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Record W2118711662 · doi:10.1109/rws.2008.4463619

Optimal power allocation for multiple beam satellite systems

2008· article· en· W2118711662 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
TopicSatellite Communication Systems
Canadian institutionsCommunications Research Centre CanadaCanadian Space AgencyEion (Canada)
Fundersnot available
KeywordsComputer scienceLagrange multiplierPower (physics)Mathematical optimizationCommunications satelliteBandwidth (computing)Constraint (computer-aided design)SatelliteThroughputPower budgetHeuristicResource allocationReal-time computingElectric power systemEngineeringTelecommunicationsComputer networkAerospace engineeringMathematicsWirelessArtificial intelligence

Abstract

fetched live from OpenAlex

Presently, multiple spot-beam satellites are being launched with the ability to allocate power dynamically and to increase throughput, because on-board resources (e.g., power, bandwidth) are scarce and expensive. It is critical to share them efficiently among as many users as possible. In this paper, we propose an innovative power allocation algorithm for the system. We use heuristic method to search the Lagrange multiplier and obtain the optimal power allocation for each spot beam in order to meet the total power constraint and individual SLA constraint together. Scilab simulation demonstrates that our algorithm maximizes the power utilization of the satellite successfully.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score0.530

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 head0.036
GPT teacher head0.235
Teacher spread0.199 · 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

Citations40
Published2008
Admission routes1
Has abstractyes

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