A Physics-Based Statistical RTN Model for the Low Frequency Noise in MOSFETs

Abstract

In this paper, we develop a statistical model for random telegraph noise (RTN) related low-frequency noise (LFN). With our proposed model, one can calculate the expected value and the variability of the noise as a function of bias and device parameters. We clarify why the variability of RTN/LFN does not follow a 1/ $\surd $ area dependence. The model explains the effect of the halo implanted regions on the LFN statistics and the large variability of long channel devices found under certain bias conditions, which can be as large as that of short channel devices. We show that the LFN of n-channel and p-channel MOSFETs can be described by the same mechanism. From our results, we derive that the trap density of the p-channel device is a strongly varying function of the Fermi level, whereas for the n-channel the trap density can be considered constant. We validate the model through numerous experimental results from different CMOS nodes, down to 40 nm. We also demonstrate that the noise, and its variability, found in our measurements can be modeled using reasonable physical quantities.