MétaCan
Menu
Back to cohort
Record W1994721667 · doi:10.1002/ett.1411

Performance analysis of best‐path selection scheme for multi‐hop amplify‐and‐forward relaying

2010· article· en· W1994721667 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEuropean Transactions on Telecommunications · 2010
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsMemorial University of Newfoundland
FundersMemorial University of Newfoundland
KeywordsCumulative distribution functionRayleigh fadingProbability density functionOutage probabilityPath lossFadingChannel (broadcasting)Moment-generating functionExpression (computer science)Channel capacityProbability of errorMathematicsComputer scienceSelection (genetic algorithm)StatisticsTopology (electrical circuits)Hop (telecommunications)Closed-form expressionAlgorithmTelecommunicationsWirelessCombinatoricsMathematical analysis

Abstract

fetched live from OpenAlex

Abstract This letter derives closed‐form expressions for the error probability, capacity outage and channel capacity for the best‐path selection amplify‐and‐forward technique over non‐identical Rayleigh fading channels. In particular, this letter derives closed‐form expressions for the cumulative distribution function (CDF) and the probability density function (PDF) of the output signal‐to‐noise (SNR) at the destination. We use these statistics to obtain the expressions of the error probability, capacity outage and channel capacity. Furthermore, closed‐form expressions for some of the statistics of the output SNR such as the SNR moments and the amount of fading have been determined. Simulation results are used to verify the analytical results. Copyright © 2010 John Wiley & Sons, Ltd.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.952
Threshold uncertainty score0.797

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.052
GPT teacher head0.300
Teacher spread0.249 · 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