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Record W2124623546 · doi:10.1109/icc.2011.5963050

Adaptive Localized Resource Allocation with Access Point Coordination in Cellular Networks

2011· article· en· W2124623546 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 Toronto
Fundersnot available
KeywordsComputer scienceTelecommunications linkResource allocationComputer networkChannel allocation schemesSpectral efficiencyResource management (computing)Transmission (telecommunications)Cellular networkChannel (broadcasting)Enhanced Data Rates for GSM EvolutionScheme (mathematics)Orthogonal frequency-division multiplexingDistributed computingWirelessTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

This paper proposes an adaptive fractional frequency reuse (FFR) resource allocation scheme for downlink transmission of OFDMA cellular networks. Resource allocation is localized in the sense that in each region system resources are assigned based on local traffic demand. Furthermore, the allocated resources in each region adapt to changes in the environment (i.e. channel gains and number/mobility of active terminals). To this end, a multi-stage proportional fair scheduler is introduced. The performance of the proposed scheme is compared with a variation of the well-known FFR technique. Numerical results studying the average and cell edge spectral efficiencies show promising improvements.

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: Methods · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.552

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 head0.015
GPT teacher head0.200
Teacher spread0.184 · 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

Citations9
Published2011
Admission routes1
Has abstractyes

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