A General Method to Evaluate RF BIST Techniques Based on Non-parametric Density Estimation

We present a general method to evaluate RF built- in self-test (BIST) techniques during the design stage. In particular, the adaptive kernel estimator is used to construct an estimate of the joint probability density function of the performances of the RF device under test and the actual BIST measurements. The density is sampled to generate a large volume of new data, which is subsequently used to estimate the relevant test metrics with parts per million (ppm) accuracy given the BIST limits. Thus, the BIST limits can be set to obtain the desired trade-offs between different test metrics. The proposed method aims to assist designers in comparing RF BIST techniques on the basis of accurately calculated test metrics and to provide information for early BIST refinements, thus reducing the design cycles. The method is demonstrated for a previously published RF BIST technique applied to an LNA.

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