APPARATUS FOR RADIO ACCESS NETWORK DATA COLLECTION

    公开(公告)号:US20220295324A1

    公开(公告)日:2022-09-15

    申请号:US17636343

    申请日:2019-09-13

    Abstract: There is provided an apparatus comprising means for: configuring a measurement collection for one or more pre-determined optimization problems at a first data producer; transmitting a first measurement request to the first data producer, wherein the first measurement request is indicative of requested measurement(s) for the one or more pre-determined optimization problems, time sampling indication and granularity; receiving a measurement response comprising first measurement results corresponding to the first measurement request; and providing the first measurement results to one or more optimization algorithms for solving the one or more pre-determined optimization problems.

    REPORT HANDLING IN MULTIPLE CONNECTION FAILURES

    公开(公告)号:US20250098008A1

    公开(公告)日:2025-03-20

    申请号:US18727263

    申请日:2023-01-09

    Abstract: Embodiments of the present disclosure relate to devices, methods, apparatuses and computer readable storage media of report handling in multiple connection failure. The method comprises receiving, from a second device, a request associated with providing a plurality of CEF reports from the first device; and transmitting, to the second device based on the request, the plurality of CEF reports wherein information related to one or more RACH reports corresponding to the plurality of CEF reports is excluded within the plurality of CEF reports.

    APPARATUSES, METHODS AND COMPUTER PROGRAMS FOR EXCHANGING IMPACT INFORMATION

    公开(公告)号:US20250048216A1

    公开(公告)日:2025-02-06

    申请号:US18762175

    申请日:2024-07-02

    Abstract: According to various, but not necessarily all, examples there is provided an apparatus for a network node, the apparatus comprising: means for sending a message to a target network node, the message comprising a request for measurement information of a measurement on an energy cost of the target network node, and the message comprising a message field requesting impact information of an impact of at least one other network node on the measurement; means for receiving from the target network node the measurement information and the impact information; and means for performing, based on the measurement information and the impact information, at least one action related to traffic offloading.

    VALIDITY INDICATION AS A FUNCTION OF CONFIDENCE LEVEL

    公开(公告)号:US20240155377A1

    公开(公告)日:2024-05-09

    申请号:US17980266

    申请日:2022-11-03

    CPC classification number: H04W24/02

    Abstract: Systems, methods, apparatuses, and computer program products for indicating validity as a function of confidence level. A requesting network entity may receive a prediction request from a requesting network entity that comprises timing information indicating when a prediction needs to be obtained. The receiving entity may then transmit a response to the requesting network entity associated with the requested prediction.

    AI/ML CONFIGURATION FEEDBACK
    37.
    发明公开

    公开(公告)号:US20240113796A1

    公开(公告)日:2024-04-04

    申请号:US18477156

    申请日:2023-09-28

    CPC classification number: H04B17/3913 H04B17/201

    Abstract: Apparatus comprising:



    one or more processors, and memory storing instructions that, when executed by the one or more processors, cause the apparatus to perform:
    monitoring whether a terminal suffers a performance issue due to an artificial intelligence/machine learning operation performed by the terminal;
    performing an action related to the artificial intelligence/machine learning operation to remove or reduce the performance issue if the terminal suffers the performance issue due to the artificial intelligence/machine learning operation.

    ENABLEMENT OF FEDERATED MACHINE LEARNING FOR TERMINALS TO IMPROVE THEIR MACHINE LEARNING CAPABILITIES

    公开(公告)号:US20240028961A1

    公开(公告)日:2024-01-25

    申请号:US18266004

    申请日:2021-01-25

    CPC classification number: G06N20/00

    Abstract: There are provided measures for enablement of federated machine learning for terminals to improve their machine learning capabilities. Such measures exemplarily comprise, at a terminal, receiving a configuration indicative of an instruction to participate in federated learning of a global machine learning model, the configuration including timing information related to said federated learning, and performing, based on said configuration, a machine learning process based on undertaken network performance related measurements, wherein said timing information includes a time limit with respect to a local machine learning model resulting from said machine learning process, and said time limit is a specification of a moment in time by when said local machine learning model is to be completed or a specification of a moment in time by when transmission of said local machine learning model is to be completed, and wherein said configuration is a minimization of drive tests configuration.

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