基于训练数据模式的8Gb/s自适应DFE移动DRAM接口电平校准

Minchang Kim, Jihwan Park, Joo-Hyung Chae, H. Ko, Mino Kim, Suhwan Kim
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引用次数: 0

摘要

设计了一种基于训练序列的8Gb/s自适应决策反馈均衡器(DFE)。训练数据模式“10111111”用于周期性检测失真数据水平。通过补偿失真数据电平与理想高直流电平之间的差值,在训练模式中自动调整分接系数。在1.05V供电电压下,功耗为10.4mW,自适应时间为90ns。仿真结果表明,对抽头系数进行训练后,数据眼得到了改善。数据眼宽度和高度分别从0.36UI提高到0.84UI,从40mV提高到90mV。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An 8Gb/s adaptive DFE with level calibration using training data pattern for mobile DRAM interface
An 8Gb/s adaptive decision feedback equalizer (DFE) using training sequence is designed in a 65nm CMOS. The training data pattern ‘10111111’ is used to detect distorted data level periodically. The tap coefficients are automatically adjusted during the training mode by compensating for the difference between the distorted data level and ideal high DC level. The power consumption is 10.4mW at 1.05V supply voltage and the adaptation time is 90ns. The simulation results show the improvement of data eye after training the tap coefficients. The data eye width and height are improved from 0.36UI to 0.84UI and from 40mV to 90mV, respectively.
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