AC Computing Methodology for RF-Powered IoT Devices

Abstract

In this paper, an alternating current (ac) computing methodology is proposed for integration into wirelessly powered devices, such as radio-frequency (RF) tags and sensor nodes. Contrary to the traditional platforms that integrate direct current (dc)-powered computational logic along with the rectification and regulation stages, in the proposed approach, the harvested RF signal is directly used to power the data processing circuitry by leveraging the charge-recycling and adiabatic circuit theory. A near-field-based wireless power harvesting system with an 8-bit arithmetic logic unit is developed to evaluate the proposed framework. Simulation results in 45-nm technology demonstrate that the overall power consumption can be reduced by up to 16 times as compared to the conventional approach that relies on ac-to-dc conversion and static CMOS logic. This reduction in power enables significant computation capability for the RF-powered devices. Several important characteristics, such as the impact of circuit size on overhead and processing power, impact of voltage scaling on circuit operation, and power consumption, are investigated. Some important design issues and related tradeoffs are also discussed.