Deconvolution algorithm dependencies of estimation errors of RTN effects on subnano-scaled SRAM margin variation

摘要

This paper compares the proposed technique with various MATLAB-built-in deconvolution-functions with regard to deconvolution errors, which have a crucial impact in reversing the effects of convolution with Random Telegraph Noise (RTN) on overall SRAM margin variations. The proposed technique successfully circumvents the issue of ringing error thanks to eliminating the need for any operations of differential, division, and maximum-likelihood gradient sequence. This advantage over the MATLAB-built-in deconvolution-functions has been demonstrated for the first time with applying it to a real analysis for the effects of the RTN on the overall SRAM margin variations. It has been shown that the proposed technique can reduce its cdf errors of the convolution of the deconvoluted-RTN with the Random Dopant Fluctuation (RDF) (i.e. fail-bit-count error) by 10-10 fold compared with the MATLAB-built-in deconvolution-functions.