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Record W2171905704 · doi:10.1109/wcnc.2009.4917874

Outage Analysis of Wireless Systems over Composite Fading/Shadowing Channels with Co-Channel Interference

2009· article· en· W2171905704 on OpenAlexaff
Imène Trigui, Amine Laourine, Sofiène Affes, Alex Stéphenne

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsEricsson (Canada)Institut National de la Recherche Scientifique
Fundersnot available
KeywordsFadingInterference (communication)Nakagami distributionCo-channel interferenceChannel (broadcasting)Computer scienceOutage probabilityProbability density functionShadow mappingWirelessFading distributionElectronic engineeringTopology (electrical circuits)TelecommunicationsRayleigh fadingMathematicsStatisticsEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

This paper presents an outage analysis of wireless systems operating in gamma-shadowed Nakagami-faded environments where the desired signal also suffers from co-channel interference. The interfering signals are also subject to fading and shadowing. Based on the obtained signal to interference ratio (SIR) probability density function (pdf), closed- form expressions for the outage probability are obtained in both cases of statistically identical interferers and multiple interferers with different parameters. The effects on the aforementioned performance metric of the reuse distance and of the combined fading, shadowing and co-channel interference are analyzed subsequently. The newly derived closed-form expressions for the outage probability allow as to assess the effects of the different channel and interference parameters easily.

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)0.006
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.288
Teacher spread0.253 · 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

Citations20
Published2009
Admission routes1
Has abstractyes

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Same topicCooperative Communication and Network CodingFrench-language works237,207