EMPLOYING NEIGHBORING CELL ASSISTANCE INFORMATION FOR INTERFERENCE MITIGATION
    171.
    发明申请
    EMPLOYING NEIGHBORING CELL ASSISTANCE INFORMATION FOR INTERFERENCE MITIGATION 审中-公开
    使用相邻的细胞辅助信息进行干扰减缓

    公开(公告)号:US20140293971A1

    公开(公告)日:2014-10-02

    申请号:US14227279

    申请日:2014-03-27

    CPC classification number: H04W56/003 H04W72/042 H04W72/1226

    Abstract: Certain aspects of the present disclosure relate to methods and apparatus for employing a neighboring cell's assistance information for interference mitigation (e.g., by conveying the information to a user equipment). A base station (BS) may determine assistance information for a neighboring cell and convey it to a user equipment (UE). A UE may receive assistance information for a neighboring cell and use that information for performing interference cancellation or suppression on received signals. The UE may receive the assistance information from a serving cell or a non-serving cell. The assistance information may be valid for a particular transmission instance, for a known period of time, or until updated by a BS.

    Abstract translation: 本公开的某些方面涉及用于使用相邻小区的辅助信息用于干扰减轻的方法和装置(例如,通过将信息传送给用户设备)。 基站(BS)可以确定相邻小区的辅助信息并将其传送给用户设备(UE)。 UE可以接收相邻小区的辅助信息,并使用该信息来对接收的信号执行干扰消除或抑制。 UE可以从服务小区或非服务小区接收辅助信息。 辅助信息对于特定的传输实例可以在已知的时间段内有效,或直到由BS更新。

    INTERFERENCE ESTIMATION IN THE PRESENCE OF ePDCCH TRANSMISSIONS
    172.
    发明申请
    INTERFERENCE ESTIMATION IN THE PRESENCE OF ePDCCH TRANSMISSIONS 审中-公开
    ePDCCH传输干扰估计

    公开(公告)号:US20140029456A1

    公开(公告)日:2014-01-30

    申请号:US13943718

    申请日:2013-07-16

    Abstract: A method of wireless communication is presented. The method includes determining, for each resource element group of a resource block pair, whether an interfering control channel is present on the resource block pair. The determination may be based on whether estimated power of the resource element groups varies among two or more resource element groups. The method also includes estimating the interference on the resource block pair based on the determination.

    Abstract translation: 提出了一种无线通信方法。 该方法包括为资源块对的每个资源元素组确定资源块对上是否存在干扰控制信道。 该确定可以基于资源元素组的估计功率是否在两个或更多个资源元素组之间变化。 该方法还包括基于该确定来估计资源块对上的干扰。

    CHANNEL STATE INFORMATION REPORTING FOR PARTIALLY CANCELLED INTERFERENCE
    173.
    发明申请
    CHANNEL STATE INFORMATION REPORTING FOR PARTIALLY CANCELLED INTERFERENCE 有权
    通道状态信息报告部分取消干扰

    公开(公告)号:US20140003267A1

    公开(公告)日:2014-01-02

    申请号:US13928202

    申请日:2013-06-26

    Abstract: Parameters associated with an interfering downlink transmission may be determined at the UE or may be signaled to the UE from an eNodeB. The parameters may be actual parameters or hypothetical parameters. Based on the parameters, the UE may determine a metric that reflects an amount of interference cancelled from the interfering data channel transmission. The UE determines a quasi-clean channel state information and/or interference efficiency based on the parameters. The UE may transmit the quasi-clean CSI and/or the interference efficiency to the eNodeB.

    Abstract translation: 可以在UE处确定与干扰下行链路传输相关联的参数,或者可以从eNodeB向eNodeB发送信号给UE。 参数可以是实际参数或假设参数。 基于参数,UE可以确定反映从干扰数据信道传输中消除的干扰量的度量。 UE基于参数确定准清除信道状态信息和/或干扰效率。 UE可以向eNodeB发送准干净CSI和/或干扰效率。

    MONOSTATIC RADAR WITH PROGRESSIVE LENGTH TRANSMISSION

    公开(公告)号:US20250164630A1

    公开(公告)日:2025-05-22

    申请号:US19034384

    申请日:2025-01-22

    Abstract: Monostatic radar with progressive length transmission may be used with half-duplex systems or with full-duplex systems to reduce self-interference. The system transmits a first signal for a first duration and receives a first reflection of the first signal from a first object during a second duration. The system transmits a second signal for a third duration longer than the first duration and receives a second reflection of the second signal from a second object during a fourth duration. The system calculates a position of the first object and the second object based on the first reflection and the second reflection. The first signal, first duration, and second duration are configured to detect reflections from objects within a first distance of the system. The second signal, third duration, and fourth duration are configured to detect reflections from objects between the first distance and a second distance from the system.

