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Effects like NBTI and HCI are degrading the characteristics of analog circuits. Available countermeasures to maintain system performances often include the use of optimizers or other external tools to size devices appropriately, which give no insight in relations between degradation and circuit parameters for the designer. This paper proposes an extension of the g m/ID sizing method by considering aged transistor parameters for fresh circuit design. A possible usage scenario for this investigation is given by optimizing a simple circuit towards higher reliability. The degradation in amplification of a common source amplifier is reduced by 19 % for a full time operation of 10 years.

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Scaled down CMOS transistors are prone to degra dation and process variation. This necessitates a transistor model that provides an insight into the internal dependencies between these two crucial effects. Models for modern transistors and their degradation behavior are hardly attachable. This paper proposes a modified BSIM6 model which includes degradation due to BTl and HCI and in addition process variations. The application of this method is demonstrated on the basis of a single MOSFET and an inverter stage. The results can be used in the grn/1d work flow or for yield estimation on circuit level.

For safety-critical applications with long operational lifetimes the analysis of aging aspects caused by NBTI and HCD is moving into the focus of the designer. The increasing complexity of modern analog and mixed-signal circuits makes a reliability analysis on transistor level for complex systems quite challenging. In this paper we present a method using BoxBehnken Designs and Response Surface Modeling with exponential function interpolation. This approach enables accelerated reliability analysis on system level. A tool is introduced to support the behavioral model generation process. The derived model includes information on degradation and process variations. The method is demonstrated for a current-mirror and a CS amplifier to quantify the degradation influence. The accuracy of the behavioral models and the age-dependent yield of the circuits is determined.

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