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Evaluation of multi-level Bang-Bang phase detector with metastability effect using Markov chain

机译:利用马尔可夫链评价多级BANG-BANG相位检测器的亚运动效应

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摘要

Bang-Bang phase detector (BBPD) as a bistable system has the metastability problem. In addition, BBPD is a non-linear block in the phase locked-loop (PLL) and clock and data recovery (CDR) that makes their analysis complicate. To simplify the analysis of the non-linear BBPD, the linear expression for the gain of multi-level BBPD (ML-BBPD) is derived in this paper by considering the metastability failure. The ML-BBPD gain is developed based on Markov chain to provide more realistic model. Simulation results show that the metastability failure not only attenuates the gain of ML-BBPD for the small input jitter, but also increases the output jitter and consequently the BER of the CDR. It is shown that by increasing the number of sampling clocks the output jitter and BER is reduced. Also, the gain of ML-BBPD is decreased for small values of the input jitter, but for the large values of input jitter ML-BBPD gain is the same for every over sampling ratio.
机译:BANG-BANG相位检测器(BBPD)作为双稳态系统具有稳定性问题。 另外,BBPD是锁相环(PLL)中的非线性块,以及时钟和数据恢复(CDR),使其分析复杂化。 为了简化非线性BBPD的分析,通过考虑亚稳定性故障,在本文中导出了多级BBPD(ML-BBPD)的增益的线性表达。 ML-BBPD增益是基于马尔可夫链开发的,以提供更现实的模型。 仿真结果表明,常温性失败不仅抑制了小型输入抖动的ML-BBPD的增益,还增加了输出抖动,从而增加了CDR的BER。 结果表明,通过增加抽样时钟的数量,输出抖动和BER减小。 而且,对于输入抖动的小值,ML-BBPD的增益降低,但对于每次采样比率,输入抖动ML-BBPD增益的大值相同。

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