, in some implementations, the processor 700 may be configured to operable to support a means for performing the following: determining configuration information for at least one AI task associated with an RRC_INACTIVE state; and transmitting the configuration information via the transceiver to a UE.

Fig. 8 illustrates a flowchart of a method 800 that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure. The operations of the method 800 may be implemented by a device or its components as described herein. For example, the operations of the method 800 may be performed by a UE 104 as described herein. In some implementations, the device may execute a set of instructions to control the function elements of the device to perform the described functions. Additionally, or alternatively, the device may perform aspects of the described functions using special-purpose hardware.

At 810, the method may include receiving configuration information for at least one AI task associated with an RRC_INACTIVE state from a network entity. The operations of 810 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 810 may be performed by a device as described with reference to Fig. 1.

At 820, the method may include performing an operation related to the at least one AI task based on the configuration information. The operations of 820 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 820 may be performed by a device as described with reference to Fig. 1.

Fig. 9 illustrates a flowchart of a method 900 that supports at least one AI task in an RRC_INACTIVE state in accordance with aspects of the present disclosure. The operations of the method 900 may be implemented by a device or its components as described herein. For example, the operations of the method 900 may be performed by a network entity 102 as described herein. In some implementations, the device may execute a set of instructions to control the function elements of the device to perform the described functions. Additionally, or alternatively, the device may perform aspects of the described functions using special-purpose hardware.

At 910, the method may include determining configuration information for at least one AI task associated with an RRC_INACTIVE state. The operations of 910 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 910 may be performed by a device as described with reference to Fig. 1.

At 920, the method may include transmitting the configuration information via the transceiver to a UE. The operations of 920 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 920 may be performed by a device as described with reference to Fig. 1.

It shall be noted that implementations of the present disclosure which have been described with reference to Figs. 1 to 5 are also applicable to the device 600, the processor 700 as well as the methods 800 and 900.

It should be noted that the methods described herein describes possible implementations, and that the operations and the steps may be rearranged or otherwise modified and that other implementations are possible. Further, aspects from two or more of the methods may be combined.

The various illustrative blocks and components described in connection with the disclosure herein may be implemented or performed with a general-purpose processor, a DSP, an ASIC, a CPU, an FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices (e.g., a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Other examples and implementations are within the scope of the disclosure and appended claims. For example, due to the nature of software, functions described herein may be implemented using software executed by a processor, hardware, firmware, hardwiring, or combinations of any of these. Features implementing functions may also be physically located at various positions, including being distributed such that portions of functions are implemented at different physical locations.

Computer-readable media includes both non-transitory computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A non-transitory storage medium may be any available medium that may be accessed by a general-purpose or special-purpose computer. By way of example, non-transitory computer-readable media may include RAM, ROM, electrically erasable programmable ROM (EEPROM) , flash memory, compact disk (CD) ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that may be used to carry or store desired program code means in the form of instructions or data structures and that may be accessed by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor.

As used herein, including in the claims, an article “a” before an element is unrestricted and understood to refer to “at least one” of those elements or “one or more” of those elements. The terms “a, ” “at least one, ” “one or more, ” and “at least one of one or more” may be interchangeable. As used herein, including in the claims, “or” as used in a list of items (e.g., a list of items prefaced by a phrase such as “at least one of” or “one or more of” or “one or both of” ) indicates an inclusive list such that, for example, a list of at least one of A, B, or C means A or B or C or AB or AC or BC or ABC (i.e., A and B and C) . Also, as used herein, the phrase “based on” shall not be construed as a reference to a closed set of conditions. For example, an example step that is described as “based on condition A” may be based on both a condition A and a condition B without departing from the scope of the present disclosure. In other words, as used herein, the phrase “based on” shall be construed in the same manner as the phrase “based at least in part on. Further, as used herein, including in the claims, a “set” may include one or more elements.

The description herein is provided to enable a person having ordinary skill in the art to make or use the disclosure. Various modifications to the disclosure will be apparent to a person having ordinary skill in the art, and the generic principles defined herein may be applied to other variations without departing from the scope of the disclosure. Thus, the disclosure is not limited to the examples and designs described herein but is to be accorded the broadest scope consistent with the principles and novel features disclosed herein.

Claims

A user equipment (UE) , comprising:

a processor; and

a transceiver coupled to the processor,

wherein the processor is configured to:

receive configuration information for at least one artificial intelligence (AI) task associated with a radio resource control (RRC) _INACTIVE state via the transceiver from a network entity; and

perform an operation related to the at least one AI task based on the configuration information.
The UE of claim 1, wherein the configuration information comprises at least one of the following:

an indication indicating whether an AI task among the at least one AI task is to be continued or to be performed in the RRC_INACTIVE state,

at least one condition for starting or stopping the AI task in the RRC_INACTIVE state,

at least one condition for resuming or suspending the AI task in the RRC_INACTIVE state,

a valid area of the AI task,

information about a further network entity initiating the AI task,

a priority of the AI task, or

valid time of the AI task.
The UE of claim 2, wherein the valid area of the AI task is indicated by one of the following:

a list of cells,

a radio access network (RAN) notification area, or

an area in which the AI task should not be performed.
The UE of claim 1, wherein the processor is configured to perform the operation related to the at least one AI task by:

