US-12627974-B2 - Updated artificial intelligence or machine learning capabilities reporting

Abstract

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may transmit an update to a previously reported set of UE artificial intelligence (AI) or machine learning (ML) capabilities. The UE may receive a configuration associated with performance of UE AI or ML operations based at least in part on the update. Numerous other aspects are described.

Inventors

• Rajeev Kumar
• Aziz Gholmieh
• Xipeng Zhu
• Gavin Bernard Horn
• Shankar Krishnan

Assignees

• QUALCOMM INCORPORATED

Dates

Publication Date

20260512

Application Date

20220509

Claims (20)

1. 1 . A user equipment (UE) for wireless communication, comprising: one or more memories; and one or more processors, coupled to the one or more memories, individually or collectively configured to: receive radio resource control (RRC) signaling indicating that the UE is to transmit updates to UE artificial intelligence (AI) or machine learning (ML) capabilities via UE assistance information (UAI); transmit, via the UAI and based at least in part on the RRC signaling, an update to a previously reported set of the UE AI or ML capabilities, wherein the update indicates one or more UE AI or ML models affected by the update; and receive a configuration associated with performance of UE AI or ML operations based at least in part on the update, wherein the configuration indicates to cease one or more of the UE AI or ML operations indicated as being affected by the update.
2. 2 . The UE of claim 1 , wherein the one or more processors, to transmit the update, are configured to: transmit the update via dynamic capability update signaling.
3. 3 . The UE of claim 2 , wherein the dynamic capability update signaling comprises one or more of: RRC signaling, an indication of whether the UE supports one or more UE AI or ML operations, autonomous signaling, or trigger-condition-based signaling.
4. 4 . The UE of claim 1 , wherein the update further indicates one or more of: whether the UE supports performance of one or more UE AI or ML operations, one or more additional UE AI or ML models unaffected by the update, or performance parameter updates for the one or more UE AI or ML models, the performance parameter updates supporting satisfaction of timing requirements associated with the one or more UE AI or ML models.
5. 5 . The UE of claim 1 , wherein the update further indicates one or more of: one or more model combinations that the UE supports based at least in part on the update, performance parameters associated with the one or more model combinations that the UE supports based at least in part on the update, one or more model combinations that the UE does not support based at least in part on the update, or performance parameters associated with the one or more model combinations that the UE does not support based at least in part on the update.
6. 6 . The UE of claim 1 , wherein the one or more processors, to transmit the update, are configured to transmit the update based at least in part on detection that the UE is unable to satisfy a timing requirement associated with one or more UE AI or ML operations that the UE is configured to perform based at least in part on the previously reported set of UE AI or ML capabilities.
7. 7 . The UE of claim 1 , wherein the one or more processors are further configured to: receive a request for transmitting the update.
8. 8 . The UE of claim 1 , wherein the RRC signaling further indicates one or more of: an update prohibition timer that indicates a minimum amount of time between transmissions of updates to the UE AI or ML capabilities, or one or more trigger conditions for the transmissions of updates to the UE AI or ML capabilities.
9. 9 . The UE of claim 1 , wherein the one or more processors are further configured to: detect a change in the UE AI or ML capabilities, wherein transmission of the update is based at least in part on the change in the UE AI or ML capabilities.
10. 10 . The UE of claim 9 , wherein the transmission of the update is based at least in part on the change in the UE AI or ML capabilities satisfying a threshold amount of change.
11. 11 . The UE of claim 1 , wherein the configuration further indicates updated configurations of the UE AI or ML operations.
12. 12 . A network node for wireless communication, comprising: one or more memories; and one or more processors, coupled to the one or more memories, individually or collectively configured to: transmit radio resource control (RRC) signaling indicating that a user equipment (UE) is to transmit updates to UE artificial intelligence (AI) or machine learning (ML) capabilities via UE assistance information (UAI); receive, via the UAI and based at least in part on the RRC signaling, an update to a previously reported set of the UE AI or ML capabilities, wherein the update indicates one or more UE AI or ML models affected by the update; and transmit a configuration associated with performance of UE AI or ML operations based at least in part on the update, wherein the configuration indicates to cease one or more of the UE AI or ML operations indicated as being affected by the update.
13. 13 . The network node of claim 12 , wherein the one or more processors, to receive the update, are configured to: receive the update via dynamic capability update signaling.
14. 14 . The network node of claim 13 , wherein the dynamic capability update signaling comprises one or more of: RRC signaling, an indication of whether the UE supports one or more UE AI or ML operations, autonomous signaling, or trigger-condition-based signaling.
15. 15 . The network node of claim 12 , wherein the update further indicates one or more of: whether the UE supports performance of one or more UE AI or ML operations, one or more additional UE AI or ML models unaffected by the update, or performance parameter updates for the one or more UE AI or ML models, the performance parameter updates supporting satisfaction of timing requirements associated with the one or more UE AI or ML models.
16. 16 . The network node of claim 12 , wherein the update further indicates one or more of: one or more model combinations that the UE supports based at least in part on the update, performance parameters associated with the one or more model combinations that the UE supports based at least in part on the update, one or more model combinations that the UE does not support based at least in part on the update, or performance parameters associated with the one or more model combinations that the UE does not support based at least in part on the update.
17. 17 . The network node of claim 12 , wherein the one or more processors, to receive the update, are configured to receive the update based at least in part on detection that the UE is unable to satisfy a timing requirement associated with one or more UE AI or ML operations that the UE is configured to perform based at least in part on the previously reported set of UE AI or ML capabilities.
18. 18 . The network node of claim 12 , wherein the one or more processors are further configured to: transmit a request for transmitting the update.
19. 19 . The network node of claim 12 , wherein the RRC signaling further indicates one or more of: an update prohibition timer that indicates a minimum amount of time between transmissions of updates to the UE AI or ML capabilities, or one or more trigger conditions for the transmissions of updates to the UE AI or ML capabilities.
20. 20 . The network node of claim 12 , wherein the configuration further indicates updated configurations of the UE AI or ML operations.

