Indirect Performance Sensing for On-Chip Self-Healing of Analog and RF Circuits
IEEE Trans. on Circuits and Systems(2014)
摘要
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.
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关键词
process variation,CMOS analogue integrated circuits,parametric yield,frequency 25 GHz,nanoscale integrated circuit,voltage-controlled oscillators,RF performance metrics,Indirect performance sensing,indirect performance sensing,radiofrequency integrated circuits,on-chip self-healing,analog integrated circuit,silicon-on-insulator,VCO,size 32 nm,RF circuits,integrated circuit,self-healing,differential Colpitts voltage-controlled oscillator,CMOS SOI process
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