APPARATUSES AND METHODS OF DETECTION OF INTERFERING CELL COMMUNICATION PROTOCOL USAGE
    331.
    发明申请
    APPARATUSES AND METHODS OF DETECTION OF INTERFERING CELL COMMUNICATION PROTOCOL USAGE 审中-公开
    检测细胞通信协议使用的方法和方法

    公开(公告)号:US20140023001A1

    公开(公告)日:2014-01-23

    申请号:US13939140

    申请日:2013-07-10

    CPC classification number: H04W24/02 H04W48/12 H04W48/20 H04W72/082

    Abstract: A method, an apparatus, and a computer program product for wireless communication are provided in connection with UE centric interfering cell communication protocol usage detection. In one example, a communications device (e.g., a UE) is equipped to receive one or more signals from each cell of a plurality of cells including a set of interfering cells. The set of interfering cells includes one or more interfering cells. The UE can detect system release version information for at least one cell from the set of interfering cells, and then modify its communication processing with a serving cell based on the detected system release version information.

    Abstract translation: 结合以UE为中心的干扰小区通信协议使用检测提供了一种用于无线通信的方法,装置和计算机程序产品。 在一个示例中,通信设备(例如,UE)被配备为从包括一组干扰小区的多个小区的每个小区接收一个或多个信号。 该组干扰小区包括一个或多个干扰小区。 UE可以从干扰小区集合中检测至少一个小区的系统发布版本信息,然后基于检测到的系统版本信息修改其与服务小区的通信处理。

    SYSTEMS AND METHODS FOR REDUCED OVERHEAD IN WIRELESS COMMUNICATION SYSTEMS
    332.
    发明申请
    SYSTEMS AND METHODS FOR REDUCED OVERHEAD IN WIRELESS COMMUNICATION SYSTEMS 有权
    无线通信系统中减少覆盖的系统和方法

    公开(公告)号:US20130294333A1

    公开(公告)日:2013-11-07

    申请号:US13797716

    申请日:2013-03-12

    Abstract: Systems and methods are disclosed which implement one or more overhead reduction technique, if channel conditions favorable to implementation of overhead reduction are present. The one or more overhead reduction technique may have one or more restriction corresponding to the channel for which the overhead reduction technique is implemented. The one or more overhead reduction technique implemented may include time-domain bundling, frequency-domain bundling, and pattern adaptation. Pattern adaptation may include pattern code-domain reduction, pattern timing-domain reduction, and pattern frequency-domain reduction.

    Abstract translation: 如果存在有利于实现开销降低的信道条件,则公开了实现一个或多个开销降低技术的系统和方法。 一个或多个开销降低技术可以具有对应于实现开销降低技术的信道的一个或多个限制。 实现的一个或多个开销降低技术可以包括时域捆绑,频域绑定和模式适配。 模式适配可以包括模式码域减少,模式定时域减少和模式频域减少。

    PER-CELL TIMING AND/OR FREQUENCY ACQUISITION AND THEIR USE ON CHANNEL ESTIMATION IN WIRELESS NETWORKS
    333.
    发明申请
    PER-CELL TIMING AND/OR FREQUENCY ACQUISITION AND THEIR USE ON CHANNEL ESTIMATION IN WIRELESS NETWORKS 有权
    单元时间和/或频率采集及其在无线网络中的信道估计中的应用

    公开(公告)号:US20130231123A1

    公开(公告)日:2013-09-05

    申请号:US13865693

    申请日:2013-04-18

    CPC classification number: H04W24/00 H04W56/00 H04W56/0015 H04W56/0035

    Abstract: A method, an apparatus, and a computer program product for wireless communication are provided in which a system timing is estimated, derived from timing of one or more cells, a timing offset is determined for a plurality of cells relative to the estimated system timing, and signals received form the plurality of cells are processed using the timing offsets. In addition, a method, an apparatus, and a computer program product for wireless communication are provided in which a carrier frequency is estimated, derived from a frequency of one or more cells, a frequency offset is determined for a plurality of cells relative to the estimated system timing, and signals received form the plurality of cells are processed using the frequency offsets.