Description

FIELD OF THE DISCLOSURE Aspects of the present disclosure generally relate to wireless communication and to techniques and apparatuses for updated artificial intelligence or machine learning capabilities reporting. BACKGROUND Wireless communication systems are widely deployed to provide various telecommunication services such as telephony, video, data, messaging, and broadcasts. Typical wireless communication systems may employ multiple-access technologies capable of supporting communication with multiple users by sharing available system resources (e.g., bandwidth, transmit power, or the like). Examples of such multiple-access technologies include code division multiple access (CDMA) systems, time division multiple access (TDMA) systems, frequency division multiple access (FDMA) systems, orthogonal frequency division multiple access (OFDMA) systems, single-carrier frequency division multiple access (SC-FDMA) systems, time division synchronous code division multiple access (TD-SCDMA) systems, and Long Term Evolution (LTE). LTE/LTE-Advanced is a set of enhancements to the Universal Mobile Telecommunications System (UMTS) mobile standard promulgated by the Third Generation Partnership Project (3GPP). A wireless network may include one or more base stations (e.g., network nodes) that support communication for a user equipment (UE) or multiple UEs. A UE may communicate with a base station via downlink communications and uplink communications. “Downlink” (or “DL”) refers to a communication link from the base station to the UE, and “uplink” (or “UL”) refers to a communication link from the UE to the base station. The above multiple access technologies have been adopted in various telecommunication standards to provide a common protocol that enables different UEs to communicate on a municipal, national, regional, and/or global level. New Radio (NR), which may be referred to as 5G, is a set of enhancements to the LTE mobile standard promulgated by the 3GPP. NR is designed to better support mobile broadband internet access by improving spectral efficiency, lowering costs, improving services, making use of new spectrum, and better integrating with other open standards using orthogonal frequency division multiplexing (OFDM) with a cyclic prefix (CP) (CP-OFDM) on the downlink, using CP-OFDM and/or single-carrier frequency division multiplexing (SC-FDM) (also known as discrete Fourier transform spread OFDM (DFT-s-OFDM)) on the uplink, as well as supporting beamforming, multiple-input multiple-output (MIMO) antenna technology, and carrier aggregation. As the demand for mobile broadband access continues to increase, further improvements in LTE, NR, and other radio access technologies remain useful. SUMMARY Some aspects described herein relate to a method of wireless communication performed by a user equipment (UE). The method may include transmitting an update to a previously reported set of UE artificial intelligence (AI) or machine learning (ML) capabilities. The method may include receiving a configuration associated with performance of UE AI or ML operations based at least in part on the update. Some aspects described herein relate to a method of wireless communication performed by a base station. The method may include receiving an update to a previously reported set of UE AI or ML capabilities. The method may include transmitting a configuration associated with performance of UE AI or ML operations based at least in part on the update. Some aspects described herein relate to a UE for wireless communication. The user equipment may include a memory and one or more processors coupled to the memory. The one or more processors may be configured to transmit an update to a previously reported set of UE AI or ML capabilities. The one or more processors may be configured to receive a configuration associated with performance of UE AI or ML operations based at least in part on the update. Some aspects described herein relate to a base station for wireless communication. The base station may include a memory and one or more processors coupled to the memory. The one or more processors may be configured to receive an update to a previously reported set of UE AI or ML capabilities. The one or more processors may be configured to transmit a configuration associated with performance of UE AI or ML operations based at least in part on the update. Some aspects described herein relate to a non-transitory computer-readable medium that stores a set of instructions for wireless communication by a UE. The set of instructions, when executed by one or more processors of the UE, may cause the UE to transmit an update to a previously reported set of UE AI or ML capabilities. The set of instructions, when executed by one or more processors of the UE, may cause the UE to receive a configuration associated with performance of UE AI or ML operations based at least in part on the update. Some aspects described herein relate to a non-transitory com