Abstract

In the context of the Internet of Things, billions of devices—especially sensors—will be linked together in the next few years. A core component of wireless passive sensor nodes is the rectifier, which has to provide the circuit with sufficient operating voltage. In these devices, the rectifier has to be as energy efficient as possible in order to guarantee an optimal operation. Therefore, a numerical optimization scheme is proposed in this paper, which is able to find a unique optimal solution for an integrated Complementary Metal-Oxide-Semiconductor (CMOS) rectifier circuit with Self-Vth-Cancellation (SVC). An exploration of the parameter space is carried out in order to generate a meaningful target function for enhancing the rectified power for a fixed communication distance. In this paper, a mean conversion efficiency is introduced, which is a more valid target function for optimization than the Voltage Conversion Efficiency (VCE) and the commonly used Power Conversion Efficiency (PCE) and is defined as the arithmetic mean between PCE and VCE. Various trade-offs between output voltage, PCE, VCE and MCE are shown, which provide valuable information for low power rectifier designs. With the proposed method, a rectifier in a low power 55 nm process from Globalfoundries (GF55LPe) is optimized and simulated at −30 dBm input power. A mean PCE of 63.33% and a mean VCE of 63.40% is achieved.

Highlights

  • In the context of the Internet of Things (IoT), the number of connected nodes in future scenarios is estimated to be 20, 40 or even 50 billion devices [1,2,3,4]

  • The effectiveness of a rectifier circuit is mainly characterized by the Power Conversion Efficiency (PCE) and the Voltage Conversion Efficiency (VCE) per stage

  • We show that VCE

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Summary

Introduction

In the context of the Internet of Things (IoT), the number of connected nodes in future scenarios is estimated to be 20, 40 or even 50 billion devices [1,2,3,4]. A large number of these will be sensors, which can be used for gathering information and make our environment “intelligent”. This information can be used for making decisions and controlling actuators. To reduce the effort for installation, wireless sensor nodes will be the method of choice. This approach raises the problem of power supply. To reduce the environmental impact of batteries, passive wireless communication systems such as Ultra-High-Frequency (UHF) Radio-Frequency Identification (RFID) are attracting more and more attention [5,6,7,8,9]

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