A 90-nm CMOS 5-Mbps Crystal-Less RF-Powered Transceiver for Wireless Sensor Network Nodes

Papotto, Giuseppe; Carrara, F.; Finocchiaro, Alessandro; Palmisano, G.

doi:10.1109/jssc.2013.2285371

Cited by 108 publications

(36 citation statements)

References 15 publications

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“…An RF-powered transmitter that supports 915 MHz downlink and 2.45 GHz uplink bands is designed in [18]. In [19], the paper computes the minimal number of sinks required to keep the network connected and to satisfy the required constraints.…”

Section: Related Workmentioning

confidence: 99%

Power Control for Passive QAM Multisensor Backscatter Communication Systems

Yan

et al. 2017

Journal of Sensors

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To achieve good quality of service level such as throughput, power control is of great importance to passive quadrature amplitude modulation (QAM) multisensor backscatter communication systems. First, we established the RF energy harvesting model and gave the energy condition. In order to minimize the interference of subcarriers and increase the spectral efficiency, then, the colocated passive QAM backscatter communication signal model is presented and the nonlinear optimization problems of power control are solved for passive QAM backscatter communication systems. Solutions include maximum and minimum access interval, the maximum and minimum duty cycle, and the minimal RF-harvested energy under the energy condition for node operating. Using the solutions above, the maximum throughput of passive QAM backscatter communication systems is analyzed and numerical calculation is made finally. Numerical calculation shows that the maximal throughput decreases with the consumed power and the number of sensors, and the maximum throughput is decreased quickly with the increase of the number of sensors. Especially, for a given consumed power of sensor, it can be seen that the throughput decreases with the duty cycle and the number of sensors has little effect on the throughput.

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Section: Related Workmentioning

confidence: 99%

Power Control for Passive QAM Multisensor Backscatter Communication Systems

Yan

et al. 2017

Journal of Sensors

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“…In Appendix, we detail the proposed approach to establish the boundary conditions, solve a corresponding system of differential equations minding the specific operation of our system, and finally obtain the stationary probability distribution π(x) (27) and the probability mass functions c(0), c(B) (26).…”

Section: Proposition 4 We Assume Here That the Spatial Distribution mentioning

confidence: 99%

“…By means of the above calculations, we establish the stationary distribution π(x) from (27) and the mass probability functions c(0), c(B) in (26), such that all the stationary parameters in our system may finally be derived.…”

Section: Boundary Conditions Transformmentioning

confidence: 99%

“…Several real-life RF-powered applications for different practical scenarios have recently been implemented and described in [24][25][26]. Particularly, in [24], the authors describe a biomedical sensor/actuator implanted in human body which is remotely powered by a sink located on the body surface.…”

Section: Introductionmentioning

confidence: 99%

“…The authors claim that their scavenger could operate having the input radio signal as weak as −39 dBm. Finally, in [26], the authors present a battery-less WSN transceiver featuring simultaneous energy and information transfer, where the transceiver receives energy and data requests in 915 MHz downlink channel and replies in 2.45 GHz uplink channel.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Smart home gateway system over Bluetooth low energy with wireless energy transfer capability

Galinina

Mikhaylov²,

Andreev

et al. 2015

J Wireless Com Network

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As billions of sensors and smart meters connect to the Internet of Things (IoT), current wireless technologies are taking decisive steps to ensure their sustainable operation. One popular IoT scenario features a smart home service gateway, which becomes the central point of user's home environment facilitating a multitude of tasks. Given that most IoT devices connected to residential gateway are small-scale and battery-powered, the key challenge is to extend their lifetime without recharging/replacing batteries. To this end, a novel radio technology named Bluetooth low energy (BLE) has recently been completed to enable energy-efficient data transfer. Another inspiring innovation is the capability of sensors to harvest wireless energy in their local environment. In this work, we envision a scenario where many in-home sensors are communicating with a smart gateway over the BLE protocol, while at the same time harvesting RF energy transmitted from the gateway wirelessly via a dedicated radio interface. We thoroughly investigate performance limitations of such wireless energy transfer interface (WETI) with dynamic analytical model and with important practical considerations. Our methodology delivers the upper bound on WETI operation coupled with BLE-based communication, which characterizes ultimate system performance over the class of practical radio and energy resource management algorithms.

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