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Record W4387938008 · doi:10.1017/s1759078723001162

Efficient rectifier circuit operating at N78 and N79 sub-6 GHz 5G bands for microwave energy-harvesting and power transfer applications

2023· article· en· W4387938008 on OpenAlexaff
Md. Ahsan Halimi, Taimoor Khan, Ahmed A. Kishk, Yahia M. M. Antar

Bibliographic record

VenueInternational Journal of Microwave and Wireless Technologies · 2023
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsRoyal Military College of CanadaConcordia University
Fundersnot available
KeywordsRectifier (neural networks)MicrowavePrecision rectifierWireless power transferMulti-band deviceImpedance matchingOptoelectronicsEnergy conversion efficiencyMaterials scienceMicrowave transmissionBottleneckElectrical engineeringElectronic engineeringElectrical impedanceComputer scienceVoltageTelecommunicationsEngineeringWirelessAntenna (radio)Power factor

Abstract

fetched live from OpenAlex

Abstract The microwave energy-harvesting (MEH) and microwave power transfer (MPT) technologies have become the most emerging areas of research nowadays. The microwave rectifier circuit is the bottleneck of both the MEH and MPT systems. The efficiency of the system depends on the power conversion efficiency (PCE) of the rectifier. Due to the recent advancement of the fifth-generation communication system, it is desirable to propose an efficient rectifier operating at sub-6 GHz 5G bands. A dual-band rectifier circuit is designed and demonstrated for MEH/MPT purposes, specifically at sub-6 GHz 5G frequency bands. The dual-band matching is achieved by using a stepped impedance transmission line. The rectifier covers N78 (3.3–3.6 GHz) and N79 (4.8–5.0 GHz) bands. Peak PCE of 67.6% @ 3.5 GHz and 56.8% @ 4.9 GHz are achieved. For validation purpose, the rectifier is fabricated and characterized and measured results show good agreement with simulated results.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.012
GPT teacher head0.219
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations12
Published2023
Admission routes1
Has abstractyes

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