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Record W2015740533 · doi:10.1364/oe.18.013915

Exact error rate analysis of equal gain and selection diversity for coherent free-space optical systems on strong turbulence channels

2010· article· en· W2015740533 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOptics Express · 2010
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia, Okanagan CampusKelowna General Hospital
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCoding gainKeyingBit error ratePhase-shift keyingDiversity gainFree-space optical communicationDiversity schemeBinary numberPhysicsComputer scienceTelecommunicationsSelection (genetic algorithm)Optical communicationStatistical physicsMathematicsOpticsStatisticsFadingDecoding methodsArithmetic

Abstract

fetched live from OpenAlex

Exact error rate performances are studied for coherent free-space optical communication systems under strong turbulence with diversity reception. Equal gain and selection diversity are considered as practical schemes to mitigate turbulence. The exact bit-error rate for binary phase-shift keying and outage probability are developed for equal gain diversity. Analytical expressions are obtained for the bit-error rate of differential phase-shift keying and asynchronous frequency-shift keying, as well as for outage probability using selection diversity. Furthermore, we provide the closed-form expressions of diversity order and coding gain with both diversity receptions. The analytical results are verified by computer simulations and are suitable for rapid error rates calculation.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.596

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 science0.0000.000
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 head0.027
GPT teacher head0.257
Teacher spread0.230 · 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