KR-20260066807-A - Method, architecture, device, and system for artificial intelligence/machine learning functions in a wireless transceiver unit

KR20260066807AKR 20260066807 AKR20260066807 AKR 20260066807AKR-20260066807-A

Abstract

Procedures, methods, architectures, devices, systems, devices, and computer program products for a WTRU within a network for enabling artificial intelligence/machine learning (AI/ML) functions in a wireless transmit-receive unit (WTRU) are described. The WTRU may receive configuration information from the network containing information regarding at least one AI/ML function that it supports, and may receive an activation indication from the network related to the activation of one or more AI/ML functions by the WTRU. The WTRU may determine at least one AI/ML function that can be supported by the WTRU upon receiving the activation indication. The WTRU may activate at least one AI/ML function that can be supported by the WTRU upon receiving the activation indication, and may transmit an indication to the network containing information regarding one or more activated AI/ML functions.

Inventors

루추문 테자스위니
나라야난 탕가라지 유게스와르 디누
테이이브 우머
투허 패트릭
콘세이카오, 필리페
밀러 제임스

Assignees

인터디지탈 패튼 홀딩스, 인크

Dates

Publication Date: 20260512
Application Date: 20240917
Priority Date: 20230926

Claims (12)

A method implemented by a wireless transmit-receive unit (WTRU) within a network, A step of receiving configuration information from the above network, including information regarding artificial intelligence/machine learning (AI/ML) functions to be supported by the WTRU; A step of receiving an activation indication from the network related to the activation of two or more AI/ML functions by the WTRU; A step of determining, based on conditions, that at least one first AI/ML function among the two or more AI/ML functions can be supported by the WTRU, and at least one second AI/ML function among the two or more AI/ML functions cannot be supported by the WTRU; The step of enabling at least one first AI/ML function; and A step of transmitting a mark to the above network - the mark includes information regarding the activated at least first AI/ML function - A method implemented by a wireless transceiver unit (WTRU) within a network, including
In paragraph 1, The above conditions are: Available processing power of WTRU; Available storage capacity of WTRU; Radio conditions observed by WTRU; and Channel conditions observed by WTRU A method implemented by a wireless transceiver unit (WTRU) in a network, comprising at least one of the following.
In paragraph 2, A method implemented by a wireless transceiver unit (WTRU) in a network, wherein the above conditions further include the priority of the AI/ML functions as indicated in the above configuration information.
In paragraph 1, A method implemented by a wireless transceiver unit (WTRU) in a network, wherein the above configuration information comprises at least one of the priority of the AI/ML functions to be supported by the WTRU; the periodicity of the evaluation of the AI/ML functions to be supported by the WTRU; and a reporting configuration for transmitting the indication to the network.
In any one of paragraphs 1 through 3, A method implemented by a wireless transceiver unit (WTRU) in a network, wherein the above configuration information includes the priority and reporting configuration of the AI/ML functions to be supported by the WTRU, and the WTRU reports to the network priority AI/ML functions that cannot be activated due to the conditions and for which an activation indication is received according to the reporting configuration.
In paragraph 1, The above configuration information includes the periodicity of the evaluation by the WTRU of the AI/ML functions supported by the WTRU, and The above method, depending on the periodicity of the above evaluation: A step of performing an evaluation of AI/ML functions supported by the above WTRU; Based on the above evaluation, activation of at least one supported AI/ML function and deactivation of unsupported AI/ML functions; A step of transmitting a list of activated AI/ML functions to the above network. A method implemented by a wireless transceiver unit (WTRU) within a network, including
As a wireless transceiver unit (WTRU) within a network, The above WTRU includes at least one processor, and The above at least one processor is: Receive configuration information from the above network, including information regarding artificial intelligence/machine learning (AI/ML) functions to be supported by the WTRU; Receive an activation indication from the network related to the activation of two or more AI/ML functions by the above WTRU; Based on the conditions, it is determined that at least one first AI/ML function among the two or more AI/ML functions can be supported by the WTRU, and at least one second AI/ML function among the two or more AI/ML functions cannot be supported by the WTRU; Activating at least the first AI/ML function mentioned above; To transmit a mark to the above network - the mark includes information regarding at least the first activated AI/ML function - A wireless transceiver unit (WTRU) within a network that is configured.
In Paragraph 7, The above conditions are: Available processing power of WTRU; Available storage capacity of WTRU; Radio conditions observed by WTRU; and Channel conditions observed by WTRU A wireless transceiver unit (WTRU) in a network comprising at least one of the following.
In paragraph 8, A wireless transceiver unit (WTRU) in a network, wherein the above conditions further include the priority of the AI/ML functions as indicated in the above configuration information.
In Paragraph 7, A wireless transceiver unit (WTRU) in a network, wherein the above configuration information comprises at least one of the priority of the AI/ML functions to be supported by the WTRU; the periodicity of the evaluation of the AI/ML functions to be supported by the WTRU; and a reporting configuration for transmitting the indication to the network.
In any one of paragraphs 7 through 9, A wireless transceiver unit (WTRU) in a network, wherein the above configuration information includes the priority and reporting configuration of the AI/ML functions to be supported by the WTRU, and the WTRU reports to the network priority AI/ML functions that cannot be activated due to the conditions and for which an activation indication is received according to the reporting configuration.
In Paragraph 7, The above configuration information includes the periodicity of the evaluation by the WTRU of the AI/ML functions supported by the WTRU, and The above at least one processor, according to the periodicity of the above evaluation: Performing an evaluation of AI/ML functions supported by the above WTRU; Based on the above evaluation, at least one supported AI/ML function is enabled and unsupported AI/ML functions are disabled; To transmit a list of activated AI/ML functions to the above network A wireless transceiver unit (WTRU) within a network that is configured.

