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    BEAM PREDICTION BY USER EQUIPMENT USING ANGLE ASSISTANCE INFORMATION
    2.
    发明公开
    BEAM PREDICTION BY USER EQUIPMENT USING ANGLE ASSISTANCE INFORMATION 审中-公开

    公开(公告)号：US20240056205A1

    公开(公告)日：2024-02-15

    申请号：US17886427

    申请日：2022-08-11

    Applicant: NOKIA TECHNOLOGIES OY

    Inventor： Andrea BONFANTE ,  Qiping ZHU ,  Frederick VOOK

    IPC: H04B17/373

    CPC classification number: H04B17/373

    Abstract: Systems, methods, apparatuses, and computer program products for beam prediction by a user equipment using angle assistance information are provided. For example, a method can include receiving assistance information from a network and measuring a plurality of reference signal transmissions from the network. The method can also include predicting best beam or reference signal received power using a model at a user equipment. The assistance information and the measurements of the plurality of reference signal transmissions are input to the model. Reporting the best beam or reference signal received power as predicted to the network can also be performed.

    DEVICES, METHODS AND APPARATUSES FOR BEAM REPORTING
    4.
    发明公开
    DEVICES, METHODS AND APPARATUSES FOR BEAM REPORTING 审中-公开

    公开(公告)号：US20240098543A1

    公开(公告)日：2024-03-21

    申请号：US18457892

    申请日：2023-08-29

    Applicant: Nokia Technologies Oy

    Inventor： Keeth Saliya Jayasinghe LADDU ,  Qiping ZHU ,  Andrea BONFANTE

    IPC: H04W24/10 ,  H04W24/08

    CPC classification number: H04W24/10 ,  H04W24/08

    Abstract: Embodiments of the present disclosure disclose devices, methods and apparatuses for a beam reporting. A terminal device receives a beam reporting configuration from a network device. The beam reporting configuration indicates at least one set of beams for at least one of beam measurements or beam predictions. Each beam of at least one set of beams is associated with a cell of multiple cells which are able to be measured by the terminal device. Then, the terminal device performs a reporting of at least one beam associated with the at least one set of beams based on the beam reporting configuration. The at least one beam comprises a predicted beam which is associated to a cell of multiple cells.

    TEMPORAL DOMAIN OVERLAPPED PREDICTION WITH UE MODEL MONITORING ENHANCEMENT
    5.
    发明申请
    TEMPORAL DOMAIN OVERLAPPED PREDICTION WITH UE MODEL MONITORING ENHANCEMENT 有权

    公开(公告)号：US20250047361A1

    公开(公告)日：2025-02-06

    申请号：US18765761

    申请日：2024-07-08

    Applicant: Nokia Technologies Oy

    Inventor： Tachporn SANGUANPUAK ,  Frederick VOOK ,  Amir Mehdi AHMADIAN TEHRANI ,  Andrea BONFANTE ,  Keeth Saliya JAYASINGHE LADDU

    IPC: H04B7/08

    Abstract: This document discloses a method and an apparatus to perform using a predicted sequence of beam measurement outputs for at least one observation window associated with at least one prediction window providing reference signal received power measurements to predict a beam prediction output; identifying that a prediction window of the at least one prediction window is overlapped with at least a portion of an observation window of the at least one observation window over a time period; and comparing the beam prediction output during the overlapped portion with measurements of the observation window during the overlapped portion to perform long term real time monitoring to determine at least one prediction output for use in a next time instant, wherein the determining is based on a predicted reference signal received power of the at least one prediction output being above a threshold.

    COMMUNICATION FUNCTIONALITY VALIDATION
    7.
    发明申请
    COMMUNICATION FUNCTIONALITY VALIDATION 有权

    公开(公告)号：US20250056244A1

    公开(公告)日：2025-02-13

    申请号：US18797517

    申请日：2024-08-08

    Applicant: Nokia Technologies Oy

    Inventor： Fahad SYED MUHAMMAD ,  Tachporn SANGUANPUAK ,  Frederick VOOK ,  Amir Mehdi AHMADIAN TEHRANI ,  Dimitri GOLD ,  Andrea BONFANTE

    IPC: H04W16/28 ,  H04W16/18

    Abstract: Embodiments of the present disclosure relate to apparatuses, methods, devices and computer readable storage medium for communication functionality validation. In a method, a first apparatus receives, from a second apparatus, a first performance metric of a first outcome of a communication functionality based on a first set of communication parameters. The first apparatus receives, from the second apparatus, a reference performance metric of a reference outcome of the communication functionality based on a set of reference communication parameters. The first apparatus validates the communication functionality based on a threshold and a first difference between the first performance metric and the reference performance metric.

    MACHINE LEARNING MODEL SELECTION FOR BEAM PREDICTION FOR WIRELESS NETWORKS
    9.
    发明公开
    MACHINE LEARNING MODEL SELECTION FOR BEAM PREDICTION FOR WIRELESS NETWORKS 审中-公开

    公开(公告)号：US20240107347A1

    公开(公告)日：2024-03-28

    申请号：US18468214

    申请日：2023-09-15

    Applicant: Nokia Technologies Oy

    Inventor： Rustam PIRMAGOMEDOV ,  Andrea BONFANTE ,  Laxmanarao GUMASTE

    IPC: H04W24/08 ,  H04W24/02

    CPC classification number: H04W24/08 ,  H04W24/02

    Abstract: A method includes beam prediction inference using a first machine learning (ML) model based algorithm that uses a first quantity of reference signal (RS) measurements; transmitting an indication that the first user device is using the first ML model based algorithm that uses the first quantity of RS measurements; receiving, based on beam change dynamics event information received by the network node from one or more other user devices that have one or more corresponding conditions within a threshold to the first user device, a request for the first user device to either: change to a non-ML model based algorithm to perform beam selection or a second ML model based algorithm that uses a second quantity of reference signal measurements to perform beam prediction inference, wherein the second quantity is different than the first quantity, or concurrently perform beam prediction inferences using the first and second ML model based algorithms.

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