QUERY-BASED CHANNEL STATE INFORMATION FEEDBACK DECODING FOR CROSS-NODE MACHINE LEARNING

    公开(公告)号:US20250062810A1

    公开(公告)日:2025-02-20

    申请号:US18450821

    申请日:2023-08-16

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a network node, decoder configuration information associated with a transmitter neural network configured to be used to generate at least one latent vector corresponding to one or more computation tasks of a plurality of computation tasks associated with a query-based cross-node machine learning system. The UE may receive, from the network node, query configuration information associated with a query-based decoder. The UE may transmit, to the network node and based at least in part on instantiation of the transmitter neural network by the UE, the at least one latent vector. Numerous other aspects are described.

    TWO STAGE MACHINE LEARNING BASED CHANNEL STATE FEEDBACK

    公开(公告)号:US20240421875A1

    公开(公告)日:2024-12-19

    申请号:US18335726

    申请日:2023-06-15

    Abstract: Methods, systems, and devices for wireless communication are described. A user equipment (UE) may select a non-Discrete Fourier Transform (non-DFT) codebook of a set of non-DFT codebooks associated with a channel state feedback message. The UE may determine a set of singular vectors associated with the non-DFT codebook based on a first machine learning model, where the set of singular vectors corresponds to a subspace associated with the non-DFT codebook. The UE may compress the non-DFT codebook, the set of singular vectors, or both, based on a second machine learning model. The UE may transmit the channel state feedback message including the compressed non-DFT codebook, the compressed set of singular vectors, or both.

    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.

Patent Agency Ranking