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Record W2038307299 · doi:10.1109/bsc.2008.4563237

Information rates of optical impulse modulation over indoor diffuse wireless channels

2008· article· en· W2038307299 on OpenAlexaff
Mohamed D. A. Mohamed, Steve Hranilovic

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsOptical wirelessKeyingComputer scienceOn-off keyingModulation (music)Channel (broadcasting)Phase-shift keyingWirelessElectronic engineeringBit error rateTelecommunicationsPhysicsAcousticsEngineering

Abstract

fetched live from OpenAlex

Optical impulse modulation (OIM) is a recent wireless optical modulation scheme that achieves high data rates by utilizing high-frequency bands to satisfy the channel non-negativity constraint. These bands are attenuated by the lowpass indoor diffuse optical wireless channel, and hence are not detected by the receiver. For a uniform binary input distribution, the information rates are investigated for OIM and compared to those of a conventional rectangular on-off keying (Rect-OOK) scheme. Using a well-known exponential model for the indoor diffuse optical channel, at a normalized delay spread of 0.3 and optical signal-to-noise ratio (SNR) of 3 dBo, the information rate of OIM with a simple lowpass receiver is shown to be 8.6% higher than that of Rect-OOK with a more complex whitened matched filter receiver.

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)0.001
metaresearch head score (Gemma)0.007
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.016
GPT teacher head0.233
Teacher spread0.217 · 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

Citations7
Published2008
Admission routes1
Has abstractyes

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