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Record W1505317658 · doi:10.1109/cdc.2001.981021

Stochastic power control for wireless systems: classical and viscosity solutions

2001· article· en· W1505317658 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

VenueProceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228) · 2001
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsHamilton–Jacobi–Bellman equationViscosity solutionStochastic controlDegenerate energy levelsBellman equationPower controlViscosityMathematicsOptimal controlPower (physics)FadingMathematical optimizationControl theory (sociology)Applied mathematicsControl (management)Computer scienceAlgorithmPhysics

Abstract

fetched live from OpenAlex

This paper considers power control for log-normal fading channels. A rate based power set point control model and an associated performance measure are introduced. Within this framework, a stochastic optimal power control law exists and the associated value function satisfies a degenerate HJB equation in a viscosity solution sense. The HJB equation is approximated by a uniformly parabolic second order equation which has a classical solution and a suboptimal control is derived. The suboptimal control is more realistic for practical implementation.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
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 head0.039
GPT teacher head0.282
Teacher spread0.243 · 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