Apparatus and method for modeling random process using reduced length least-squares autoregressive parameter estimation

    公开(公告)号:US10394985B2

    公开(公告)日:2019-08-27

    申请号:US15465181

    申请日:2017-03-21

    Abstract: An apparatus and method for modelling a random process using reduced length least-squares autoregressive parameter estimation is herein disclosed. The apparatus includes an autocorrelation processor, configured to generate or estimate autocorrelations of length m for a stochastic process, where m is an integer; and a least-squares (LS) estimation processor connected to the autocorrelation processor and configured to model the stochastic process by estimating pth order autoregressive (AR) parameters using LS regression, where p is an integer much less than m. The method includes generating, by an autocorrelation processor, autocorrelations of length m for a stochastic process, where m is an integer; and modelling the stochastic process, by a least-squares estimation processor, by estimating pth order autoregressive (AR) parameters by least-squares (LS) regression, where p is an integer much less than m.

    APPARATUS AND METHOD OF FIVE DIMENSIONAL (5D) VIDEO STABILIZATION WITH CAMERA AND GYROSCOPE FUSION

    公开(公告)号:US20190147606A1

    公开(公告)日:2019-05-16

    申请号:US16016232

    申请日:2018-06-22

    Abstract: An apparatus and method of five dimensional (5D) video stabilization with camera and gyroscope fusion are herein disclosed. According to one embodiment, an apparatus includes a feature matcher configured to receive an image sequence and determine feature pairs in the image sequence; a residual two-dimensional (2D) translation estimator connected to the feature matcher and configured to determine a raw 2D translation path; a residual 2D translation smoother connected to the residual 2D translation estimator and configured to determine a 2D smoothed translation path; a distortion calculator connected to the residual 2D translation estimator and the residual 2D translation smoother and configured to determine a distortion grid; and a distortion compensator connected to the distortion calculator and configured to compensate for distortion in the image sequence.

    Apparatus for and method of channel quality prediction through computation of multi-layer channel quality metric

    公开(公告)号:US09628154B2

    公开(公告)日:2017-04-18

    申请号:US15040437

    申请日:2016-02-10

    CPC classification number: H04B7/0413 H04B17/309 H04L1/203

    Abstract: An apparatus and method for a transceiver are provided. The apparatus for the transceiver includes a multiple input multiple output (MIMO) antenna; a transceiver connected to the MIMO antenna; and a processor configured to measure channel gain Hk, based on the received signal, where k is a sample index from 1 to K, Hk is an m×n matrix of complex channel gain known to the transceiver, measure noise variance σ2 of a channel, calculate a per-sample channel quality metric q(Hk, σ2) using at least one bound of mutual information; reduce a dimension of a channel quality metric vector (q(H1, σ2), . . . , q(HK, σ2)) by applying a dimension reduction function g(.); and estimate a block error rate (BLER) as a function of a dimension reduced channel quality metric g(q(H1, σ2), . . . , q(HK, σ2)).

    Systems, methods, and apparatus for determining precoding information for beamforming

    公开(公告)号:US12155429B2

    公开(公告)日:2024-11-26

    申请号:US17852358

    申请日:2022-06-28

    Abstract: A method may include determining, for a channel, a target component of precoding information, determining at least a part of the precoding information based on the target component and a decompressed component of the precoding information, and sending, from a user equipment, the at least a part of the precoding information. Determining the at least a part of the precoding information may be based on a correlation between the target component and the decompressed component. The at least a part of the precoding information may include a vector of coefficients. The vector of coefficients may include a vector of complex numbers. At least one of the complex numbers may include an amplitude representing a scaling coefficient and a phase representing a rotation coefficient. The target component may include a target matrix. The decompressed component may include a decompressed matrix. The target matrix may include a linear combination coefficients matrix. The precoding information may include a precoding matrix indicator.

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