面向复杂多陷阱的随机电报噪声提取技术  

Extraction technology of random telegraph noise under complex multi-trap conditions

作　　者：肖雨 纪志罡 XIAO Yu;JI Zhi-gang(Department of Micro/Nano Electronics,Shanghai Jiao Tong University,Shanghai 200240,China)

机构地区：[1]上海交通大学微纳电子系,上海200240

出　　处：《计算机工程与科学》2023年第4期582-589,共8页Computer Engineering & Science

摘　　要：随着集成电路的发展,器件尺寸不断减小,导致MOSFET栅氧化层中的陷阱增多。低频噪声随之产生,尤其是随机电报噪声RTN变得愈发明显,对器件的可靠性提出了挑战。当器件中的陷阱个数多于1个时,陷阱间的耦合效应也对RTN信号的分析产生了重要影响。因此,开展针对复杂多陷阱情况下的RTN信号的提取技术的研究变得尤为迫切。目前现存的RTN提取技术在处理大数据量时迭代所耗费的时间成本大,且自动化程度不高,这些问题亟需解决。基于RTN信号非高斯性质,提出了自动化检测RTN信号的方法和自动化判定陷阱数方法,使得RTN信号的提取更加准确和高效。另外,还针对迭代过程中重要参数提出了自适应模型的方法,实现了大部分RTN信号提取的迭代加速。最后,对实测RTN信号应用上述方法进行参数提取,并分析了耦合效应对参数产生的影响。With the development of integrated circuits,the size of devices decreases,which leads to the increase of traps in MOSFET gate oxide layer.The generated low frequency noise,especially Random Telegraph Noise(RTN),becomes more and more obvious,which challenges the reliability of devices.When there are more than one trap in the device,the coupling effect between traps also has an important influence on the analysis of RTN signals.Therefore,it is particularly urgent to carry out research on RTN signal extraction technology in complex and multi-trap situations.At present,the existing RTN extraction technology consumes a lot of time when processing large amounts of data,and the degree of automation is not high.These problems need to be solved urgently.In this paper,based on the non-Gaussian property of RTN signal,an automatic detection method of RTN signal and an automatic detection method of trap number are proposed,which makes the extraction of RTN signal more accurate and efficient.In addition,this paper also proposes an adaptive model for important parameters in the iterative process,and realizes the iterative acceleration of most RTN signal extraction.Finally,the method is used to extract parameters of the measured RTN signal,and the influence of coupling effect on the parameters is analyzed.

关 键 词：随机电报噪声 隐式马尔可夫模型 耦合效应 高斯判断 自适应模型 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]