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Record W2099054420

Switching rates of dual selection diversity in κ-μ and α-μ fading channels

2009· article· en· W2099054420 on OpenAlexaff
Xin Wang, Norman C. Beaulieu

Bibliographic record

VenueWireless Communications and Networking Conference · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFadingRician fadingFading distributionNakagami distributionRayleigh fadingDiversity combiningIndependent and identically distributed random variablesDiversity schemeComputer scienceDual (grammatical number)Topology (electrical circuits)Electronic engineeringTelecommunicationsMathematicsStatisticsChannel (broadcasting)EngineeringRandom variable
DOInot available

Abstract

fetched live from OpenAlex

Switching rate is an important parameter in selection diversity receiver design because the switching transients increase the system outage. An exact closed-form solution for the switching rate of dual selection diversity in κ-µ and α-µ distributed fadings is derived. Independent and identically distributed (i.i.d.) κ-µ and α-µ fading channels are considered. The switching rate for dual i.i.d. κ-µ distributed fading includes the switching rate for dual i.i.d. Rayleigh, Rician and Nakagami-m fading channels as special cases. Similarly, the switching rate for dual α-µ fading channels also includes special cases such as Rayleigh, Nakagami-m and Weibull fading channels.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.052
GPT teacher head0.287
Teacher spread0.236 · 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.

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

Citations0
Published2009
Admission routes1
Has abstractyes

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