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Record W3131650466 · doi:10.1109/lwc.2021.3058942

Outage Performance for Optical Feeder Link in Satellite Communications With Diversity Combining

2021· article· en· W3131650466 on OpenAlexaff
Xiaoyu Liu, Min Lin, Huaicong Kong, Jian Ouyang, Julian Cheng

Bibliographic record

VenueIEEE Wireless Communications Letters · 2021
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersShenzhen International Cooperation Research ProjectShanghai Aerospace Science and Technology Innovation FoundationNanjing University of Posts and TelecommunicationsNational Natural Science Foundation of China
KeywordsIndependent and identically distributed random variablesFadingComputer scienceProbability density functionExpression (computer science)Diversity combiningOutage probabilityDiversity gainCommunications satelliteSatelliteMaximal-ratio combiningTelecommunicationsRandom variableMathematicsPhysicsStatisticsDecoding methods

Abstract

fetched live from OpenAlex

This letter investigates the outage performance of an optical feeder link in satellite communications, where the gateway is equipped with multiple apertures and employs diversity combining schemes to mitigate the effect of atmosphere turbulence. In particular, by assuming that the optical link undergoes the Málaga fading, we first derive a closed-form expression for the outage probability (OP) of the considered system with selection combining (SC). Subsequently, when equal gain combining (EGC) is utilized, we present an approximate yet accurate probability density function expression for the sum of independent and identically distributed Málaga random variables. Next, we derive an OP expression for the considered system with EGC. To gain more insights, we further obtain diversity order for both SC and EGC schemes. It is found that the diversity order for both schemes is related to the number of receive apertures and the effective number of large-scale cells of the scattering process.

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)0.003
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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.035
GPT teacher head0.247
Teacher spread0.212 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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