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Record W2079898523 · doi:10.1002/ett.1295

Accurate closed‐form approximations for the performance of equal gain combining diversity systems in Nakagami fading channels

2008· article· en· W2079898523 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 · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFadingNakagami distributionClosed-form expressionDiversity gainMathematicsEnvelope (radar)Expression (computer science)Diversity combiningOutage probabilityComputer scienceAlgorithmTelecommunicationsTopology (electrical circuits)StatisticsMathematical analysisCombinatorics

Abstract

fetched live from OpenAlex

Abstract Accurate closed‐form approximations for the distribution and density of the signal envelope at the output of L ‐branch equal gain combining (EGC) receivers in Nakagami fading channels are derived. These expressions are used to analyse the probability of error of an L ‐branch predetection EGC diversity system operating in different fading conditions. Coherent and noncoherent binary signalling as well as coherent M ‐ary signalling are considered. In addition, a closed‐form expression for the outage probability of these systems is derived. These closed‐form expressions permit rapid evaluation of the performance of EGC diversity systems without resorting to numerical integration as required by previous solutions. Copyright © 2008 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 categoriesScience and technology studies
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 score0.922
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
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.050
GPT teacher head0.253
Teacher spread0.203 · 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