METHOD AND APPARATUS FOR BEAM FAILURE RECOVERY

    公开(公告)号:US20240072878A1

    公开(公告)日:2024-02-29

    申请号:US18464215

    申请日:2023-09-09

    Applicant: MEDIATEK INC.

    CPC classification number: H04B7/088 H04L5/0051 H04W56/001 H04W76/19 H04W80/02

    Abstract: A unified solution to support all PCell, SCell, and per-TRP based beam failure recovery (BFR) procedure is proposed, with less standard impact and reduced latency. In a first novel aspect, a set of reference signals (RSs) for BFD is configured for each BWP of a serving cell, and a maximum number of BFD RSs (N) per TRP for each BWP of a serving cell is configured. In a second novel aspect, for single DCI multi-TRP, the BFD RSs can be updated via MAC CE to reduce latency. In a third novel aspect, new RRC parameters for BFD RSs and candidate beam RSs are configured, with different sets of SSB/CSI-RS resources associated to each TRP. Specifically, an additional lists of SSB/CSI-RS resource set is defined for each corresponding TRP.

    Techniques For Channel State Information (CSI) Pre-Processing

    公开(公告)号:US20240137139A1

    公开(公告)日:2024-04-25

    申请号:US18374139

    申请日:2023-09-28

    Applicant: MediaTek Inc.

    CPC classification number: H04B17/3913

    Abstract: Techniques pertaining to channeling state information (CSI) pre-processing are described. A user equipment (UE) that is in wireless communication with a base station node extracts eigenvectors (EVs) from CSI acquired by the UE. The UE generates pre-processed CSI for compression by a machine-learning (ML)-based encoder of the UE into CSI feedback for the base station node by at least performing one or more of a phase discontinuity compensation (PDC), a one-step polarization separation with re-ordering, or a two-step polarization separation that includes separation based on polarization type and separation by position on the EVs.

    Task-Aware Information Hiding
    4.
    发明申请

    公开(公告)号:US20250039063A1

    公开(公告)日:2025-01-30

    申请号:US18784044

    申请日:2024-07-25

    Applicant: MediaTek Inc.

    Abstract: Techniques pertaining to task-aware information hiding artificial intelligence/machine learning (AI/ML) models used in wireless communications are described. An apparatus performs task-aware information hiding or partial task-aware information hiding using an information hiding AI/ML model to embed information in a host data as a container. The apparatus then communicates with a network using the container which contains the embedded information.

    NETWORK-SIDE ARTIFICIAL INTELLIGENCE (AI) / MACHINE LEARNING (ML) MODEL MONITORING

    公开(公告)号:US20250038811A1

    公开(公告)日:2025-01-30

    申请号:US18780808

    申请日:2024-07-23

    Applicant: MEDIATEK INC.

    Abstract: In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be a base station. The base station receives a sounding reference signal (SRS) from a user equipment (UE). The base station estimates an uplink (UL) channel state information (CSI) based on the received SRS. The base station monitors the estimated UL CSI to track changes. The base station determines whether to update or switch an artificial intelligence (AI)/machine learning (ML) model used for downlink (DL) CSI compression based on the monitoring of the estimated UL CSI.

    METHOD AND APPARATUS FOR AI/ML BASED BEAM MANAGEMENT

    公开(公告)号:US20240196242A1

    公开(公告)日:2024-06-13

    申请号:US18529092

    申请日:2023-12-05

    Applicant: MEDIATEK INC.

    CPC classification number: H04W24/08 H04L41/16

    Abstract: A UE receives, from a base station, a first monitoring configuration for monitoring an artificial intelligence/machine learning (AI/ML) model for managing a set of beams. The UE measures a first subset of the set of beams. The UE performs inference using the AI/ML model based on measurements of the first subset to determine predication values of a second subset of the set of beams. The second subset is selected based on the first monitoring configuration. The UE measures the second subset of the set of beams to determine measured values of the second subset. The UE calculates one or more performance metrics based on the predication values and the measured values of the second subset. The one or more performance metrics are selected based on the first monitoring configuration.

    SPATIAL AND FREQUENCY DOMAIN BEAM MANAGEMENT USING TIME SERIES INFORMATION

    公开(公告)号:US20240106510A1

    公开(公告)日:2024-03-28

    申请号:US18369488

    申请日:2023-09-18

    Applicant: MEDIATEK INC.

    CPC classification number: H04B7/0639 H04B7/06958

    Abstract: In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be wireless equipment. The wireless equipment selects a first subset of beams to be utilized for beam management. The beams are from a set of first type of beams used for communication with a base station or a UE. The wireless equipment measures signals transmitted on a second subset of beams. The beams are from the set of first type of beams or from a set of second type of beams. The wireless equipment measures the signals over a time window. The wireless equipment inputs the measurements to a computational model. The wireless equipment receives predictions of channel measurements on the first subset of beams from the computational model.

    Techniques For Channel State Information (CSI) Compression

    公开(公告)号:US20240088965A1

    公开(公告)日:2024-03-14

    申请号:US18242090

    申请日:2023-09-05

    Applicant: MediaTek Inc.

    CPC classification number: H04B7/0626 G06N20/00 H04B7/0617

    Abstract: Techniques pertaining to channeling state information (CSI) compression are described. A user equipment (UE) that is in wireless communication with a base station node acquires channel state information (CSI) at least associated with the wireless communication. The UE further compresses the CSI into CSI feedback for the base station node via an artificial intelligence (AI)/machine-learning (ML)-based encoder that implements at least one of convolutional projection, expandable kernels, or multi-head re-attention (MHRA).

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