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Effect of Correlated Turbulence on Integrated SAG-FSO/SH-FSO/RF Transmission for Satellite Communications

2024· article· en· W4405975433 on OpenAlexaff
Ramy Samy, Hassan Ahmed, Hong-Chuan Yang, Mohamed‐Slim Alouini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsTurbulenceTransmission (telecommunications)SatelliteCommunications satelliteComputer scienceTelecommunicationsElectronic engineeringPhysicsEngineeringAerospace engineeringMeteorology

Abstract

fetched live from OpenAlex

Free-space optics (FSO) is slated as a promising solution to support extremely high data rates for future satellite communications (SatCom). Nonetheless, FSO transmission is susceptible to atmospheric turbulence impacts. Space-air-ground (SAG) FSO and hybrid single-hop (SH) FSO/radio frequency (RF) transmission systems are suggested to enhance the performance and reliability of FSO-based SatCom systems. They can also be integrated to further improve system performance. Previous work analyzed the performance of the resulting integrated SAG-FSO/SH-FSO/RF transmission system, assuming independent turbulence effects. In this paper, we perform a capacity analysis of the system in the presence of correlated turbulence. A novel analytical expression for the end-to-end ergodic capacity is derived and validated by Monte Carlo simulations. The numerical results demonstrate that, although the correlated turbulence adversely affects its performance, the integrated transmission system can still achieve a considerable capacity gain over existing solutions.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.012
GPT teacher head0.275
Teacher spread0.263 · 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 designOther design
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

Citations4
Published2024
Admission routes1
Has abstractyes

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