A Long-Distance RF-Powered Sensor Node with Adaptive Power Management for IoT Applications

• Published in: Sensors (Basel, Switzerland) Vol. 17; no. 8; p. 1732
• Main Authors: Pizzotti, Matteo, Perilli, Luca, Del Prete, Massimo, Fabbri, Davide, Canegallo, Roberto, Dini, Michele, Masotti, Diego, Costanzo, Alessandra, Franchi Scarselli, Eleonora, Romani, Aldo
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 28.07.2017; MDPI
• Subjects: adaptive power management; Adaptive sampling; Co-design; Design; Design optimization; Energy consumption; Energy harvesting; Energy policy; nano-power DC/DC converter; Power management; rectifying antenna; RF power transfer; ultra-low power sensor node; Very high frequencies; Wireless communications; wireless sensor networks; nano-power DC/DC converter; wireless sensor networks; ultra-low power sensor node; adaptive power management; RF power transfer; energy harvesting; rectifying antenna
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s17081732

We present a self-sustained battery-less multi-sensor platform with RF harvesting capability down to -17 dBm and implementing a standard DASH7 wireless communication interface. The node operates at distances up to 17 m from a 2 W UHF carrier. RF power transfer allows operation when common energy scavenging sources (e.g., sun, heat, etc.) are not available, while the DASH7 communication protocol makes it fully compatible with a standard IoT infrastructure. An optimized energy-harvesting module has been designed, including a rectifying antenna (rectenna) and an integrated nano-power DC/DC converter performing maximum-power-point-tracking (MPPT). A nonlinear/electromagnetic co-design procedure is adopted to design the rectenna, which is optimized to operate at ultra-low power levels. An ultra-low power microcontroller controls on-board sensors and wireless protocol, to adapt the power consumption to the available detected power by changing wake-up policies. As a result, adaptive behavior can be observed in the designed platform, to the extent that the transmission data rate is dynamically determined by RF power. Among the novel features of the system, we highlight the use of nano-power energy harvesting, the implementation of specific hardware/software wake-up policies, optimized algorithms for best sampling rate implementation, and adaptive behavior by the node based on the power received.