subtracting linear impairments for non-linear impairment digital pre-distortion error signal
    1.
    发明申请
    subtracting linear impairments for non-linear impairment digital pre-distortion error signal 有权
    减去非线性损伤数字预失真误差信号的线性损伤

    公开(公告)号:US20150236730A1

    公开(公告)日:2015-08-20

    申请号:US14185888

    申请日:2014-02-20

    CPC classification number: H04B1/0475 H03F1/3241 H04B2001/0425

    Abstract: Example embodiment of the systems and methods of linear impairment modeling to improve digital pre-distortion adaptation performance includes a DPD module that is modified during each sample by a DPD adaptation engine. A linear impairment modeling module separates the linear and non-linear errors introduced in the power amplifier. The linear impairment model is adjusted during each sample using inputs from the input signal and from a FB post processing module. The linear impairment modeling module removes the linear errors such that the DPD adaptation engine only adapts the DPD module based on the non-linear errors. This increases system stability and allows for the correction of IQ imbalance inside the linear impairment modeling, simplifying the feedback post-processing.

    Abstract translation: 用于改善数字预失真适应性能的线性损伤建模的系统和方法的示例性实施例包括在DPD适配引擎的每个采样期间修改的DPD模块。 线性损伤建模模块分离功率放大器中引入的线性和非线性误差。 在每个采样中使用输入信号和FB后处理模块的输入调整线性损伤模型。 线性损伤建模模块消除线性误差,使得DPD自适应引擎仅基于非线性误差来适应DPD模块。 这增加了系统稳定性,并允许在线性损伤建模中对IQ不平衡进行校正,从而简化了反馈后处理。

    Capture selection for digital pre-distortion adaptation and capture concatenation for frequency hopping pre-distortion adaptation
    4.
    发明授权
    Capture selection for digital pre-distortion adaptation and capture concatenation for frequency hopping pre-distortion adaptation 有权
    捕获选择数字预失真适应和捕获级联跳频预失真适应

    公开(公告)号:US09374112B2

    公开(公告)日:2016-06-21

    申请号:US14475552

    申请日:2014-09-02

    CPC classification number: H04B1/0475 H03F1/3241 H04B2001/0425 H04W88/08

    Abstract: A digital pre-distortion component includes: a first capturing component that captures a first sample set of data; a first generating component that generates a first change matrix associated with a portion of the first sample set of data; a first memory component that stores the first change matrix; a second capturing component that captures a second sample set of data; a second generating component that generates a second change matrix associated with a portion of the second sample set of data; a second memory component that stores the second change matrix; a third capturing component that captures a third sample set of data; a third generating component that generates a third change matrix associated with a portion of the third sample set of data; a comparing component that compares the third change matrix with the first change matrix to obtain a first comparison, and compares the third change matrix with the second change matrix to obtain a second comparison; and an adapting component that adapts the digital pre-distortion component with the third sample set of data based on one of the first comparison and the second comparison.

    Abstract translation: 数字预失真部件包括:第一捕获部件,其捕获第一采样数据集; 第一生成组件,其生成与所述第一样本数据集合的一部分相关联的第一改变矩阵; 存储所述第一改变矩阵的第一存储器组件; 捕获第二样本数据集合的第二捕获组件; 第二生成组件,其生成与所述第二样本数据集合的一部分相关联的第二改变矩阵; 存储所述第二改变矩阵的第二存储器组件; 捕获第三样本数据集合的第三捕获组件; 第三生成组件,其生成与所述第三样本数据集的一部分相关联的第三变化矩阵; 将所述第三变化矩阵与所述第一变化矩阵进行比较以获得第一比较的比较部,将所述第三变化矩阵与所述第二变化矩阵进行比较,得到第二比较; 以及适配部件,其基于第一比较和第二比较中的一个来适配数字预失真分量与第三样本数据集合。

    CAPTURE SELECTION FOR DIGITAL PRE-DISTORTION ADAPTATION AND CAPTURE CONCATENATION FOR FREQUENCY HOPPING PRE-DISTORTION ADAPTATION
    5.
    发明申请
    CAPTURE SELECTION FOR DIGITAL PRE-DISTORTION ADAPTATION AND CAPTURE CONCATENATION FOR FREQUENCY HOPPING PRE-DISTORTION ADAPTATION 有权
    用于频率预失真适应的数字预失真适应和捕获定位的捕获选择

    公开(公告)号:US20160065249A1

    公开(公告)日:2016-03-03

    申请号:US14475552

    申请日:2014-09-02

    CPC classification number: H04B1/0475 H03F1/3241 H04B2001/0425 H04W88/08

    Abstract: A digital pre-distortion component includes: a first capturing component that captures a first sample set of data; a first generating component that generates a first change matrix associated with a portion of the first sample set of data; a first memory component that stores the first change matrix; a second capturing component that captures a second sample set of data; a second generating component that generates a second change matrix associated with a portion of the second sample set of data; a second memory component that stores the second change matrix; a third capturing component that captures a third sample set of data; a third generating component that generates a third change matrix associated with a portion of the third sample set of data; a comparing component that compares the third change matrix with the first change matrix to obtain a first comparison, and compares the third change matrix with the second change matrix to obtain a second comparison; and an adapting component that adapts the digital pre-distortion component with the third sample set of data based on one of the first comparison and the second comparison.

