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Outage Probability Analysis for Multi-User Single-Relay OFDMA DF Networks in Frequency Selective Rayleigh Fading Channels

2014· article· en· W2012683364 on OpenAlexaff
Hamidreza Boostanimehr, Vijay K. Bhargava

Bibliographic record

VenueIEEE Communications Letters · 2014
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRayleigh fadingFadingComputer scienceRelayFading distributionOrthogonal frequency-division multiple accessProbability density functionChannel (broadcasting)Cumulative distribution functionRelay channelOrthogonal frequency-division multiplexingComputer networkTopology (electrical circuits)AlgorithmTelecommunicationsMathematicsStatisticsPhysics

Abstract

fetched live from OpenAlex

In this letter, we study a multi-user single-relay decode-and-forward orthogonal frequency division multiple access system, where the channel model is Rayleigh frequency selective fading. We provide analytical approximations for the global outage probability in the sense that the outage event occurs when at least one link goes into outage. The main contribution of this letter is the consideration of the statistical correlation between the link capacities which is created by the relay-destination channel that is common to all the links. The analysis is carried out by fitting the multi-variate normal distribution to the joint probability distribution function of the link capacities.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.785
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0040.001
Research integrity0.0000.001
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 head0.088
GPT teacher head0.305
Teacher spread0.217 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations6
Published2014
Admission routes1
Has abstractyes

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