METHOD AND APPARATUS FOR INTERFERENCE CANCELLATION BY A USER EQUIPMENT USING BLIND DETECTION
    111.
    发明申请
    METHOD AND APPARATUS FOR INTERFERENCE CANCELLATION BY A USER EQUIPMENT USING BLIND DETECTION 有权
    用于使用盲点检测的用户设备进行干扰消除的方法和装置

    公开(公告)号:US20140098773A1

    公开(公告)日:2014-04-10

    申请号:US14105086

    申请日:2013-12-12

    Abstract: In order to cancel any interference due to the second signal (e.g., from a non-serving cell) from a signal received at a UE, without receiving additional control information, the UE blindly estimates parameters associated with decoding the second signal. This may include determining a metric based on sets of symbols associated with the signals in order to determine parameters for the second signal, e.g., the transmission mode, modulation format, and/or spatial scheme of the second signal. The parameters for the signal may be determined based on a comparison of the metric with a threshold. When a spatial scheme and a modulation format is unknown, the blind estimation may include determining a plurality of constellations of possible transmitted modulated symbols associated with a potential spatial scheme and modulation format combination. Interference cancellation can be performed using the constellations and a corresponding probability weight.

    Abstract translation: 为了从UE接收到的信号中消除由于第二信号(例如,来自非服务小区)的任何干扰而不接收附加控制信息,UE盲目地估计与解码第二信号相关联的参数。 这可以包括基于与信号相关联的符号集来确定度量,以便确定第二信号的参数,例如第二信号的传输模式,调制格式和/或空间方案。 可以基于度量与阈值的比较来确定信号的参数。 当空间方案和调制格式未知时,盲估计可以包括确定与潜在的空间方案和调制格式组合相关联的可能传输的调制符号的多个星座。 干扰消除可以使用星座和相应的概率权重进行。

    APPARATUS AND METHODS FOR RESOURCE ELEMENT GROUP BASED TRAFFIC TO PILOT RATIO AIDED SIGNAL PROCESSING
    112.
    发明申请
    APPARATUS AND METHODS FOR RESOURCE ELEMENT GROUP BASED TRAFFIC TO PILOT RATIO AIDED SIGNAL PROCESSING 审中-公开
    用于资源元素组交通的导引比例信号处理的装置和方法

    公开(公告)号:US20130336249A1

    公开(公告)日:2013-12-19

    申请号:US13916437

    申请日:2013-06-12

    CPC classification number: H04W72/0406 H04L5/005 H04L5/0053

    Abstract: A method, a computer program product, and an apparatus are provided. The methods and apparatus for wireless communication include receiving a transmission, the transmission including a plurality of resource element groups (REGs). Aspects of the methods and apparatus include selecting a set of REGs from the plurality of REGs, the set of REGs including at least one REG and determining a traffic to pilot ratio (TPR) for the set of REGs based on the transmission and reference signals in the transmission. Aspects of the methods and apparatus include determining whether the set of REGs includes at least one of control information or data based on the TPR and canceling at least one of control information or data from the set of REGs based on the TPR.

    Abstract translation: 提供了一种方法,计算机程序产品和装置。 无线通信的方法和装置包括接收传输,该传输包括多个资源单元组(REG)。 方法和装置的方面包括从多个REG中选择一组REG,包括至少一个REG的REG集合,并且基于传输和参考信号来确定REG集合的业务与导频比(TPR) 传输。 方法和装置的方面包括基于TPR来确定该REG组是否包括控制信息或数据中的至少一个,并且基于该TPR从该组REG中取消控制信息或数据中的至少一个。

    ARTIFICIAL INTELLIGENCE MODEL ASSISTANCE INFORMATION

    公开(公告)号:US20250063386A1

    公开(公告)日:2025-02-20

    申请号:US18764892

    申请日:2024-07-05

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, based at least in part on one or more performance metrics associated with an artificial intelligence (AI) model associated with wireless communication, assistance information associated with an expected performance of the AI model. The UE may assess, based at least in part on the assistance information, the expected performance of the AI model. Numerous other aspects are described.

    QUASI CO-LOCATION RELATION INDICATION FOR ARTIFICIAL INTELLIGENCE OR MACHINE LEARNING MODELS

    公开(公告)号:US20250055561A1

    公开(公告)日:2025-02-13

    申请号:US18366042

    申请日:2023-08-07

    Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may communicate, with a network entity, an indication of operation of an artificial intelligence (AI) or (ML) model at the UE and/or the network entity. Based on the indication of the operation of the AI or ML model, the UE may communicate, with the network entity, an indication of the QCL relation between the AI or ML model and reference signal communicated by the UE, a physical channel communicated by the UE, an antenna port of the network entity, or an antenna port of the UE. The QCL relation may indicate the radio characteristics applicable to the AI or ML model. The QCL relation may indicate the radio characteristics applicable to the AI or ML model.

    SYSTEMS AND METHODS FOR POSITIONING WITH CHANNEL MEASUREMENTS

    公开(公告)号:US20240430846A1

    公开(公告)日:2024-12-26

    申请号:US18821799

    申请日:2024-08-30

    Abstract: Position determination of a user equipment (UE) is supported using channel measurements obtained for Wireless Access Points (WAPs), wherein the channel measurements are for Line of Sight (LOS) and Non-LOS (NLOS) signals. Based on WAP almanac information and the channel measurements, channel parameters indicative of positions of signal sources relative to a first position of a UE may be determined. Using the first position of the UE and an association of the signal sources with corresponding channel parameters, a second position of the UE may be determined. The position of the UE may be a probability density function. Additionally, position information for signal sources may be determined, such as a probability density function, as well as signal blockage probability and an antenna geometry and the WAP almanac information may be updated accordingly.

    CHANNEL STATE FEEDBACK WITH FRACTIONAL RANK INDICATOR

    公开(公告)号:US20240413867A1

    公开(公告)日:2024-12-12

    申请号:US18695678

    申请日:2021-11-18

    Abstract: Certain aspects of the present disclosure provide techniques for reporting channel state information (CSI). According to certain aspects, a method for wireless communications by a user equipment (UE) generally includes generating channel state information (CSI) comprising a (at least one) fractional rank indication (RI) value for a set of candidate ranks, a first indication of a first layer or first singular vector, and a second indication of a second layer or second singular vector and transmitting the CSI to a network entity.

    LOCALIZATION VIA MACHINE LEARNING BASED ON PERCEIVED CHANNEL PROPERTIES AND INERTIAL MEASUREMENT UNIT SUPERVISION

    公开(公告)号:US20240372636A1

    公开(公告)日:2024-11-07

    申请号:US18481655

    申请日:2023-10-05

    Abstract: Certain aspects of the present disclosure provide techniques and apparatus for improved machine learning. A sequence of data records is accessed, each data record comprising wireless channel measurements and inertial measurement unit (IMU) data. Known position information corresponding to at least a first data record is accessed. A first sequence of positions is determined by processing the sets of IMU data and known position information using a forward operation. A second sequence of positions is determined by processing the sets of IMU data and known position information using a backward operation. An IMU adjustment parameter is generated using the first and second sequences of positions. A pseudo-label is generated for a second data record using the IMU adjustment parameter and the sets of IMU data. A machine learning model is trained, using the second data record and the pseudo-label, to predict positions using one or more wireless channel measurements.

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