    TWO-STAGE FREQUENCY DOMAIN MACHINE LEARNING-BASED CHANNEL STATE FEEDBACK

    公开(公告)号:US20250119224A1

    公开(公告)日:2025-04-10

    申请号:US18484269

    申请日:2023-10-10

    Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may communicate signaling with a network entity, the signaling indicating a first bandwidth size and a second bandwidth size associated with a projection parameter (W1) and a compression parameter (W2), respectively. The second bandwidth size may be less than the first bandwidth size. In some cases, the UE may determine W1 and W2 based on a first machine learning (ML) model and a second ML model, respectively. The UE may project a portion of received channel state information (CSI) associated with the first bandwidth size onto a sub-space defined by W1 and may compress a portion of the projection associated with the second bandwidth size based on W2. The UE may transmit channel state feedback including the projection, the compression of the projection, a compression of W1, a compression of W2, or any combination thereof.

    INDICATING CAUSES FOR LIFE CYCLE MANAGEMENT OPERATIONS

    公开(公告)号:US20250048131A1

    公开(公告)日:2025-02-06

    申请号:US18362759

    申请日:2023-07-31

    Abstract: Methods, systems, and devices for wireless communication are described. A network entity may monitor a performance of a machine learning (ML) model or ML model-based functionality associated with a user equipment (UE). The UE may receive one or more control messages that indicate a life cycle management (LCM) operation for the ML model or ML model-based functionality. The one or more control messages may include an indication of whether the LCM operation is based on the performance of the MIL model or ML model-based functionality. In some examples, the indication may include or be an example of a performance report associated with the performance of the ML model or ML model-based functionality. The UE may perform the LCM operation for the ML model or ML model-based functionality. The UE or the network entity may transmit the indication to a server associated with the ML model or ML model-based functionality.

    DOWNLINK-BASED AI/ML POSITIONING FUNCTIONALITY AND MODEL IDENTIFICATION

    公开(公告)号:US20240414500A1

    公开(公告)日:2024-12-12

    申请号:US18331014

    申请日:2023-06-07

    Abstract: Aspects presented herein may enable a UE and a network entity to have a common understanding for AI/ML models used in association with AI/ML positioning, thereby improving the performance and efficiency of AI/ML positioning. In one aspect, a UE transmits, to a network entity, a list of UE-supported AI/ML positioning functionalities. The UE receives, from the network entity, an indication of a set of network-supported AI/ML positioning functionalities that are supported by the network entity. The UE transmits, to the network entity, a PRS-based measurement or an estimated location of the UE that is based on using at least one AI/ML model associated with at least one UE-supported AI/ML positioning functionality in the list of UE-supported AI/ML positioning functionalities or at least one network-supported AI/ML positioning functionality in the set of network-supported AI/ML positioning functionalities.

    UPLINK-BASED ARTIFICIAL INTELLIGENCE / MACHINE LEARNING (AI/ML) POSITIONING FUNCTIONALITY AND MODEL IDENTIFICATION

    公开(公告)号:US20240406927A1

    公开(公告)日:2024-12-05

    申请号:US18329273

    申请日:2023-06-05

    Abstract: Disclosed are techniques for communication. In an aspect, a radio access network (RAN) node transmits, to a network entity, a set of machine learning positioning capabilities supported by the RAN node, wherein the set of machine learning positioning capabilities includes a list of identifiers of a set of machine learning positioning functionalities supported by the RAN node, wherein the set of machine learning positioning functionalities is associated with a set of machine learning models that support the set of machine learning positioning functionalities, and wherein each machine learning positioning functionality of the set of machine learning positioning functionalities is associated with one or more machine learning models of the set of machine learning models, and transmits, to the network entity, one or more measurements of one or more sounding reference signal (SRS) resources transmitted by a user equipment (UE).

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