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A Predetermined LMS Digital Background Calibration Technique for Pipelined ADCs

机译:用于流水线ADC的预定LMS数字背景校准技术

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A digital background calibration technique for pipelined analog-to-digital converters (ADCs) is proposed to correct the capacitor mismatch, finite dc gain, and nonlinearity of residue amplifiers. It divides the pipelined ADC into two equal channels and changes the decision points of sub-ADCs with a pseudorandom sequence to perform the digital background calibration. The difference between the digital outputs of the channels is used to drive the least mean square (LMS) machine to correct the mentioned errors and also the mismatch between the channels. In order to speed up the error correction, an accurate estimation for the errors is identified. The estimation is done by utilizing a piecewise linear model and a slope mismatch measurement technique in the digital domain. Behavioral simulations of a 12-bit 100-MS/s split pipelined ADC show that the convergence time of the proposed LMS calibration technique is significantly reduced in comparison with the conventional LMS algorithm for the same signal-to-noise-and-distortion ratio.
机译:提出了一种用于流水线模数转换器(ADC)的数字背景校准技术,以校正电容器失配,有限的直流增益和残留放大器的非线性。它将流水线ADC分为两个相等的通道,并使用伪随机序列更改子ADC的决策点,以执行数字背景校准。通道数字输出之间的差异用于驱动最小均方(LMS)机器,以纠正上述错误以及通道之间的失配。为了加快错误校正,识别出错误的准确估计。通过利用分段线性模型和数字域中的斜率失配测量技术来完成估算。一个12位100-MS / s分离式流水线ADC的行为仿真表明,与传统LMS算法相比,在相同的信噪比下,该LMS校准技术的收敛时间显着减少。

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