With more and more integration of analog and RF circuits in scaled CMOS technologies, process variation is playing a critical role which makes it difficult to achieve all the performance specifications across all the process corners. Moreover, at scaled technology nodes, due to lower voltage and current handling capabilities of the devices, they suffer from reliability issues that reduce the overall lifetime of the system. Finally, traditional static style of designing analog and RF circuits does not result in optimal performance of the system. A new design paradigm is emerging toward digitally assisted analog and RF circuits and systems aiming to leverage digital correction and calibration techniques to detect and compensate for the manufacturing imperfections and improve the analog and RF performance offering a high level of integration. The objective of the proposed research is to design digital friendly and performance tunable adaptive analog/RF circuits and systems with digital enhancement techniques for higher performance, better process variation tolerance, and more reliable operation and developing strategy for testing the proposed adaptive systems. An adaptation framework is developed for process variation tolerant RF systems which has two parts – optimized test stimulus driven diagnosis of individual modules and power optimal system level tuning. Another direct tuning approach is developed and demonstrated on a carbon nanotube based analog circuit. An adaptive switched mode power amplifier is designed which is more digital-intensive in nature and has higher efficiency, improved reliability and better process resiliency. Finally, a testing strategy for adaptive RF systems is shown which reduces test time and test cost compared to traditional testing.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/52919 |
| Date | 12 January 2015 |
| Creators | Banerjee, Aritra |
| Contributors | Chatterjee, Abhijit |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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