Efficient polyphase architecture for interpolator and decimator

    公开(公告)号:US10917122B2

    公开(公告)日:2021-02-09

    申请号:US16656971

    申请日:2019-10-18

    Abstract: Apparatuses (and methods of manufacturing same), systems, and methods concerning polyphase digital filters are described. In one aspect, an apparatus is provided, including at least one pair of subfilters, each having symmetric coefficients, and a lattice comprising two adders and feedlines corresponding to each of the at least one pair of subfilters, each having symmetric coefficients. In one aspect, the apparatus is a polyphase finite impulse response (FIR) digital filter, including an interpolator and a decimator, where each of the interpolator and the decimator have at least one pair of subfilters, each having symmetric coefficients, and a lattice comprising two adders and feedlines corresponding to each of the at least one pair of subfilters, each having symmetric coefficients.

    Soft channel tracking using detection output

    公开(公告)号:US10536239B2

    公开(公告)日:2020-01-14

    申请号:US15447899

    申请日:2017-03-02

    Abstract: A method and apparatus are provided. The method includes receiving, by a user equipment (UE), a first signal from a transceiver, determining one of a probability and a soft mean with a soft variance associated with the detected data symbol, determining a first coefficient and a second coefficient based on the determined one of the probability and the soft mean with the soft variance associated with the detected data symbol, determining channel state information (CSI) on a channel between the transceiver and the UE based on a second signal received by the UE from the transceiver, a previous CSI, the first coefficient and the second coefficient, and tracking the communication channel based on the determined CSI.

    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.

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