Survey of Robustness Enhancement Techniques for Wireless Systems-on-a-Chip and Study of Temperature as Observable for Process Variations

  • Authors:
  • Marvin Onabajo;Didac Gómez;Eduardo Aldrete-Vidrio;Josep Altet;Diego Mateo;Jose Silva-Martinez

  • Affiliations:
  • Department of Electrical & Computer Eng., Texas A&M University, College Station, USA 77843-3128;Department of Electronic Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain 08034;Department of Electronic Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain 08034;Department of Electronic Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain 08034;Department of Electronic Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain 08034;Department of Electrical & Computer Eng., Texas A&M University, College Station, USA 77843-3128

  • Venue:
  • Journal of Electronic Testing: Theory and Applications
  • Year:
  • 2011

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Abstract

Built-in test and on-chip calibration features are becoming essential for reliable wireless connectivity of next generation devices suffering from increasing process variations in CMOS technologies. This paper contains an overview of contemporary self-test and performance enhancement strategies for single-chip transceivers. In general, a trend has emerged to combine several techniques involving process variability monitoring, digital calibration, and tuning of analog circuits. Special attention is directed towards the investigation of temperature as an observable for process variations, given that thermal coupling through the silicon substrate has recently been demonstrated as mechanism to monitor the performances of analog circuits. Both Monte Carlo simulations and experimental results are presented in this paper to show that circuit-level specifications exhibit correlations with silicon surface temperature changes. Since temperature changes can be measured with efficient on-chip differential temperature sensors, a conceptual outline is given for the use of temperature sensors as alternative process variation monitors.