Low Energy Design Techniques For Data Converters

Abstract

Analog to Digital Converters (ADCs) are crucial to capture data in almost any Internet of Everything (IoE) device as sensed physical signals have to be converted into digital data, before some processing and data transmission can take place. Today, ADCs are designed for low supply energy consumption, usually expressed in energy-per-conversion step which for state-of-the art architecture is (stagnated) ~ 1fJ/conversion-step. However, the energy consumed from the always ON sensor interface circuitry e.g. the input driver is usually not taken into account and seldom addressed. This input drive energy (usually larger than the ADC supply energy) presents a major challenge in minimizing the energy consumption of e.g. autonomous and event-driven IoE applications. This thesis presents design techniques to reduce the amount of energy required to perform various operations during data conversion, such as comparison, buffering the input signal and sampling the buffered input signal. These techniques aim at reducing the amount of charge (and energy) required to perform each of these operations that require a certain capacitance to satisfy the theoretical kT/C noise limit for a given SNR. The energy consumption for charging-discharging of this capacitor is reduced by minimizing the voltage change across this capacitor for the operations mentioned above without compromising the SNR. The low energy design techniques presented in this thesis contributed towards attaining the lowest reported Walden FoM of 0.35 fJ/conv-step for the standalone SAR ADC. When including the energy consumption of the buffers the Walden FoM of 87 fJ/conv-step (using only a single supply voltage) is also the lowest among all the reported buffered SAR ADCs to the best of my knowledge. In addition the design techniques presented in this thesis allow the buffered SAR ADC to operate from a single supply voltage (1.2 V) thereby alleviating the need of any additional supply voltage level to interface with wireless sensor nodes.