A de-embedding method with matrix rectification and influences of residual errors on model parameters extraction of InP HEMTs
A de-embedding method with matrix rectification and influences of residual errors on model parameters extraction of InP HEMTs
复制标题
矩阵校正去嵌入方法及残余误差对InP HEMT模型参数提取的影响
DOI：
10.1002/mmce.22218
复制
发表时间：
2020
影响因子：
1.7
通讯作者：
Jin Zhi
中科院分区：
文献类型：
--
作者：
Ding Wuchang;Ding Peng;Su Yongbo;Zhou Jingtao;Yang Feng;Hu Jun;Peng Songang;Shi Jingyuan;Zhang Dayong;Jin Zhi
随着InP HEMT的截止频率进入太赫兹频段，数百千兆赫的高频测量和建模技术成为进一步毫米波单片集成电路设计的迫切需要。我们提出了一种基于HFSS和高级设计系统(ADS)获得的完整电磁仿真数据的器件测量和建模相结合的去嵌入方法。对无源虚拟结构的模拟结果与实验结果吻合较好，证明了该去嵌入方法对于高分布埋入环境的阻性无源器件在40 GHz以下的频率范围内非常有效。基于这些实验事实，将电磁模拟扩展到300 GHz，并进一步研究了相应的去嵌入偏差。结果表明，该去嵌入方法在整个频段内具有很高的精度，最大参数偏差仅为2.58%。然而，进一步的分析证明，小的残差仍然对提取的InP HEMT的小信号模型参数有显著的影响，特别是对于渡越时间τ。因此，需要进一步提高去嵌入精度或在建模过程中仔细考虑更多的误差函数，以获得具有物理意义的模型参数。
As the cutoff frequency of InP HEMTs enters the terahertz band, high frequency measurement and modeling techniques in hundreds of gigahertz become urgent needs for further millimeter monolithic integrated circuits design. We proposed a new de‐embedding method linking device measurements and modeling based on full EM simulation data acquired from HFSS and advanced design system (ADS). The simulation results for passive dummy structures are well consistent with experiments, and the de‐embedding method is proved very effective for a resistive passive device with high distributed embedding surroundings in frequency range below 40 GHz. Based on these experimental facts, the EM simulations were extended up to 300 GHz and corresponding de‐embedding deviation was further investigated. Results show that the proposed de‐embedding method has very high accuracy in the whole frequency region with a maximumS‐parameters deviation of only 2.58%. However, further analysis proves that the small residual errors still significantly affect extracted small signal model parameters of InP HEMTs especially for transit timeτ. Thus, further improvements on de‐embedding accuracy or careful considerations of more error functions in modeling process are necessary for obtaining physically meaningful model parameters.