OPTIMIZING SPECTRAL EFFICIENCY IN A 5G MASSIVE MIMO SPLIT ARCHITECTURE

    公开(公告)号:US20240056159A1

    公开(公告)日:2024-02-15

    申请号:US18548942

    申请日:2022-03-29

    CPC classification number: H04B7/0695 H04B7/0617 H04B17/336

    Abstract: This disclosure relates to apparatuses, systems, and methods for scheduling user equipment (UE) transmissions, and in particular for scheduling UE transmissions in a 5G New Radio system with a split architecture. The scheduler selects a beamforming algorithm for a UE group that includes a first UE and a second UE, where the beamforming algorithm is based on characteristics of the beamforming algorithm and/or the UE group. The scheduler determines an effective SINR for the UE group based on the beamforming algorithm and determines a summed proportion fair metric for the UE group based on the effective SINR for the UE group. The scheduler schedules a transmission for either the first UE or the UE group, based on a proportional fair metric for the first UE and the summed proportional fair metric for the UE group.

    ENHANCED COLLABORATION BETWEEN USER EQUPIMENT AND NETWORK TO FACILITATE MACHINE LEARNING

    公开(公告)号:US20240349082A1

    公开(公告)日:2024-10-17

    申请号:US18552641

    申请日:2022-04-29

    CPC classification number: H04W24/02 H04W60/04

    Abstract: This disclosure describes systems, methods, and devices related to collaboration between user equipment (UE) and network for machine learning. A radio access network (RAN) node B device may transmit, to the CE device, an indication that the node B device supports machine learning; identify a service registration, received from the UE device, indicating that the UE device requests machine learning support from the node B device; transmit, to the UE device, a request for information associated with the UE device, the information associated with at least one of hardware capabilities or machine learning capabilities of the UE device; identify the information received from the UE based on the request for information; and transmit, to the UE device, a machine learning configuration for use by the UE device, wherein the machine learning configuration is based on the information.

    USING AI-BASED MODELS FOR NETWORK ENERGY SAVINGS

    公开(公告)号:US20240298225A1

    公开(公告)日:2024-09-05

    申请号:US18574651

    申请日:2022-10-19

    CPC classification number: H04W36/0072 H04W24/02 H04W52/02

    Abstract: An apparatus for an access node, includes a memory interface to send or receive, to or from a data storage device, measurement information for measurement signaling between a first next generation radio access network (NG-RAN) node and a second NG-RAN node. The apparatus also includes processor circuitry communicatively coupled to the memory interface, the processor circuitry to initiate execution of a machine learning (ML) model by the first NG-RAN node to select an energy saving state for the first NG-RAN node, the second NG-RAN node or a user equipment (UE), and generate one or more messages with an information element (IE) with one or more parameters to request measurement information according to the one or more parameters, the measurement information to comprise feedback information to train the ML model. Other embodiments are described and claimed.

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