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Record W2597963303 · doi:10.1109/vtcfall.2016.7881084

Measurement and Analysis of Available Ambient Radio Frequency Energy for Wireless Energy Harvesting

2016· article· en· W2597963303 on OpenAlexaffabout
Jonathan C. Kwan, Abraham O. Fapojuwo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEnergy harvestingRadio frequencyTransmitterWirelessEnergy (signal processing)Spectrum analyzerComputer scienceElectrical engineeringEnvironmental scienceTelecommunicationsEngineeringPhysicsChannel (broadcasting)

Abstract

fetched live from OpenAlex

This paper presents the results of ambient RF energy measurements conducted at 23 locations in Calgary and area, including a mix of indoor/outdoor, rural/urban, public/private locations across frequency bands for cell phones (824-960MHz, 1710-2170MHz) and unlicensed industrial, scientific, and medical devices (2.4-2.5GHz, 5.150-5.875GHz) using a spectrum analyzer. A best case test scenario where an active RF source was nearby a user was also conducted. It was found that RF energy at the measurement locations is generally too low or too inconsistent for energy harvesting. Analysis of measurement data reveals that up to 37% and 11% of the locations can attain a peak power of at least -30dBm and -20dBm, respectively. However, ambient RF harvesting is probably feasible with an active source nearby. The findings open the door for further research in intended RF energy harvesting with a dedicated transmitter for simultaneous wireless information and power transfer in future generation sensors powered by ambient RF energy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.195
Teacher spread0.172 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2016
Admission routes2
Has abstractyes

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