triggering an RRC state transition from the RRC_INACTIVE state to an RRC_CONNECTED state based on determining one of the following:

an AI task among the at least one AI task becomes applicable or available,

the AI task is complete,

valid time of the AI task has been elapsed,

a timer defining the valid time of the AI task expires, or

the UE moves to a cell that is not in a valid area of the AI task.
The UE of claim 1, wherein the processor is configured to perform the operation related to the at least one AI task by:

receiving, via the transceiver from the network entity or a further network entity, at least one access control parameter for an access category related to the at least one AI task; and

performing, based on the at least one access control parameter, access barring check for the access category related to the at least one AI task.
The UE of claim 5, wherein the at least one access control parameter for the access category related to the at least one AI task comprises at least one of the following:

access barring factor which represents a probability that an access attempt would be allowed during the access barring check,

access barring time which indicates average time before a new access attempt is to be performed after the access attempt was barred at the access barring check for the access category, or

access baring for access identity which indicates whether the access attempt is allowed for each access identity.
The UE of claim 5, wherein the processor is configured to perform the access barring check by:

drawing a random number uniformly distributed in a range of zero to one;

determining whether the random number is lower than a value indicated by an access barring factor for the access category among the at least one access control parameter;

based on determining that the random number is lower than a value indicated by the access barring factor, considering access attempt as allowed; and

based on determining that the random number is equal to or higher than the value indicated by the access barring factor, considering the access attempt as barred.
The UE of claim 5, wherein the access category related to the at least one AI task comprises a first access category which is associated with a first type of access attempt, wherein the first type of access attempt is related to one of the following:

signaling transmission for the at least one AI task originated from a non-access stratum (NAS) or dedicated AI/machine learning (ML) layer of the UE, or

data transmission for the at least one AI task originated from the NAS or dedicated AI/ML layer of the UE.
The UE of claim 1 or 4, wherein the processor is configured to perform the operation related to the at least one AI task by:

transmitting, via the transceiver to the network entity, a cause for an RRC state transition from the RRC_INACTIVE state to an RRC_CONNECTED state, wherein the cause is related to the at least one AI task.
The UE of claim 9, wherein the cause indicates one of the following:

an AI task among the at least one AI task becomes applicable or available,

the AI task is complete,

valid time of the AI task has been elapsed,

a timer defining the valid time of the AI task expires,

the RRC state transition is initiated by AI or machine learning (ML) purpose,

the RRC state transition is initiated by mobile originated AI or ML purpose, or

the RRC state transition is initiated by mobile terminated AI or ML purpose.
The UE of claim 1, wherein the processor is configured to perform the operation related to the at least one AI task by:

performing a cell reselection procedure to reselect a first cell in a valid area of an AI task among the at least one AI task.
The UE of claim 11, wherein the processor is configured to perform the cell reselection procedure by:

starting measurements for reselection of the first cell in the valid area of the AI task based on at least one threshold.
The UE of claim 12, wherein the at least one threshold comprises at least one of the following:

a first threshold for receiving level, or

a second threshold for quality level.
The UE of claim 11, wherein the processor is configured to perform the cell reselection procedure by:

determining at least one cell in the valid area of the AI task and a serving cell of the UE as candidate cells for ranking of cells, wherein the at least one cell in the valid area of the AI task comprises the first cell.
The UE of claim 14, wherein the processor is configured to perform the cell reselection procedure by:

updating an R value for each of the at least one cell in the valid area of the AI task with an offset applied to the at least one cell.
The UE of claim 1, wherein the processor is configured to perform the operation related to the at least one AI task by:

based on determining that the UE moves to a cell that is out of a valid area of an AI task among the at least one AI task, performing one of the following:

suspending the AI task and resuming the AI task when moving back to a cell in the valid area of the AI task; or

releasing the AI task.
A network entity, comprising:

a processor; and

a transceiver coupled to the processor,

wherein the processor is configured to:

determine configuration information for at least one artificial intelligence (AI) task associated with a radio resource control (RRC) _INACTIVE state; and

transmit the configuration information via the transceiver to a user equipment (UE) .
The network entity of claim 17, wherein the configuration information comprises at least one of the following:

an indication indicating whether an AI task among the at least one AI task is to be continued or to be performed in the RRC_INACTIVE state,

at least one condition for starting or stopping the AI task in the RRC_INACTIVE state,

at least one condition for resuming or suspending the AI task in the RRC_INACTIVE state,

a valid area of the AI task,

information about a further network entity initiating the AI task,

a priority of the AI task, or

valid time of the AI task.
A method for wireless communication, comprising:

receiving configuration information for at least one artificial intelligence (AI) task associated with a radio resource control (RRC) _INACTIVE state from a network entity; and

performing an operation related to the at least one AI task based on the configuration information.
A processor for wireless communication, comprising:

at least one memory; and

a controller coupled with the at least one memory and configured to cause the controller to:

receive configuration information for at least one artificial intelligence (AI) task associated with a radio resource control (RRC) _INACTIVE state via the transceiver from a network entity; and

perform an operation related to the at least one AI task based on the configuration information.