Description

Method, architecture, device, and system for artificial intelligence/machine learning functions in a wireless transceiver unit Cross-reference of related applications This application claims the benefit of U.S. provisional patent application No. 63/540,464 filed September 26, 2023, the full text of which is incorporated herein by reference. The present disclosure generally relates to the fields of communications, software, and encoding, including methods, architectures, devices, and systems related to Artificial Intelligence/Machine Learning (AI/ML) operations for wireless transmit-receive units (WTRUs) in wireless networks, for example. It is desirable to address some of the challenges faced by AI/ML support in wireless networks. In the following, methods and apparatus for improving handover and AI/ML function support for wireless transceiver units and base stations, claimed pursuant to the appended claims, are defined and described. This can be understood in more detail from the following detailed description, which is given as an example together with the drawings attached herein. The illustrations in such drawings are examples, as with the detailed description. As such, the drawings and the detailed description should not be interpreted as limiting, and other equally effective examples are possible and probable. Also, similar reference numbers ("ref.") in the illustrations indicate similar elements, where: FIG. 1a is a system diagram illustrating an exemplary communication system; FIG. 1b is a system diagram illustrating an exemplary wireless transceiver unit (WTRU) that can be used within the communication system exemplified in FIG. 1a; FIG. 1c is a system diagram illustrating an exemplary radio access network (RAN) and an exemplary core network (CN) that can be used within the communication system illustrated in FIG. 1a; FIG. 1d is a system diagram illustrating additional exemplary RAN and additional exemplary CN that can be used within the communication system illustrated in FIG. 1a; FIG. 2 is a sequence chart illustrating legacy capability reporting by WTRU within a network; FIG. 3 is a sequence chart for the handover of a WTRU within a network from a source network node to a target network node according to an embodiment; FIG. 4 is a sequence chart for the handover of a WTRU within a network from a source network node to a target network node according to an embodiment; FIG. 5 is a flowchart of a method according to an embodiment; FIG. 6 is a flowchart of a method according to an embodiment; FIG. 7 is a flowchart of a method according to an embodiment; FIG. 8 is a flowchart of a method according to an embodiment. In the following detailed description, numerous specific details are provided to provide a sufficient understanding of the embodiments and/or examples disclosed herein. However, it will be understood that such embodiments and examples may be practiced without some or all of the specific details provided herein. In other cases, well-known methods, procedures, components, and circuits are not described in detail so as not to obscure the following description. Furthermore, embodiments and examples not specifically described herein may be practiced in place of, or in combination with, the embodiments and other examples described, disclosed, or otherwise provided (collectively referred to as “provided”) herein. Although various embodiments are described and/or claimed herein in which a device, system, device, etc., and/or any element thereof performs an operation, process, algorithm, function, etc., and/or any part thereof, it should be understood that any embodiment described and/or claimed herein is configured such that any device, system, device, etc., and/or any element thereof performs any operation, process, algorithm, function, etc., and/or any part thereof. Abbreviations and Acronyms ACK Acknowledgement AI Artificial Intelligence BLER Block Error Rate BM Beam Management BWP Bandwidth Part CQI Channel Quality Indicator C-RNTI Cell-RNTI CSI Channel State Information DL Downlink; Deep Learning DNN Deep Neural Network HIT Handover Interruption Time HO Handover LPP LTE Positioning Protocol LTE Long Term Evolution, for example, 3GPP LTE R8 or higher Layer1-RSRP MAC CE MAC control element ML Machine Learning NACK Negative ACK NR New Radio NW Network PDU Packet Data Unit PMI Precoding Matrix Indicator PRS Positioning Reference Signal RACH Random Access Channel (or Procedure) RI Rank Indicator RNTI Radio Network Temporary Identifier RRC Radio Resource Control RS Reference Signal RSRP Reference Signal Received Power RSRQ Reference Signal Received Quality RSSI Received Signal Strength Indicator SINR Signal-to-Interference-plus-Noise Ratio UE User Equipment (Refer to WTRU) UL Uplink WTRU Wireless Transmit-Receive Unit (See UE) Exemplary communication system The methods, devices, and systems provided herein are highly suitable for communications involving both wired