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Record W2078668522 · doi:10.1109/ccece.2006.277544

A Real-Time Radio Resource Allocation Scheme in OFDMA System

2006· article· en· W2078668522 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 institutionsLakehead University
Fundersnot available
KeywordsOrthogonal frequency-division multiple accessComputer scienceResource allocationGreedy algorithmOrthogonal frequency-division multiplexingMathematical optimizationFrequency-division multiple accessComputational complexity theoryTransmission (telecommunications)Scheme (mathematics)Resource management (computing)Optimization problemAlgorithmDistributed computingMathematicsComputer networkTelecommunications

Abstract

fetched live from OpenAlex

Radio resource allocation (RRA) problem for orthogonal frequency division multiple access (OFDMA) system is considered in this paper. Based on the greedy approach, an efficient real-time suboptimal RRA algorithm, which is referred to as the fast bits-feeding algorithm in this paper, is proposed to solve both classes of RRA problems. It solves RRA optimization problems by satisfying the constraints one by one without any assumptions of bit-loading or transmission power distribution. Compared with other suboptimal methods, the performance of the proposed suboptimal algorithm is closer to that of the optimal one with even lower computational complexity, which makes it outperform other suboptimal methods

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 score0.573
Threshold uncertainty score0.444

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 head0.003
GPT teacher head0.172
Teacher spread0.169 · 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

Citations4
Published2006
Admission routes1
Has abstractyes

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