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Two Useful Bounds Related to Weighted Sums of Rayleigh Random Variables with Applications to Interference Systems

2012· article· en· W2138057312 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.

Bibliographic record

VenueIEEE Transactions on Communications · 2012
Typearticle
Languageen
FieldEngineering
TopicWireless Communication Security Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCumulative distribution functionMathematicsRayleigh distributionRandom variableRayleigh scatteringUpper and lower boundsContext (archaeology)Function (biology)Constant (computer programming)Probability density functionApplied mathematicsCombinatoricsDiscrete mathematicsStatisticsMathematical analysisComputer sciencePhysics

Abstract

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Weighted sums of Rayleigh random variables occur in diverse problems in wireless, and particularly in interference systems. Previous work has reported upper bounds on the cumulative distribution function of weighted Rayleigh sums. New lower bounds to the cumulative distribution function of weighted Rayleigh sums are derived. The new lower bounds to the cumulative distribution function are used as an intermediate result in deriving a new upper bound on the ratio of a Rayleigh random variable to a weighted sum of Rayleigh random variables shifted by a nonnegative constant. Special cases of this ratio occur in the context of cognitive radio systems and synchronization components. Novel approximations, that are tighter than any known bounds, to the cumulative distribution function of weighted Rayleigh sums are also presented.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.024
GPT teacher head0.275
Teacher spread0.251 · 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