Design of self-healing mixed-signal/RF systems and support CAD tools: A scalable approach

Due to the proliferation of nanometer CMOS mixed-signal/RF circuits and a push towards high operating speeds (5-100 Ghz+), there has been renewed interest in the design of high-speed circuits and systems that can self-calibrate and self-heal post-manufacture and in the field. In the past, designers have invented self-healing mechanisms that are tailored towards specific (critical) mixed-signal/RF performance metrics of specific circuit architectures (transmitter, receiver, etc). What is desired, however, is the ability to monitor multiple performance metrics concurrently and trade them off against one another in an optimal manner, through performance tuning mechanisms, to satisfy system-level Quality of Service (QoS) guarantees. Further, the methods employed must be scalable across different device types/circuit architectures and supported by CAD tools that enable automation of self-healing design procedures. In this paper, recent research advances are presented that allow low cost and rapid self-healing of complex mixed-signal/RF systems and enable the development of design automation tools to support such activity across diverse performance metrics and circuit types.

[1]  Abhijit Chatterjee,et al.  Efficient system-level testing and adaptive tuning of MIMO-OFDM wireless transmitters , 2013, 2013 18th IEEE European Test Symposium (ETS).

[2]  Abhijit Chatterjee,et al.  Orthogonally tunable inductorless RF LNA for adaptive wireless systems , 2011, 2011 IEEE International Symposium of Circuits and Systems (ISCAS).

[3]  Hua Wang,et al.  A CMOS Broadband Power Amplifier With a Transformer-Based High-Order Output Matching Network , 2010, IEEE Journal of Solid-State Circuits.

[4]  John D. Cressler,et al.  A 6–20 GHz Adaptive SiGe Image Reject Mixer for a Self-Healing Receiver , 2012, IEEE Journal of Solid-State Circuits.

[5]  Abhijit Chatterjee,et al.  DSP-Driven Self-Tuning of RF Circuits for Process-Induced Performance Variability , 2010, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[6]  Abhijit Chatterjee,et al.  Optimized Multitone Test Stimulus Driven Diagnosis of RF Transceivers Using Model Parameter Estimation , 2011, 2011 24th Internatioal Conference on VLSI Design.

[7]  James Tschanz,et al.  Parameter variations and impact on circuits and microarchitecture , 2003, Proceedings 2003. Design Automation Conference (IEEE Cat. No.03CH37451).

[8]  Abhijit Chatterjee,et al.  Digitally Assisted Concurrent Built-In Tuning of RF Systems Using Hamming Distance Proportional Signatures , 2010, 2010 19th IEEE Asian Test Symposium.

[9]  A. Hajimiri,et al.  A fully-integrated self-healing power amplifier , 2012, 2012 IEEE Radio Frequency Integrated Circuits Symposium.

[10]  Abhijit Chatterjee,et al.  Design of process variation tolerant radio frequency low noise amplifier , 2008, 2008 IEEE International Symposium on Circuits and Systems.

[11]  Abhijit Chatterjee,et al.  A holistic approach to accurate tuning of RF systems for large and small multiparameter perturbations , 2010, 2010 28th VLSI Test Symposium (VTS).

[12]  J. Freidman,et al.  Multivariate adaptive regression splines , 1991 .

[13]  Abhijit Chatterjee,et al.  Analog Signature- Driven Postmanufacture Multidimensional Tuning of RF Systems , 2010, IEEE Design & Test of Computers.

[14]  Abhijit Chatterjee,et al.  Built-in Test Enabled Diagnosis and Tuning of RF Transmitter Systems , 2008, VLSI Design.