MétaCan
Menu
Back to cohort

Design and Implementation of Rolling Shutter MIMO-OFDM scheme for Optical Camera Communication System

2021· article· en· W4200319630 on OpenAlexfundno aff
Huy Nguyen, Yeong Min Jang

Bibliographic record

Venue2021 International Conference on Information and Communication Technology Convergence (ICTC) · 2021
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsnot available
FundersInformation Technology Research CentreMinistry of Science and ICT, South Korea
KeywordsOrthogonal frequency-division multiplexingVisible light communicationRolling shutterComputer scienceElectronic engineeringModulation (music)Optical wirelessBroadbandMIMO-OFDMMIMOMultiplexingOptical wireless communicationsWirelessInterference (communication)Optical communicationTelecommunicationsShutterEngineeringElectrical engineeringOpticsPhysicsChannel (broadcasting)Light-emitting diode

Abstract

fetched live from OpenAlex

Orthogonal Frequency-Division Multiplexing (OFDM) is known as the digital multi-carrier modulation technology, which has a lot of advantages compared with single-carrier modulation. OFDM is deployed for broadband wireless communication and broadband wired communication to debate with Inter-Symbol Interference. Currently, the Visible Light band was researched in place of RF band, which shown some applicants: Visible Light Communication (VLC), Optical Camera Communication (OCC), and Light Fidelity (LiFi). The OFDM for LiFi system is known with a lot of schemes (ACO-OFDM, DCO-OFDM. …), however, applying OFDM waveforms for Optical Camera Communication is not known much due to difficulty to deploy. MIMO techniques are known as the techniques to increase the data rate for OCC system. The Rolling Shutter MIMO OFDM technique based on the rolling shutter phenomenon will be presented in this study.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.014

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.024
GPT teacher head0.277
Teacher spread0.253 · 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
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

Citations12
Published2021
Admission routes1
Has abstractyes

Explore more

Same venue2021 International Conference on Information and Communication Technology Convergence (ICTC)Same topicOptical Wireless Communication TechnologiesFrench-language works237,207