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Record W2167801251 · doi:10.1109/ccece.2008.4564763

Blind detection of on-off keying for free-space optical communications

2008· article· en· W2167801251 on OpenAlexaffvenue
M.L.B. Riediger, Robert Schober, Lutz Lampe

Bibliographic record

VenueConference proceedings - Canadian Conference on Electrical and Computer Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsKeyingDetectorOn-off keyingChannel (broadcasting)Detection theoryComputer scienceFree-space optical communicationChannel state informationWindow (computing)Amplitude-shift keyingOptical communicationElectronic engineeringTelecommunicationsBit error rateOpticsPhysicsPhase-shift keyingEngineeringWireless

Abstract

fetched live from OpenAlex

We investigate blind detection, i.e. detection assuming the absence of instantaneous channel state information (CSI) and a statistical channel description at the receiver, of on-off keying (OOK) in a free-space optical (FSO) system. Using an observation window encompassing many consecutive independent bits, our blind detector capitalizes on the fact that the atmospheric turbulence is constant over the observation window and that the expected number of transmitted 1s and 0 s are equal. To improve receiver performance beyond that of the initial blind detector, we also consider the use of decision-aided threshold estimation and a second detection stage, respectively. Provided that a sufficiently large observation window is employed, simulation results indicate that the proposed receiver can attain performance comparable to that of the lower performance bound given by detection with CSI.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.216
Teacher spread0.182 · 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 designBench or experimental
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

Citations45
Published2008
Admission routes2
Has abstractyes

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