Design of a compact RF energy harvester for wireless sensor networks

Ajmal, Tahmina; Jazani, David; Allen, Ben

doi:10.1049/cp.2012.0600

Cited by 18 publications

(11 citation statements)

References 9 publications

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“…A thorough assessment of the power density in a variety of scenarios and distances was performed in [6], but was limited to (global system for mobile communications) GSM900/1800 and WiFi bands. Other work has focused on the medium wave range (909 kHz) to benefit from the large transmit powers and low path loss at those frequencies [7,8] or extremely large transmit powers up to 1 MW over a short distance (a few kilometres) to scavenge tens of microwatts (μW) [9].…”

Section: Introductionmentioning

confidence: 99%

Ambient RF energy harvesting trial in domestic settings

Mimis

Gibbins

Dumanlı

et al. 2015

IET Microwaves, Antennas & Propagation

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This study investigates the feasibility of ambient radio frequency (RF) energy harvesting for powering low-power electronic devices, in domestic environments. An RF spectrum survey was carried out in a variety of locations around the city of Bristol, UK between 500 MHz and 6 GHz. Locations are limited to indoor residential environments, and as a comparison an office. The measurement setup consists of an omnidirectional, broadband, discone antenna and a handheld spectrum analyser. On the basis of the measured power consumption of a number of low-power electronic devices and the analysed results, the required harvesting time to power each device is calculated. The results show that in order to harvest enough energy to power-up a small calculator (2 μW) for 1 s, an antenna array covering 1.7-2.5 GHz with effective area of 1 m 2 requires on average about 10 min of harvesting.

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Section: Introductionmentioning

confidence: 99%

Ambient RF energy harvesting trial in domestic settings

Mimis

Gibbins

Dumanlı

et al. 2015

IET Microwaves, Antennas & Propagation

View full text Add to dashboard Cite

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“…In situations where the energy harvesting equipment designer does not have explicit knowledge of where exactly the device will be deployed, the expression (5) can yield insight into the expected power available for harvesting for a certain environment. Figure 2 shows the mean power available for harvesting from ‰ D 3 different RATs using (5). Given the limited growth in both TV and cellular antenna infrastructure growth, and the tremendous growth in Wi-Fi networks, the Wi-Fi hotspot density and number of Wi-Fi bands are varied in Figure 2.…”

Section: Formulationmentioning

confidence: 99%

“…However, direct sunlight is not always readily available. RF harvesting solutions have been proposed as an alternative [5][6][7]. By amalgamating multiple radio signals, RF energy harvesting has the greatest potential in urban areas, where there is an abundance of wireless communication devices from multiple Radio Access Technologies (RATs).…”

Section: Introductionmentioning

confidence: 99%

“…Existing performance tests have focused on specific model scenarios, single dominant link scenario (i.e. nearby TV station) [5], or field tests in a particular area. This paper employs stochastic geometry [8] to derive the mean and probability distribution of the received RF radiation energy available for harvesting from multiple heterogeneous networks.…”

Section: Introductionmentioning

confidence: 99%

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Radio‐frequency energy harvesting potential: a stochastic analysis

Guo

Siyi

2013

Trans. Emerging Tel. Tech.

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This paper considers the energy harvesting potential from ambient electromagnetic waves in the radio frequency (RF) communications spectrum. Because of chaotic positioning nature of cells, handsets and hotspots, the analysis employs stochastic geometry theory to derive the mean and probability distribution of the received RF radiation energy available for harvesting. The mean and density function of energy harvested, as a function of transmitter deployment density, spectrum and pathloss characteristics are given. The novel benefit is that the derived expressions serve as a design guideline for RF harvesting solutions. For a given power harvesting and reliability requirement, the expressions in this paper can yield insight into which set and how many RF spectrum bands to harvest. Copyright © 2013 John Wiley & Sons, Ltd.

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“…The novelty of this work has focussed to power the wireless sensor nodes at a distance of 120 km from the 150‐kW transmitter. Here, a compact ferrite rod antenna is used for harvesting RF signals in Ajmal et al The author surveyed outdoor RF power density level in urban area at Southern China. The measurements are taken for the frequency range of 0.7 to 3GHz, which covers the mobile band and Wi‐Fi band.…”

Section: Introductionmentioning

confidence: 99%

Statistical analysis on ambient RF energy harvesting for low‐power wireless applications

Inbaraj¹,

Kailasam²,

Sankararajan³

2018

Int J Communication

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Renewable energy sources from the earth constitute another option apart from the available ones for wellspring of energy for economizing on cost of power supply. The energy obtained from ambient sources is called energy harvesting. Energy-harvesting low-power systems have acquired a remarkable consideration as a viable hotspot for expanding both energy efficiency and spectral efficiency. Radio frequency (RF) energy harvesting from ambient source is a promising technique for fulfilling the irreplaceable power prerequisites for powering the low-power devices. Hence, it requires the development of an antenna for harvesting RF energy. In this paper, a coplanar waveguide (CPW) antenna has been designed and fabricated using FR4 lossy substrate. This CPW antenna covers frequency bands from the most important RF patrons (GSM 900, GSM 1800, 3G, and Wi-Fi) within the frequency range from (0.58 to 3 GHz) with a percentage fractional bandwidth of 116% with the center frequency of 1.65 GHz. The fabricated antenna then has been experimentally validated at SSN College of Engineering campus. The effects on the RF power density level for CPW antenna are examined by statistical approach known as Taguchi method. The L9 and L8 orthogonal arrays and analysis of variance are implemented to analyze the execution qualities. The CPW antenna control factors are distance, time, and number of receivers. Then, statistical test (P) are used to determine the significant factors on RF power density. KEYWORDSANOVA, CPW antenna, RF energy harvesting, spectral survey, Taguchi orthogonal array | INTRODUCTIONThe enormous growth in communication networks has triggered persistent expansion of the need for energy supply, leading to a battery exhaustion issue for wireless communication devices. 1 Research work has been conducted recently to increase energy from ambient sources, which is an alternate option for maintaining a sustainable energy supply instead of rechargeable or replaceable batteries. 2 Energy harvesting has been proposed for accomplishing this and ensuring unlimited energy supply to electronic systems and saving energy consumption. 3,4 Hence, energy harvesting grasps energy from the ambient environment and stores them for future use. There are different types of energy harvesting such as thermal, solar, and radio frequency (RF). Energy harvesting from electromagnetic (EM) radiation has huge consideration because of wireless communications networks. 5 Electromagnetic radiations from the far-field applications have emerged in the form of radio frequency and can be collected by aerial, which converts the radio waves into electric power using rectifier circuits. 6 This paper envisages the usage of harvesting arising from the availability of frequency bands such as Wi-Fi routers, cell phones, and laptops. Cognitive radio can be powered from RF ambient sources, which improve the spectrum efficiency and energy efficiency. 6 Use of the RF signal and the distance between an RF energy source can help harvesting RF energy. First, the purpose of the ...

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Design of a compact RF energy harvester for wireless sensor networks

Cited by 18 publications

References 9 publications

Ambient RF energy harvesting trial in domestic settings

Ambient RF energy harvesting trial in domestic settings

Radio‐frequency energy harvesting potential: a stochastic analysis

Statistical analysis on ambient RF energy harvesting for low‐power wireless applications

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