Improving the accuracy of RF alternate test using multi-VDD conditions: application to envelope-based test of LNAs

Trabajo presentado al "20 Asina Test Symposium" celebrado en Nueva Delhi (India) del 20 al 23 de Noviembre del 2011.-- Reprinted from (relevant publication info). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the products or services of CSIC Spanish National Research Council, Digital.CSIC. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This work demonstrates that multi-VDD conditions may be used to improve the accuracy of machine learning mod- els, significantly decreasing the prediction error. The proposed technique has been successfully applied to a previous alternate test strategy for LNAs based on response envelope detection. A prototype has been developed to show its feasibility. The prototype consists of a low-power 2.4GHz LNA and a simple envelope detector, integrated in a 90nm CMOS technology. Post- layout simulation results are provided to verify the functionality of the approach. Copyright © 2011 IEEE.This work has been partially funded by a CSIC JAE-Doc contract (cofinanced by FSE), a Spanish MAE-AECID grant and projects: SR2 - Short Range Radio (Catrene European project 2A105SR2 and Avanza I+D Spanish project TSI-020400-2010-55, cofinanced with FEDER program), Auto-calibración y auto-test en circuitos analógicos, mixtos y de radio frecuencia (Andalusian Government project P09-TIC-5386, cofinanced with FEDER program), and Catrene project TOETS (CT 302).Peer reviewe

Feature selection and feature design for machine learning indirect test: a tutorial review

International audienc

Alternate test of LNAs through ensemble learning of on-chip digital envelope signatures

El pdf del artículo es el manuscrito de autor.This paper presents a novel and low-cost methodology for testing embedded Low Noise Amplifiers (LNAs). It is based on the detection and analysis of the response envelope of the Device Under Test (DUT) to a two-tone input signal. The envelope signal is processed to obtain a digital signature sensitive to key specifications of the DUT. An optimized regression model based on ensemble learning is used to relate the digital signatures to the target specifications. A new Figure of Merit (FOM) is proposed to evaluate the prediction accuracy of the statistical model, and a demonstrator has been developed to prove the feasibility of the approach. This demonstrator features a 2.445 GHz low-power LNA and a simple envelope detector, and has been developed in a 90 nm CMOS technology. Post-layout simulations are provided to verify the functionality of the proposed test techniqueThis work has been funded in part by the Spanish Government and FEDER funds through projects TEST (TEC2007-68072/MIC), SR2 (TSI-020400-2008-71/MEDEA+2A105), TOETS (CATRENE CT302), and by the Junta de Andalucia through project ACATEX (P09-TIC-5386).Peer reviewe