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Record W2171031786 · doi:10.1109/icc.2008.272

A Quadrature Markov Chain Model of the Rayleigh Fading Channel

2008· article· en· W2171031786 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFadingRayleigh fadingFading distributionMarkov chainChannel state informationMarkov modelMarkov processComputer scienceRayleigh scatteringStatistical physicsMathematicsChannel (broadcasting)Electronic engineeringStatisticsTelecommunicationsPhysicsEngineeringWirelessOptics

Abstract

fetched live from OpenAlex

A quadrature Markov chain model of the Rayleigh fading channel is examined. The model is defined by formulating a Markov chain model of the underlying Gaussian fading process, using a state-space that consists of both the amplitude and rate-of-change of the Gaussian fading, then transforming that model into a Markov chain model of the Rayleigh fading process. Power margin quality measures are used to determine the most suitable number of states for the model. It is shown that the proposed model is an improvement over previous amplitude-based models, and that, in some instances, it is also an improvement over previous amplitude/rate models.

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 categoriesnone
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 score0.935
Threshold uncertainty score0.288

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 head0.011
GPT teacher head0.179
Teacher spread0.168 · 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

Quick stats

Citations6
Published2008
Admission routes1
Has abstractyes

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