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Modeling Crosstalk Coefficients in Orbital Angular Momentum-Multiplexed FSO Channels under Gaussian Pointing Errors

2024· article· en· W4400908926 on OpenAlexaff
Mohammed Elamassie, Maysa Yaseen, Salama Ikki, Murat Uysal

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsLakehead University
Fundersnot available
KeywordsCrosstalkAngular momentumMultiplexingGaussianOrbital angular momentum multiplexingPhysicsComputer scienceElectronic engineeringOpticsOrbital angular momentum of lightTotal angular momentum quantum numberTelecommunicationsEngineeringClassical mechanicsQuantum mechanics

Abstract

fetched live from OpenAlex

Crosstalk coefficients induced by pointing errors pose a significant challenge in orbital angular momentum (OAM)-multiplexed free space optical (FSO) communication systems. This paper presents a detailed investigation into the impact of Gaussian pointing errors on crosstalk coefficients within OAM-multiplexed FSO channels. Unlike previous studies which primarily focused on fixed strength of pointing error, our analysis encompasses a range of pointing error strengths. We propose closed-form expressions for the probability distribution function (PDF) governing the crosstalk coefficient, accommodating varying pointing error strengths. This analytical framework provides valuable insights into the behavior of crosstalk under different environmental conditions, facilitating the design and optimization of robust OAM-based FSO communication systems.

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)0.002
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: none
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.019
GPT teacher head0.259
Teacher spread0.239 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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