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Record W1975679266 · doi:10.1093/ietfec/e89-a.11.3148

MAP Detectors for Differential Pulse-Position Modulation over Indoor Optical Wireless Communications

2006· article· en· W1975679266 on OpenAlexaff
Ubolthip Sethakaset, T. Aaron Gulliver

Bibliographic record

VenueIEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences · 2006
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsDetectorIntersymbol interferencePulse-position modulationInterference (communication)Modulation (music)Channel (broadcasting)Optical wirelessDifferential (mechanical device)OpticsPhysicsWirelessPosition (finance)Pulse shapingComputer sciencePulse (music)Electronic engineeringTelecommunicationsPulse-amplitude modulationEngineeringAcousticsLaser

Abstract

fetched live from OpenAlex

In this letter, it is shown that a MAP detector can be employed with differential pulse-position modulation (L-DPPM) in an indoor optical wireless system. The MAP detector error performance is evaluated and compared with that of a hard-decision detector and MLSD over an intersymbol interference channel. It is shown that a MAP detector provides superb performance even in a dispersive channel with high DT.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score0.893

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.254
Teacher spread0.238 · 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.

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

Citations2
Published2006
Admission routes1
Has abstractyes

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