MétaCan
Menu
Back to cohort
Record W2032906529 · doi:10.1109/vetecf.2007.374

A Novel Subcarrier Allocation Algorithm for Multiuser OFDM System With Fairness: User's Perspective

2007· article· en· W2032906529 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

VenueIEEE Vehicular Technology Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSubcarrierComputer scienceTelecommunications linkOrthogonal frequency-division multiplexingBase stationBit error rateMax-min fairnessResource allocationChannel (broadcasting)Transmitter power outputTransmission (telecommunications)Multiuser detectionAlgorithmFairness measureComputer networkMathematical optimizationReal-time computingWirelessTransmitterTelecommunicationsCode division multiple accessMathematicsThroughput

Abstract

fetched live from OpenAlex

In wireless multiuser OFDM systems, dynamic resource allocation has been shown to improve the performance by exploiting the multiuser diversity. In this paper we propose a subcarrier allocation algorithm to increase the total data rate for the downlink of a variable bit rate multiuser OFDM system with proportional rate constraints subject to bit error rate and total transmit power. We assume that the channel is quasi-static where the channel status does not vary within each transmission block and the base station has perfect knowledge of subchannel gains. The proposed algorithm is based on prioritizing the critical (most sensitive) user in the system and the variance of the subchannel gains for each user is used to define the sensitivity of the user to the subcarrier allocation. Simulation results show that this algorithm achieves higher capacity with acceptable proportional fairness compared to the previous suboptimal solutions proposed by Rhee et al. in [9] and Shen et al. in [12].

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 categoriesMeta-epidemiology (narrow)
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 score0.774
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.221
Teacher spread0.213 · 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