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Record W4399110536 · doi:10.1109/jphot.2024.3406156

Nested PPM for Visible Light Communication With Heterogeneous Optical Receivers

2024· article· en· W4399110536 on OpenAlex
Jan Mietzner, Lutz Lampe

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE photonics journal · 2024
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVisible light communicationComputer scienceBit error rateTransmitterPulse-position modulationElectronic engineeringInterference (communication)Optical communicationSIGNAL (programming language)Optical wirelessLight-emitting diodeTelecommunicationsPulse-amplitude modulationCommunications systemElectrical engineeringDecoding methodsDetectorPulse (music)Engineering

Abstract

fetched live from OpenAlex

We consider visible light communication (VLC) using phosphorescent white light-emitting diodes (LEDs) and two different receiver types – a simple receiver for moderate data rate requirements and a sophisticated receiver for higher data rate requirements equipped with an optical blue filter. We address the question, whether it is viable to support both heterogeneous receiver types simultaneously, using a single LED-based transmitter, and characterize the trade-offs associated with a common waveform. In particular, with regard to a simplistic transmitter and receiver structure, we propose a “nested” pulse-position modulation (nPPM) scheme and show that it improves upon conventional time sharing, when the bit rate of the simple receiver is supposed to be retained, while realizing a higher bit rate for the sophisticated receiver. An analysis of the available signal-to-noise ratio at the receiver for a practical setting combined with analytical and simulated error performance results corroborates the feasibility of our approach. Furthermore, we devise an end-to-end signal model, which includes the electrical properties of the LED as well as interference effects associated with optical filtering, and assess the influence on the resulting error performance. Due to its simplicity, our nPPM scheme may be particularly relevant for future mass-market VLC deployments as well as for proprietary solutions.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.242
Teacher spread0.229 · 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