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Record W4394914811 · doi:10.21203/rs.3.rs-4261890/v1

Implementation of a Full-Duplex Visible Light Communication System

2024· preprint· en· W4394914811 on OpenAlexaff
Sorel Bagio Nono Fotso, Jimmi Hervé Talla Mbé, Alain R. Ndjiongue, Armand Nzeukou

Bibliographic record

VenueResearch Square · 2024
Typepreprint
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsDuplex (building)Visible light communicationComputer scienceTelecommunicationsOptoelectronicsPhysicsChemistryLight-emitting diode

Abstract

fetched live from OpenAlex

Abstract In telecommunication research, most outputs are based on simulation and/or analysis. Practical implementations are scarce. This is the case with visible light communication systems. With the knowledge that there is a gap between theoretical and practical implementation, we propose in this paper a two-way light communication system that provides efficient transmitting and receiving of files between two nodes. First, we develop hardware consisting of an emitting antenna, a receiving antenna, and a microcontroller. In order to ensure file transmission, we also develop software using the MATLAB programming language. Experimental results indicate that the bit error rate (BER) of the system increases with the transmission range, the data rate, and the angle of incidence. Accordingly, the recovered files match the transmitted files without any error correction scheme. An appropriate choice of system parameters can allow the BER to reach zero. An effective data rate of 1 Mbps is obtained with a BER of $6\times10^{-6}$. In addition, when data communication is not taking place, the designed modems provide illumination to the environment to meet the other requirements of visible light communication. Finally, the designed light-communication system proves cost-effective and easy to implement.

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: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.050
GPT teacher head0.397
Teacher spread0.347 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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