    Abstract translation: 数字预失真部件包括:第一捕获部件,其捕获第一采样数据集; 第一生成组件,其生成与所述第一样本数据集合的一部分相关联的第一改变矩阵; 存储所述第一改变矩阵的第一存储器组件; 捕获第二样本数据集合的第二捕获组件; 第二生成组件,其生成与所述第二样本数据集合的一部分相关联的第二改变矩阵; 存储所述第二改变矩阵的第二存储器组件; 捕获第三样本数据集合的第三捕获组件; 第三生成组件,其生成与所述第三样本数据集的一部分相关联的第三变化矩阵; 将所述第三变化矩阵与所述第一变化矩阵进行比较以获得第一比较的比较部,将所述第三变化矩阵与所述第二变化矩阵进行比较,得到第二比较; 以及适配部件,其基于第一比较和第二比较中的一个来适配数字预失真分量与第三样本数据集合。

    Subtracting linear impairments for non-linear impairment digital pre-distortion error signal
    6.
    发明授权
    Subtracting linear impairments for non-linear impairment digital pre-distortion error signal 有权
    减去非线性损伤数字预失真误差信号的线性损伤

    公开(公告)号:US09136887B2

    公开(公告)日:2015-09-15

    申请号:US14185888

    申请日:2014-02-20

    CPC classification number: H04B1/0475 H03F1/3241 H04B2001/0425

    Abstract: Example embodiment of the systems and methods of linear impairment modeling to improve digital pre-distortion adaptation performance includes a DPD module that is modified during each sample by a DPD adaptation engine. A linear impairment modeling module separates the linear and non-linear errors introduced in the power amplifier. The linear impairment model is adjusted during each sample using inputs from the input signal and from a FB post processing module. The linear impairment modeling module removes the linear errors such that the DPD adaptation engine only adapts the DPD module based on the non-linear errors. This increases system stability and allows for the correction of IQ imbalance inside the linear impairment modeling, simplifying the feedback post-processing.

    Abstract translation: 用于改善数字预失真适应性能的线性损伤建模的系统和方法的示例性实施例包括在DPD适配引擎的每个采样期间修改的DPD模块。 线性损伤建模模块分离功率放大器中引入的线性和非线性误差。 在每个采样中使用输入信号和FB后处理模块的输入调整线性损伤模型。 线性损伤建模模块消除线性误差,使得DPD自适应引擎仅基于非线性误差来适应DPD模块。 这增加了系统稳定性,并允许在线性损伤建模中对IQ不平衡进行校正,从而简化了反馈后处理。

    Dynamic determination of volterra kernels for digital pre-distortion
    8.
    发明授权
    Dynamic determination of volterra kernels for digital pre-distortion 有权
    用于数字预失真的Volterra内核的动态确定

    公开(公告)号:US08804872B1

    公开(公告)日:2014-08-12

    申请号:US13752577

    申请日:2013-01-29

    CPC classification number: H04L27/368

    Abstract: A method of dynamically calculating and updating the Volterra kernels used by the Digital Pre Distortion engine based on output power, input signal bandwidth, multicarrier configuration, frequency response and power amplifier temperature. A dominant Volterra kernels searching DSP engine based on innovation bases with minimum RMS error selection is implemented to continuously update the Volterra kernels set used in DPD to model the power amplifier non linear behaviors.

    Abstract translation: 一种基于输出功率,输入信号带宽,多载波配置,频率响应和功率放大器温度动态计算和更新数字预失真引擎使用的Volterra内核的方法。 基于具有最小RMS误差选择的创新基础的主导Volterra内核搜索DSP引擎实现了持续更新DPD中使用的Volterra内核集,以对功率放大器的非线性行为进行建模。

    Dynamic Determination of Volterra Kernels for Digital Pre-Distortion
    9.
    发明申请
    Dynamic Determination of Volterra Kernels for Digital Pre-Distortion 有权
    用于数字预失真的Volterra内核的动态确定

    公开(公告)号:US20140211882A1

    公开(公告)日:2014-07-31

    申请号:US13752577

    申请日:2013-01-29

    CPC classification number: H04L27/368

    Abstract: A method of dynamically calculating and updating the Volterra kernels used by the Digital Pre Distortion engine based on output power, input signal bandwidth, multicarrier configuration, frequency response and power amplifier temperature. A dominant Volterra kernels searching DSP engine based on innovation bases with minimum RMS error selection is implemented to continuously update the Volterra kernels set used in DPD to model the power amplifier non linear behaviours.

    Abstract translation: 一种基于输出功率,输入信号带宽,多载波配置,频率响应和功率放大器温度动态计算和更新数字预失真引擎使用的Volterra内核的方法。 基于具有最小RMS误差选择的创新基础的主导Volterra内核搜索DSP引擎实现了持续更新DPD中使用的Volterra内核集,以对功率放大器的非线性行为进行建模。

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