Energy-Efficient Mixed-Signal Circuits and Systems for Communication and Signal Processing
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In recent years, there has been an explosive increase in the amount of digital data generated globally, driven by a variety of online applications. With the rise of deep learning and Internet of Things (IoT), this trend is likely to be maintained for the foreseeable future. The major portion of the data will be generated from endpoint devices whereas it will be stored in the clouds, creating the capacity and energy issues in the data centers and networks. Therefore, to sustain this rapid growth of data, it is critical to develop faster and energy efficient communication and network systems, while reducing the data traffic with the efficient processing of data. This dissertation introduces three major topics on energy-efficient mixed signal circuits and systems that addresses the aforementioned issues: (1) a low jitter energy efficient ring-oscillator based PLL with reference oversampling technique which achieves wide bandwidth to suppress the ring oscillator noise, (2) a 67fs rms ultra-low jitter and low spur LC-oscillator based PLL using the reference oversampling techniques, (3) a low power keyword spotting system with dynamic neural network which adaptively power gates the entire system including the analog front end and the digital back end.
Professor David Blaauw, Co-Chair
Professor Dennis Sylvester, Co-Chair