A High-Efficiency Self-Powered Wireless Sensor Network Driven by Ambient RF Energy Far-Field

Wireless self-powered systems based on RF energy harvesting (RFEH) have emerged as an effective solution to the energy challenges in the Internet of Things devices (IoT). However, two critical challenges still persist: low energy harvesting efficiency at the receiver under low power conditions typical of long-distance scenarios, and the power range of RFEH not being suitable for most low-power IoT applications. To solve these problems, we proposed a high-efficiency RFEH system with wide input power range and high sensitivity. We employed harmonic suppression technology to mitigate higher-order harmonics generated by diodes and used radial stubs instead of capacitors and inductors to reduce insertion losses and parasitic effects. The proposed rectifier achieves a peak power efficiency of 74.4 % at 9.5 dBm. Efficiency remains above 50 % within the input power range of -8 to 15.5 dBm and exceeds 70 % between 2.5 to 11.5 dBm. Even at -14 dBm, a PCE of 30 % is maintained, significantly improving the efficiency of RFEH. Building on this RFEH system, we propose a dual-mode self-powered wireless sensor network system. Experimental results demonstrate that the low-power mode can operate up to 6 m away and have a minimum sensitivity of -10 dBm. The high-power (7 mW) mode can continuously monitor strain information for over 4.5 hours at 1 m. This system provides a solution for the widespread application of IoT in the future.

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Publication Details

Journal
IEEE Transactions on Instrumentation and Measurement
Published
2025-01-01
DOI
https://doi.org/10.1109/tim.2025.3552865
Citations
5
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
Field-Weighted Citation Impact
3.65

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article

A High-Efficiency Self-Powered Wireless Sensor Network Driven by Ambient RF Energy Far-Field

Yanping Fan, Dawei Zhang, Yumei Wen, Ningning Wu
5 citations
IEEE Transactions on Instrumentation and Measurement
Energy Harvesting in Wireless Networks
3.65
article

A High-Efficiency Self-Powered Wireless Sensor Network Driven by Ambient RF Energy Far-Field

Yanping Fan, Dawei Zhang, Yumei Wen, Ningning Wu
article en
5 citations

Abstract

Wireless self-powered systems based on RF energy harvesting (RFEH) have emerged as an effective solution to the energy challenges in the Internet of Things devices (IoT). However, two critical challenges still persist: low energy harvesting efficiency at the receiver under low power conditions typical of long-distance scenarios, and the power range of RFEH not being suitable for most low-power IoT applications. To solve these problems, we proposed a high-efficiency RFEH system with wide input power range and high sensitivity. We employed harmonic suppression technology to mitigate higher-order harmonics generated by diodes and used radial stubs instead of capacitors and inductors to reduce insertion losses and parasitic effects. The proposed rectifier achieves a peak power efficiency of 74.4 % at 9.5 dBm. Efficiency remains above 50 % within the input power range of -8 to 15.5 dBm and exceeds 70 % between 2.5 to 11.5 dBm. Even at -14 dBm, a PCE of 30 % is maintained, significantly improving the efficiency of RFEH. Building on this RFEH system, we propose a dual-mode self-powered wireless sensor network system. Experimental results demonstrate that the low-power mode can operate up to 6 m away and have a minimum sensitivity of -10 dBm. The high-power (7 mW) mode can continuously monitor strain information for over 4.5 hours at 1 m. This system provides a solution for the widespread application of IoT in the future.

IEEE Transactions on Instrumentation and MeasurementVol. 74
University of Shanghai for Science and Technology (CN), Shanghai Jiao Tong University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 7%
Energy Harvesting in Wireless Networks
3.65
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A High-Efficiency Self-Powered Wireless Sensor Network Driven by Ambient RF Energy Far-Field — Yanping Fan, Dawei Zhang, et al. · IEEE Transactions on Instrumentation and Measurement (2025) | TGRS Research Map | TGRS