ADAPTIVE PERFORMANCE MONITORING
    11.
    发明申请

    公开(公告)号:US20250048160A1

    公开(公告)日:2025-02-06

    申请号:US18787591

    申请日:2024-07-29

    Abstract: Solutions for adaptive performance monitoring are disclosed. A solution comprises maintaining (200) ability to collect network performance data utilising a collecting policy from more than one collecting policy, receiving (202) from a network element a request to apply a given collecting policy, applying (204) the requested collecting policy in collecting network performance data and transmitting (206) network performance data to network based on the applied policy.

    MANAGING LISTEN BEFORE TALK
    13.
    发明公开

    公开(公告)号:US20240147528A1

    公开(公告)日:2024-05-02

    申请号:US18548182

    申请日:2022-03-02

    CPC classification number: H04W74/0808 H04W74/002

    Abstract: Examples of the present disclosure relate to management of Listen-Before-Talk. Certain examples provide a centralized unit 210 of an access node 120 for use in a network comprising at least the centralized unit 210 and a distributed unit 220, the centralized unit 120 comprising means configured to: receive information 301 indicative of a quality of a channel; and cause an adaptation 302 of a Listen-Before-Talk state 501 of at least one network node based 220/110, at least in part, on the received information 301.

    AI/ML OPERATION IN SINGLE AND MULTI-VENDOR SCENARIOS

    公开(公告)号:US20240112087A1

    公开(公告)日:2024-04-04

    申请号:US18475873

    申请日:2023-09-27

    CPC classification number: G06N20/00

    Abstract: Method comprising:



    providing, to a second node different from a first node, for each of one or more machine learning models, a respective support indication, wherein the respective support indication indicates that the first node supports the respective machine learning model, and the respective support indication comprises an identifier of the respective machine learning model and at least one capability of the respective machine learning model;
    monitoring whether the first node receives, from the second node for at least one of the one or more machine learning models, a configuration request requesting to configure the respective machine learning model according to a respective requested configuration;
    configuring the at least one of the one or more machine learning models according to the respective requested configuration if the first node receives the configuration request for the at least one of the one or more machine learning models from the second node.

    ENHANCED REPORT FOR RANDOM ACCESS CHANNEL
    15.
    发明公开

    公开(公告)号:US20230156806A1

    公开(公告)日:2023-05-18

    申请号:US17907584

    申请日:2020-04-09

    CPC classification number: H04W74/0833 H04W74/008

    Abstract: Example embodiments of the present disclosure relate to devices, methods, apparatuses and computer readable storage media of enhancing a report for random access channel (RACH). The method comprises in accordance with a determination that a random access attempt in a random access process for accessing a second device based on configuration information is performed, determining an entry for recording the random access attempt, the entry at least comprising fallback information indicating whether a change associated with the random access attempt has occurred; generating a report for the random access process at least based on the entry; and causing the report to be transmitted to the second device. In this way, with the UE RACH report, the network device may achieve a targeted optimization for the configuration for RA process, which may improve the efficiency of the RA process and decrease the cost due to a multiple of fallback.

    CONDITIONAL HANDOVER
    17.
    发明公开

    公开(公告)号:US20240292288A1

    公开(公告)日:2024-08-29

    申请号:US18585987

    申请日:2024-02-23

    CPC classification number: H04W36/0072 H04W36/08 H04W36/324 H04W36/362

    Abstract: A network node comprising:



    means for providing to one or more UE, a UE configuration for conditional handover from a serving cell to one or more target cells, wherein the UE configuration for conditional handover configures one or more conditions for executing conditional handover;
    means for providing to the one or more target cells, a network configuration for conditional handover from a serving cell to the one or more target cells, wherein the network configuration for conditional handover configures at least one or more network resources for conditional handover; wherein the network configuration for conditional handover provides at least an estimated arrival timing for a UE arriving for handover at a target cell.

    DISTRIBUTED MACHINE LEARNING SOLUTION FOR ROGUE BASE STATION DETECTION

    公开(公告)号:US20240121678A1

    公开(公告)日:2024-04-11

    申请号:US18480318

    申请日:2023-10-03

    CPC classification number: H04W36/00833 H04W36/0085

    Abstract: An apparatus configured to: obtain an indication of partitions of a machine learning model corresponding to respective ones of the one or more groups; transmit, to the respective ones of the plurality of user equipments, a corresponding partition, of the partitions of the machine learning model; transmit, to the plurality of user equipments, an indication to record measurements for the first cell; receive, from at least one of the plurality of user equipments, at least one message regarding a handover failure, wherein the at least one message comprises a message generated using a first partition of the partitions of the machine learning model; and determine, with a second partition of the partitions of the machine learning model, whether the first cell is a rogue base station based, at least partially, on a plurality of detection reports.

    RADIO RESOURCE CONTROL PROCEDURES FOR MACHINE LEARNING

    公开(公告)号:US20220279341A1

    公开(公告)日:2022-09-01

    申请号:US17637228

    申请日:2019-09-13

    Abstract: An example method, apparatus, and computer-readable storage medium are provided for radio resource control (RRC) procedures for machine learning (ML). In an example implementation, the method may include receiving, by a user equipment (UE), machine learning (ML) configuration from a network node; collecting, by the user equipment (UE), machine learning (ML) data based at least on the machine learning (ML) configuration received from the network node, the machine learning (ML) data being collected from one or more layers of the user equipment (UE) in a coordinated manner; and transmitting, by the user equipment (UE), the collected machine learning (ML) data to the network node. In another example implementation, the method may include transmitting, by a network node, machine learning (ML) configuration to a user equipment (UE); and receiving, by the network node, machine learning (ML) data from the user equipment (UE), the machine learning (ML) data received in response to the machine learning (ML) configuration transmitted to the user equipment (UE).

    DISTINCTION OF MINIMIZATION DRIVE TEST LOGGING THROUGH DIFFERENT RADIO RESOURCE CONTROLLER STATES

    公开(公告)号:US20220201526A1

    公开(公告)日:2022-06-23

    申请号:US17603783

    申请日:2019-05-02

    Abstract: Systems, methods, apparatuses, and computer program products for distinguishing minimization of drive tests (MDT) logging through different radio resource controller (RRC) states. One method may include receiving, from a network element, a logged measurement configuration comprising specific content for a user equipment depending on a connection state of the user equipment. The method may also include validating the logged measurement configuration, wherein the validating is embodied by the network element prior to transitioning to a different user equipment state, or by a user equipment after entering a logging state, for which the logged measurement configuration was designated. The method may further include performing logging of a measurement according to the content of the logged measurement configuration. In addition, the method may include tagging the logged measurement. The method may also include transmitting the tagged logged measurement to the network element.

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