Indirect performance sensing for on-chip self-healing of analog and RF circuits


Journal Article

The advent of the nanoscale integrated circuit (IC) technology makes high performance analog and RF circuits increasingly susceptible to large-scale process variations. On-chip self-healing has been proposed as a promising remedy to address the variability issue. The key idea of on-chip self-healing is to adaptively adjust a set of on-chip tuning knobs (e.g., bias voltage) in order to satisfy all performance specifications. One major challenge with on-chip self-healing is to efficiently implement on-chip sensors to accurately measure various analog and RF performance metrics. In this paper, we propose a novel indirect performance sensing technique to facilitate inexpensive-yet-accurate on-chip performance measurement. Towards this goal, several advanced statistical algorithms (i.e., sparse regression and Bayesian inference) are adopted from the statistics community. A 25 GHz differential Colpitts voltage-controlled oscillator (VCO) designed in a 32 nm CMOS SOI process is used to validate the proposed indirect performance sensing and self-healing methodology. Our silicon measurement results demonstrate that the parametric yield of the VCO is significantly improved for a wafer after the proposed self-healing is applied. © 2014 IEEE.

Full Text

Duke Authors

Cited Authors

  • Sun, S; Wang, F; Yaldiz, S; Li, X; Pileggi, L; Natarajan, A; Ferriss, M; Plouchart, JO; Sadhu, B; Parker, B; Valdes-Garcia, A; Sanduleanu, MAT; Tierno, J; Friedman, D

Published Date

  • January 1, 2014

Published In

Volume / Issue

  • 61 / 8

Start / End Page

  • 2243 - 2252

International Standard Serial Number (ISSN)

  • 1549-8328

Digital Object Identifier (DOI)

  • 10.1109/TCSI.2014.2333311

Citation Source

  • Scopus