MétaCan
Menu
Back to cohort
Record W2898784777 · doi:10.1049/iet-com.2018.5664

WDM for multi‐user indoor VLC systems with SCM

2019· preprint· en· W2898784777 on OpenAlexfundno aff
Safwan Hafeedh Younus, Aubida A. Al‐Hameed, Ahmed Taha Hussein, Mohammed T. Alresheedi, Jaafar M. H. Elmirghani

Bibliographic record

VenueIET Communications · 2019
Typepreprint
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsnot available
FundersInstitute of Population and Public HealthEngineering and Physical Sciences Research CouncilKing Saud University
KeywordsVisible light communicationSubcarrierComputer scienceWavelength-division multiplexingMultiplexingInterference (communication)Channel (broadcasting)Electronic engineeringReal-time computingComputer hardwareOrthogonal frequency-division multiplexingTelecommunicationsWavelengthOpticsEngineeringPhysicsLight-emitting diode

Abstract

fetched live from OpenAlex

A system that employs wavelength division multiplexing (WDM) in conjunction with sub‐carrier multiplexing (SCM) tones is proposed to realise high data rate multi‐user indoor visible light communication (VLC). The SCM tones, which are unmodulated signals, are used to identify each light unit, to find the optimum light unit for each user and to calculate the level of the co‐channel interference (CCI). WDM is utilised to attain a high data rate for each user. In this study, multi‐colour (four colours) laser diodes are utilised as sources of lighting and data communication. One of the WDM colours is used to convey the SCM tones at the beginning of the connection to set up the connection among receivers and light units (to find the optimum light unit for each user). To evaluate the performance of the VLC system, two types of receivers are proposed: an array of non‐imaging receivers and an array of non‐imaging angle diversity receivers. In this study, the effects of diffuse reflections, CCI and mobility on the system performance are considered.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.795
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0050.003
Research integrity0.0010.002
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 head0.070
GPT teacher head0.301
Teacher spread0.231 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueIET CommunicationsSame topicOptical Wireless Communication TechnologiesFrench-language works237,207