Digitally Assisted Pipeline ADCs: Theory and Implementation

Digitally Assisted Pipeline ADCs: Theory and Implementation explores the opportunity to reduce ADC power dissipation by leveraging digital signal processing capabilities in fine line integrated circuit technology. The described digitally assisted pipelined ADC uses a statistics-based system identification technique as an enabling element to replace precision residue amplifiers with simple open-loop gain stages. The digital compensation of analog circuit distortion eliminates one key factor in the classical noise-speed-linearity constraint loop and thereby enables a significant power reduction.

Digitally Assisted Pipeline ADCs: Theory and Implementation describes in detail the implementation and measurement results of a 12-bit, 75-MSample/sec proof-of-concept prototype. The Experimental converter achieves power savings greater than 60% over conventional implementations.

Digitally Assisted Pipeline ADCs: Theory and Implementation will be of interest to researchers and professionals interested in advances of state-of-the-art in A/D conversion techniques.

 

Table of Contents

List of Figures. List of Tables. Acknowledgements. Preface. 1: Introduction. 1. Motivation. 2. Overview. 3. Chapter Organization. 2: Performance Trends. 1. Introduction. 2. Digital Performance Trends. 3. ADC Performance Trends. 3: Scaling Analysis. 1. Introduction. 2. Basic Device Scaling from a Digital Perspective. 3. Technology Metrics for Analog Circuits. 4. Scaling Impact on Matching-Limited Circuits. 5. Scaling Impact on Noise-Limited Circuits. 4: Improving Analog Circuit Efficiency. 1. Introduction. 2. Analog Circuit Challenges. 3. The Cost of Feedback. 4. Two-Stage Feedback Amplifier vs. Open-Loop Gain Stage. 5. Discussion. 5: Open-Loop Pipelined ADCs. 1. A Brief Review of Pipelined ADCs. 2. Conventional Stage Implementation. 3. Open-Loop Pipeline Stages. 4. Alternative Transconductor Implementations. 6: Digital Nonlinearity Correction. 1. Overview. 2. Error Model and Digital Correction. 3. Alternative Error Models. 7: Statistics-Based Parameter Estimation. 1. Introduction. 2. Modulation Approach. 3. Required Sub-ADC and Sub-DAC Redundancy. 4. Parameter Estimation Based on Residue Differences. 5. Statistics Based Difference Estimation. 6. Complete Estimation Block. 7. Simulation Example. 8. Discussion. 8: Prototype Implementation. 1. ADC Architecture. 2. Stage 1. 3. Stage 2. 4. Post-Processor. 9: Experimental Results. 1. Layout and Packaging. 2. Test Setup. 3. Measured Results. 4. Post-Processor Complexity. 10: Conclusion. 1. Summary. 2. Suggestions for Future Work. Appendices. A: Open-Loop Charge Redistribution. B: Estimator Variance. C: LMS Loop Analysis. 1. Time Constant. 2. Output Variance. 3. Maximum Gain Parameters. References. Index.