    Abstract translation: 提供了一种用于无线通信的方法,装置和计算机程序产品,其中从一个或多个单元的定时导出系统定时,相对于估计的系统定时为多个单元确定定时偏移, 并且使用定时偏移来处理从多个单元接收的信号。 此外,提供了一种用于无线通信的方法,装置和计算机程序产品,其中从一个或多个单元的频率导出载波频率,相对于多个单元确定频率偏移 使用频率偏移来处理估计的系统定时和从多个小区接收的信号。

    INCREMENTAL INTERFERENCE CANCELATION CAPABILITY AND SIGNALING
    334.
    发明申请
    INCREMENTAL INTERFERENCE CANCELATION CAPABILITY AND SIGNALING 有权
    增加干扰消除能力和信号

    公开(公告)号:US20130114447A1

    公开(公告)日:2013-05-09

    申请号:US13659633

    申请日:2012-10-24

    CPC classification number: H04J11/0023 H04B1/7103 H04B2201/7071

    Abstract: Incremental interference cancelation (IC) capability management and signaling is disclosed. A mobile device selects certain groups of its individual IC capabilities to deactivate in response to various operating conditions it is experiencing. The mobile device reports its currently active IC capability to a serving base station, which uses information to determine whether to modify any existing communication conditions with respect to the reporting mobile device. The base station detects and analyzes the current communication conditions with respect to the reporting mobile device in light of the mobile device's currently active IC capabilities. The base station may modify such conditions through actions such as signaling the mobile device to activate or deactivate certain other groups of IC capabilities. The base station can make other modifications such as changing the communication schedule for the mobile device, modifying the control loop for channel quality indicator (CQI) reporting, and the like.

    Abstract translation: 公开了增量干扰消除(IC)能力管理和信令。 移动设备根据其正在经历的各种操作条件选择其各个IC功能的某些组来停用。 移动设备向服务基站报告其当前活动的IC能力,其使用信息来确定是否修改关于报告移动设备的任何现有通信条件。 根据移动设备的当前活动IC能力,基站检测并分析与报告移动设备相关的当前通信条件。 基站可以通过诸如发信号通知移动设备激活或去激活某些其他IC能力组的动作来修改这些条件。 基站可以进行其他修改,例如改变移动设备的通信调度,修改用于信道质量指示符(CQI)报告的控制环路等。

    MACHINE LEARNING MODELS FOR PREDICTIVE RESOURCE MANAGEMENT

    公开(公告)号:US20250105929A1

    公开(公告)日:2025-03-27

    申请号:US18834119

    申请日:2022-03-08

    Abstract: Methods, systems, and devices for wireless communications are described. A network entity may transmit, and a user equipment (UE) may receive, signaling identifying a configuration of a set of multiple machine learning (ML) models for channel characteristic prediction. The channel characteristic prediction may include a channel characteristic prediction for each ML model of the set of multiple ML models based on a respective reference signal resource of the set of multiple reference signal resources. The network entity may obtain an input to the set of multiple ML models based on performing one or more measurements associated with the set of multiple reference signal resources. The network entity may output, and the UE may obtain, the input. The UE may process the input using at least one ML model of the set of multiple ML models to obtain the channel characteristic prediction of the at least one ML model.

    Derivation of channel features using a subset of channel ports

    公开(公告)号:US12256248B2

    公开(公告)日:2025-03-18

    申请号:US17450245

    申请日:2021-10-07

    Inventor: Taesang Yoo

    Abstract: In one aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be a user equipment (UE) or a component thereof. The apparatus may be configured to receive pilot signals from a base station on a first subset of a set of antenna ports of a channel. The apparatus may be further configured to measure a first set of values corresponding to the first subset of the set of antenna ports based on receiving the pilot signals transmitted from the base station on the first subset of the set of antenna ports. The apparatus may be further configured to derive a second set of values corresponding to a second subset of the set of antenna ports of the channel based on receiving the pilot signals on the first subset of the set of antenna ports.

    Distortion probing reference signals

    公开(公告)号:US12245251B2

    公开(公告)日:2025-03-04

    申请号:US18324005

    申请日:2023-05-25

    Abstract: Methods, systems, and devices for wireless communications are described. A first device and a second device may communicate via a channel. The first device may generate and transmit a reference signal, which may be a distortion probing reference signal with a high peak to average power ratio. In one implementation, the first device may use the reference signal as an input for a neural network model to learn a nonlinear response of the second device transmission components. In another implementation, the second device may sample the generated reference signal, and use the samples as inputs for a neural network model to learn the nonlinear response. The first device and the second device may exchange signaling based on learning the nonlinear response, and each device may compensate for the nonlinear response when communicating via the channel.

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