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Record W2132238728 · doi:10.1109/vetecs.2011.5956657

EDFA-Based All-Optical Relaying in Free-Space Optical Systems

2011· article· en· W2132238728 on OpenAlexaff
Ehsan Bayaki, Diomidis S. Michalopoulos, Robert Schober

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOptical amplifierComputer scienceAttenuationElectronic engineeringOptical wirelessFadingFree-space optical communicationBackhaul (telecommunications)WirelessOptical communicationOptical performance monitoringFree spaceScintillationWavelength-division multiplexingChannel (broadcasting)TelecommunicationsPhysicsEngineeringOpticsLaser

Abstract

fetched live from OpenAlex

Free-space optical (FSO) communications has recently received considerable attention for last-mile terrestrial applications and wireless backhaul in mobile communication systems. The performance of these systems is mainly impaired by weather-dependent attenuation and the intensity variations of the channel known as scintillation. The distance-dependence of both attenuation and scintillation motivates the use of relays as a means of improving system performance and extending the communication link. In this paper, we propose an exact and practical model for all-optical relays employing erbium-doped fiber amplifiers (EDFAs), which avoid the optical-to-electrical and electrical-to-optical conversions required in conventional FSO relays employing electrical amplification. The proposed model is shown to be more accurate than existing simplified models and an outage probability analysis for all-optical EDFA-based relaying in the presence of lognormal fading is presented. Our results show that FSO systems with simple all-optical relays achieve a better performance compared to systems with relays employing electrical amplification.

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)0.001
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.041
GPT teacher head0.223
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

Citations14
Published2011
Admission routes1
Has abstractyes

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