A micropower programmable DSP using approximate signal processing based on distributed arithmetic

Abstract

A recent trend in low-power design has been the employment of reduced precision processing methods for decreasing arithmetic activity and average power dissipation. Such designs can trade off power and arithmetic precision as system requirements change. This work explores the potentialof distributed arithmetic (DA) computation structures for low-power precision-on-demand computation. We present an ultralow-power DSP which uses variable precision arithmetic, low-voltage circuits, and conditional clocks to implement a biomedical detection and classification algorithm using only 560 nW. Low energy consumption enables self-powered operation using ambient mechanical vibrations, converted to electric energy by a MEMS transducer and accompanying power electronics. The MEMS energy scavenging system is estimated to deliver 4.3 to 5.6 μW of power to the DSP load.