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Background Calibration of Comparator Offsets in SHA-Less Pipelined ADCs

机译:SHA-Less流水线ADC中比较器失调的背景校准

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摘要

Sample-and-hold amplifier-less (SHA-less) pipelined analog-to-digital converters (ADCs) are well suited for high-resolution, high-speed and low-power applications. Apart from the comparator static offset, a dynamic offset is induced due to the timing skew and bandwidth mismatch between the multiplying digital-to-analog converter and the comparator input paths in the first stage, which brings a serious design challenge. This brief presents a novel background calibration technique for these offsets. First, the comparator's static offset and dynamic offset are discussed and analyzed. Then, a new evaluation technique is proposed to synchronously extract the values of the static offset and dynamic offset through the residue output at decision points. In this brief, the new calibration method is validated using behavioral models. The effective number of bits is improved from 5.04 bits to 11.96 bits, while the spurious free dynamic range is improved by 50.7 dB from our simulation. Thanks to the background calibration, comparator offset errors exceeding the built-in redundancy of the architecture become acceptable. The proposed method relaxes comparator design requirements effectively. More importantly, the calibration can maximize the input frequency of the SHA-less pipelined ADCs.
机译:无采样保持放大器(无SHA)流水线模数转换器(ADC)非常适合高分辨率,高速和低功耗应用。除了比较器静态偏移以外,在第一阶段,由于倍增数模转换器和比较器输入路径之间的时序偏斜和带宽不匹配,还会引起动态偏移。这给设计带来了严峻的挑战。本简介为这些偏移量提供了一种新颖的背景校准技术。首先,讨论并分析了比较器的静态偏移和动态偏移。然后,提出了一种新的评估技术,通过决策点的残差输出来同步提取静态偏移和动态偏移的值。在本文中,使用行为模型验证了新的校准方法。有效位数从5.04位提高到11.96位,而无杂散动态范围从我们的仿真中提高了50.7 dB。由于进行了背景校准,所以可以接受超出架构内置冗余的比较器失调误差。所提出的方法有效地放宽了比较器的设计要求。更重要的是,校准可以最大化无SHA流水线ADC的输入频率。

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