EFFICIENT LARGE-SCALE MULTIPLE INPUT MULTIPLE OUTPUT COMMUNICATIONS
    14.
    发明申请
    EFFICIENT LARGE-SCALE MULTIPLE INPUT MULTIPLE OUTPUT COMMUNICATIONS 有权
    有效的大规模多输入多输出通信

    公开(公告)号:US20150365143A1

    公开(公告)日:2015-12-17

    申请号:US14738268

    申请日:2015-06-12

    CPC classification number: H04B17/309 H04B7/0452 H04B7/0617 H04B17/104

    Abstract: Methods and systems for beam forming, implemented in a base station used in a communication system, include measuring channel state information (CSI) for a number of active phased-array antennas less than a full number of phased-array antennas. Analog beam forming weights are determined using the measured CSI. An optimal digital precoder is determined from the analog beam forming weights. The analog beam forming weights and optimal digital precoder are applied to one phased-array antenna.

    Abstract translation: 在用于通信系统的基站中实现的用于波束形成的方法和系统包括测量小于全数量相控阵列天线的多个有源相控阵天线的信道状态信息(CSI)。 使用测量的CSI确定模拟波束形成权重。 从模拟波束形成权重确定最优数字预编码器。 模拟波束形成权重和最佳数字预编码器应用于一个相控阵天线。

    Unmanned aerial vehicle network
    15.
    发明授权

    公开(公告)号:US11356172B2

    公开(公告)日:2022-06-07

    申请号:US16816605

    申请日:2020-03-12

    Abstract: Systems and methods implementing a multi-unmanned aerial vehicle (UAV) wireless communication network are provided. The system includes application UAVs that wirelessly provide applications. The system includes relay UAVs that connect the application UAVs to a ground station. The ground station connects to a wireless backhaul network. Processor devices determine mobility for the application UAVs based on application-specific objectives. The processor devices also determine mobility for the relay UAVs based on forming and maintaining the wireless backhaul network.

    NEAR REAL-TIME RECONSTRUCTION USING DRONES

    公开(公告)号:US20210311504A1

    公开(公告)日:2021-10-07

    申请号:US17220046

    申请日:2021-04-01

    Abstract: Systems and methods for automatically constructing a 3-dimensional (3D) model of a feature using a drone. The method includes generating a reconnaissance flight path that minimizes battery usage by the drone, and conducting a discovery flight that uses the reconnaissance flight path. The method further includes transmitting reconnaissance laser sensor data from the drone to a processing system for target identification, and selecting a target feature for 3D model construction based on the reconnaissance laser sensor data. The method further includes scanning the target feature using a laser sensor, transmitting laser sensor data for the target feature having a minimum point density from the drone to the processing system for 3D model construction, and constructing the 3D model from the minimum point density laser sensor data.

    READING PASSIVE WIRELESS TAGS USING COMMODITY DEVICES

    公开(公告)号:US20210294993A1

    公开(公告)日:2021-09-23

    申请号:US17202854

    申请日:2021-03-16

    Abstract: A method for product tagging is presented including emitting, by at least one RF backscatter transmitter, a dual-tone Radio Frequency (RF) signal embedded within a standardized RF signal on a frequency channel, reflecting and frequency shifting, by a passive RF backscatter tag associated with a product, the dual-tone RF signal to a different frequency channel, and reading, by at least one RF backscatter receiver, the product on the different frequency channel by detecting a distributed ambient backscatter signal generated by a reflection and frequency shifting of the dual-tone RF signal by the passive RF backscatter tag.

    Speculative scheduling in mobile networks

    公开(公告)号:US10582529B2

    公开(公告)日:2020-03-03

    申请号:US15915491

    申请日:2018-03-08

    Abstract: A system is provided for speculative scheduling that includes a base station having a processor. The processor computes an overall schedule for a set of clients. The overall schedule is formed from a set of speculative schedules, is configured to maximize unlicensed spectrum usage, and is computed by (a) determining a speculative schedule for each resource block from a set of resource blocks in a given sub-frame based on statistics determined for the clients individually and jointly, and (b) selecting, for formation into the overall schedule, (i) a particular resource block and (ii) the speculative schedule for the particular resource block, that yield the maximum incremental utility relative to already determined speculative schedules for other resource blocks in the set, based on criteria including uplink access statistics. The processor executes the overall schedule responsive to a completion of the speculative schedule determination for each resource block in the given sub-frame.

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