Connection behavior identification for wireless networks

    公开(公告)号:US11979754B2

    公开(公告)日:2024-05-07

    申请号:US17309823

    申请日:2018-12-22

    CPC classification number: H04W24/02 G06N20/00 H04W76/10

    Abstract: A method includes receiving, from a radio access network (RAN) node within a wireless network, connection event information for one or more user devices and associated channel condition information; and determining a connection behavior status of a user device based on at least a portion of the connection event information and associated channel condition information and a connection behavior status model, wherein the connection behavior status model provides a mapping or association between connection event information and associated channel condition information for one or more user devices and a connection behavior status.

    Power saving in radio access network

    公开(公告)号:US11765654B2

    公开(公告)日:2023-09-19

    申请号:US17976376

    申请日:2022-10-28

    CPC classification number: H04W52/0206 H04W24/10

    Abstract: To maximize power saving in a radio access network comprising cells, an optimal action amongst actions comprising switching on one or more cells, switching off one or more cells, and doing nothing is determined using a trained model, which maximizes a long term reward on tradeoff between throughput and power, the trained model taking as input a load estimate. The trained model may be updated online using measurement results on load, throughput and power consumption.

    SCell Selection and Optimization for Telecommunication Systems

    公开(公告)号:US20200252142A1

    公开(公告)日:2020-08-06

    申请号:US16856142

    申请日:2020-04-23

    Inventor: Anand Bedekar

    Abstract: UE-related measurements taken on a Pcell in a wireless communication system are formed into a set of data. The Pcell overlaps with Scell(s). The UE-related measurements on the Pcell are for a specific UE in the Pcell. Using a ML algorithm applied to the set of data, achievable channel quality is predicted for the specific UE for each of the Scell(s). The predicted achievable channel qualities are output for the specific UE to be used for Scell selection. At a RAN node, the set of data is sent toward an Scell prediction module for the module to determine information suitable to enable Scell selection for the specific UE. The RAN node receives information from the module allowing the RAN node to inform the selected UE of Scell(s) to be used for Scell selection for the specific UE. A node may train the ML algorithm using UE-related measurements on the Pcell.

    SCELL SELECTION AND OPTIMIZATION FOR TELECOMMUNICATION SYSTEMS

    公开(公告)号:US20200106536A1

    公开(公告)日:2020-04-02

    申请号:US16143776

    申请日:2018-09-27

    Inventor: Anand Bedekar

    Abstract: UE-related measurements taken on a Pcell in a wireless communication system are formed into a set of data. The Pcell overlaps with Scell(s). The UE-related measurements on the P cell are for a specific UE in the Pcell. Using a ML algorithm applied to the set of data, achievable channel quality is predicted for the specific UE for each of the Scell(s). The predicted achievable channel qualities are output for the specific UE to be used for Scell selection. At a RAN node, the set of data is sent toward an S cell prediction module for the module to determine information suitable to enable Scell selection for the specific UE. The RAN node receives information from the module allowing the RAN node to inform the selected UE of Scell(s) to be used for Scell selection for the specific UE. A node may train the ML algorithm using UE-related measurements on the Pcell.

    Identifying transient blockage
    10.
    发明授权

    公开(公告)号:US12262231B2

    公开(公告)日:2025-03-25

    申请号:US17412438

    申请日:2021-08-26

    Abstract: Apparatuses and methods in a communication system for identifying transient blockage are presented. Transmission to one or more RAN nodes of parameters for the one or more RAN node is controlled to detect occurrences of sharp channel degradation events in connections served by the node. Data is received from the one or more RAN nodes, the data being related to channel or transmission events related to detected sharp channel degradation in connections served by the node. Based on the received data, likelihood is determined that one or more RAN nodes have a high level of transient blockages.

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