Methods and systems for multi-layer perceptron based non-linear interference management in multi-technology communication devices
    11.
    发明授权
    Methods and systems for multi-layer perceptron based non-linear interference management in multi-technology communication devices 有权
    多技术通信设备中基于多层感知器的非线性干扰管理方法与系统

    公开(公告)号:US09484974B2

    公开(公告)日:2016-11-01

    申请号:US14849528

    申请日:2015-09-09

    CPC classification number: H04B1/40 H04B1/123 H04B1/525 H04B15/00

    Abstract: The various embodiments include methods and apparatuses for canceling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a multilayer perceptron neural network with Hammerstein structure by dividing an aggressor signal into real and imaginary components, augmenting the components by weight factors, executing a linear combination of the augmented components, and executing a nonlinear sigmoid function for the combined components at a hidden layer of multilayer perceptron neural network to produce a hidden layer output signal. At an output layer, hidden layer output signals may be augmented by weight factors, and the augmented hidden layer output signals may be linearly combined to produce real and imaginary components of an estimated jammer signal. A linear filter function may be executed for the components of the jammer signal, and to produce a nonlinear interference estimate used to cancel the nonlinear interference of a victim signal.

    Abstract translation: 各种实施例包括用于在多技术无线通信设备的并发通信期间消除非线性干扰的方法和装置。 可以使用具有Hammerstein结构的多层感知器神经网络来估计非线性干扰,通过将侵略者信号除以实部和虚部,通过权重因子增加分量,执行增强分量的线性组合,以及执行组合的非线性S形函数 组件在隐藏层的多层感知器神经网络中产生隐层输出信号。 在输出层,可以通过加权因子来增加隐层输出信号,并且增强的隐层输出信号可以被线性组合以产生估计的干扰信号的实部和虚部。 可以对干扰信号的分量执行线性滤波器功能,并且产生用于消除受害信号的非线性干扰的非线性干扰估计。

    Methods and Systems for Multi-Model, Multi-Layer Perceptron Based Non-Linear Interference Management in Multi-Technology Communication Devices
    13.
    发明申请
    Methods and Systems for Multi-Model, Multi-Layer Perceptron Based Non-Linear Interference Management in Multi-Technology Communication Devices 审中-公开
    多技术通信设备中多模式,多层感知器的非线性干扰管理方法与系统

    公开(公告)号:US20160072543A1

    公开(公告)日:2016-03-10

    申请号:US14849532

    申请日:2015-09-09

    CPC classification number: H04B1/40 H04B1/123 H04B1/525 H04B15/00

    Abstract: The various embodiments include methods and apparatuses for canceling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a multi-layer perceptron neural network with Hammerstein structure by dividing an aggressor signal into real and imaginary components, augmenting the components by weight factors, executing a linear combination of the augmented components, and executing a nonlinear sigmoid function for the combined components at a hidden layer of multi-layer perceptron neural network to produce a hidden layer output signal. At an output layer, hidden layer output signals may be augmented by weight factors, and the augmented hidden layer output signals may be linearly combined to produce real and imaginary components of an estimated jammer signal. A linear filter function may be executed for the components of the jammer signal, and to produce a nonlinear interference estimate used to cancel the nonlinear interference of a victim signal.

    Abstract translation: 各种实施例包括用于在多技术无线通信设备的并发通信期间消除非线性干扰的方法和装置。 可以使用具有Hammerstein结构的多层感知器神经网络来估计非线性干扰,通过将侵略者信号划分成实部和虚部,通过权重因子增加分量,执行增强分量的线性组合,以及执行非线性Sigmoid函数 组合成分在隐层多层感知神经网络中产生隐层输出信号。 在输出层,可以通过加权因子来增加隐层输出信号,并且增强的隐层输出信号可以被线性组合以产生估计的干扰信号的实部和虚部。 可以对干扰信号的分量执行线性滤波器功能,并且产生用于消除受害信号的非线性干扰的非线性干扰估计。

    Multilayer Perceptron for Dual SIM Dual Active Interference Cancellation
    14.
    发明申请
    Multilayer Perceptron for Dual SIM Dual Active Interference Cancellation 审中-公开
    用于双SIM双重主动干扰消除的多层感知器

    公开(公告)号:US20160071003A1

    公开(公告)日:2016-03-10

    申请号:US14510907

    申请日:2014-10-09

    Abstract: The various embodiments include methods and apparatuses for cancelling nonlinear interference during concurrent communication of dual-technology wireless communication devices. Nonlinear interference may be estimated using a multilayer perceptron neural network by augmenting aggressor signal(s) by weight factors, executing a linear combination of the augmented aggressor signals, and executing a nonlinear sigmoid function for the combined aggressor signals at a hidden layer of multilayer perceptron neural network to produce a hidden layer output signal. Multiple hidden layers may repeat the process for the hidden layer output signals. At an output layer, hidden layer output signals may be augmented by weight factors, and the augmented hidden layer output signals may be linearly combined to produce an estimated nonlinear interference used to cancel the nonlinear interference of a victim signal. The weight factors may be trained based on a determination of an error of the estimated nonlinear interference.

    Abstract translation: 各种实施例包括用于在双技术无线通信设备的并发通信期间消除非线性干扰的方法和装置。 可以使用多层感知器神经网络来估计非线性干扰,通过用权重因子增强攻击者信号,执行增强的侵略者信号的线性组合,以及在多层感知器的隐藏层处执行组合的攻击者信号的非线性S形函数 神经网络产生隐层输出信号。 多个隐藏层可能会重复隐藏层输出信号的过程。 在输出层,可以通过加权因子来增加隐层输出信号,并且增强隐层输出信号可以被线性组合以产生用于消除受害信号的非线性干扰的估计的非线性干扰。 可以基于估计的非线性干扰的误差的确定来训练加权因子。

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