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首页> 外文期刊>IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems >A study of a hybrid phase-pole macromodel for transient simulation of complex interconnects structures
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A study of a hybrid phase-pole macromodel for transient simulation of complex interconnects structures

机译:复杂相干结构瞬态仿真的混合相极宏模型研究

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An overview of standard macromodeling techniques (i.e., employ poles but no phase shifts) for transient simulation of high-speed interconnects is first presented. Then, the limitations of these standard macromodeling techniques (e.g., high model order and slow convergence) are discussed. In order to overcome these limitations, generalized method of characteristics (MoC) techniques include the physical phenomenology of phase shift (time delay) in addition to the system poles, thereby making it possible to model single and coupled transmission lines using far fewer terms than when standard macromodeling techniques are employed. Since MoC techniques incorporate the time delay into the model, causality is also guaranteed. In this paper, the MoC idea is extended by developing a hybrid phase-pole macromodel (HPPM) for the modeling of more complex interconnects with embedded discontinuities. Unlike other generalized MoC techniques that have only been applied to single and coupled transmission lines, the HPPM macromodel can be applied to larger portions of the system that contain multiple cascaded transmission lines and discontinuities. The HPPM parameters can be extracted from either measured or simulated transient data. Comparisons between a standard macromodel and the HPPM show that the HPPM has significant advantages in terms of reduced macromodel orders.
机译:首先介绍了用于高速互连的瞬态仿真的标准宏模型技术(即采用极点但没有相移)的概述。然后,讨论了这些标准宏建模技术的局限性(例如,高模型阶数和缓慢收敛)。为了克服这些限制,除了系统极点以外,通用的特征方法(MoC)技术还包括相移的物理现象(时间延迟),从而可以比使用时少得多的项对单个和耦合的传输线进行建模。使用标准的宏建模技术。由于MoC技术将时间延迟纳入了模型,因此也可以保证因果关系。在本文中,通过开发混合相-极宏模型(HPPM)扩展了MoC的思想,该模型用于对具有嵌入式不连续性的更复杂互连进行建模。与仅应用于单个和耦合传输线的其他广义MoC技术不同,HPPM宏模型可以应用于包含多个级联传输线和不连续性的系统的较大部分。 HPPM参数可以从测量的或模拟的瞬态数据中提取。标准宏模型与HPPM之间的比较表明,在减少宏模型订单方面,HPPM具有显着优势。

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