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AC Computing Methodology for RF-Powered IoT Devices

机译:射频供电的物联网设备的交流计算方法

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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.
机译:在本文中,提出了一种交流(ac)计算方法,用于集成到无线设备中,例如射频(RF)标签和传感器节点。与将直流(dc)供电的计算逻辑以及整流和调节级集成在一起的传统平台相反,在提出的方法中,通过利用电荷循环和绝热技术,将采集到的RF信号直接用于为数据处理电路供电。电路理论。开发了具有8位算术逻辑单元的基于近场的无线电力收集系统,以评估所提出的框架。 45纳米技术的仿真结果表明,与传统的依赖于AC-DC转换和静态CMOS逻辑的方法相比,总功耗可降低多达16倍。功耗的降低使射频供电设备具有显着的计算能力。研究了几个重要的特性,例如电路大小对开销和处理能力的影响,电压缩放对电路操作的影响以及功耗。还讨论了一些重要的设计问题和相关的取舍。

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