MODEL IDENTIFICATION USING USER EQUIPMENT CAPABILITY INDICATOR

    公开(公告)号:US20240397306A1

    公开(公告)日:2024-11-28

    申请号:US18592990

    申请日:2024-03-01

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may transmit a UE capability reporting message including information associated with identifying a set of UE conditions associated with a first set of functionalities, wherein the first set of functionalities corresponds to a set of model features. The UE may receive, based at least in part on transmitting the UE capability reporting message, control signaling identifying a second set of functionalities that is a subset of the first set of functionalities. Numerous other aspects are described.

    COMPRESSING AND REPORTING PRS/SRS MEASUREMENTS FOR LMF-SIDED AI/ML POSITIONING

    公开(公告)号:US20240388472A1

    公开(公告)日:2024-11-21

    申请号:US18320918

    申请日:2023-05-19

    Abstract: Aspects presented herein may improve the efficiency and performance of artificial intelligence (AI)/machine learning (ML) (AI/ML) positioning by enabling a user equipment (UE) to compress downlink (DL) reference signal measurements to reduce reporting overhead for the DL reference signal measurements. In one aspect, a UE performs at least one channel impulse response (CIR) measurement or at least one channel frequency response (CFR) measurement for a set of positioning reference signals (PRSs). The UE compresses the at least one CIR measurement or the at least one CFR measurement for the set of PRSs. The UE reports, for a network entity, one or more of the at least one compressed CIR measurement or the at least one compressed CFR measurement for the set of PRSs.

    FRAMEWORK FOR SEMANTIC ENCODING AND DECODING IN A WIRELESS COMMUNICATION NETWORK

    公开(公告)号:US20240306000A1

    公开(公告)日:2024-09-12

    申请号:US18179953

    申请日:2023-03-07

    CPC classification number: H04W16/18 G06F40/30

    Abstract: Certain aspects of the present disclosure provide techniques for semantic communication. A method for wireless communications includes obtaining, by a semantic encoder, a set of real values for transmission to a receiving device; encoding, by the semantic encoder, the set of real values based on a semantic model and a first dimension of a set of dimensions, wherein each different dimension in the set of dimensions corresponds to a different number of real values to output; outputting an encoded set of real values; outputting the encoded set of real values for transmission to the receiving device over a wireless communication channel; obtaining feedback from the receiving device; and using a second dimension of the set of dimensions based on the feedback.

    ADAPTATION OF ARTIFICIAL INTELLIGENCE/MACHINE LEARNING MODELS BASED ON SITE-SPECIFIC DATA

    公开(公告)号:US20240057021A1

    公开(公告)日:2024-02-15

    申请号:US18446320

    申请日:2023-08-08

    CPC classification number: H04W64/003 H04W72/046

    Abstract: Systems and techniques for wireless communications are described herein. For example, a process for wireless communications at a first network entity include obtaining site-specific data associated with a geographic location and adapting, at the first network entity, a machine learning model based on the site-specific data to generate an updated machine learning model for estimating or predicting of at least one characteristic associated with wireless communications between the first network entity and one or more network entities. The first network entity can experience a trigger event which causes the first network entity to transmit a request for the site-specific data. The triggering event can be based on at least one of a location of the first network entity in the geographic location or the first network entity moving to the geographic location or based on other factors such as a change in a physical characteristic of the location.

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