Data Prediction Cuts Power Use in Wireless Sensors

Researchers at an unspecified institution present a new analog-to-digital converter (ADC) design that dramatically reduces power consumption for low-power applications like wearable health monitors and Internet of Things (IoT) devices. The team’s successive approximation register (SAR) ADC uses a Kalman filter to predict the four most significant bits of data from past conversions.

This allows for simultaneous switching of capacitors, eliminating unnecessary energy use. The design, implemented in a 180-nanometer CMOS process, operates in both a conventional mode and a predictive mode for reliable performance.

Testing shows the predictive mode reduces total power consumption by 50.3%, from 1.96 milliwatts to 0.975 milliwatts, at a 20 megasample per second rate and 1.8-volt supply. The ADC achieved a signal-to-noise ratio of 57.88 dB and a spurious-free dynamic range of 74.51 dB.