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Record W2587171280 · doi:10.1109/glocomw.2016.7848882

Dual-Hop VLC/RF Transmission System with Energy Harvesting Relay under Delay Constraint

2016· article· en· W2587171280 on OpenAlexaff
Tamer Rakia, Hong‐Chuan Yang, Fayez Gebali, Mohamed‐Slim Alouini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsVisible light communicationRetransmissionRelayComputer scienceNetwork packetRadio frequencyPacket lossData transmissionPath lossTransmission (telecommunications)WirelessComputer networkTransmission delayElectronic engineeringElectrical engineeringTelecommunicationsPower (physics)EngineeringPhysicsLight-emitting diode

Abstract

fetched live from OpenAlex

In this paper, we introduce a dual-hop visible light communication (VLC) / radio frequency (RF) transmission system to extend the coverage of indoor VLC systems. The relay between the two hops is able to harvest light energy from different artificial light sources and sunlight entering the room. The relay receives data packet over a VLC channel and uses the harvested energy to retransmit it to a mobile terminal over an RF channel. We develop a novel statistical model for the harvested electrical power and analyze the probability of data packet loss. We define a system design parameter (α ∈ [0, 1)) that controls the time dedicated for excess energy harvesting and data packet retransmission. It was found that the parameter has an optimal value which minimizes the packet loss probability. Further more, this optimal value is independent of the RF channel path loss. However, optimal showed inverse dependence on the packet size.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.179
Teacher spread0.171 · 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 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

Citations38
Published2016
Admission routes1
Has abstractyes

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