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Record W2105433213 · doi:10.1109/rws.2009.4957430

Proportional fairness packet scheduling with transmit beamforming for multi-user MIMO systems

2009· article· en· W2105433213 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 institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsComputer scienceBeamformingTelecommunications linkScheduling (production processes)Fairness measureNetwork schedulerNetwork packetMIMOComputer networkTransmission delayProportionally fairReal-time computingRound-robin schedulingProcessing delayThroughputFair-share schedulingWirelessTelecommunicationsEngineeringQuality of service

Abstract

fetched live from OpenAlex

In this paper, the well known proportional fairness scheduling is investigated when we joint transmit beamforming and packet level scheduling taking into consideration the traffic arrival process with different packet lengths for the downlink of multiple-input multiple-output (MIMO) multi-user systems. The new scheduler called the proportional fairness zero-forcing beamforming (PF-ZB) can perform at the packet level and provide low average packet transmission delay as well as fairness to users. The scheduler is work conserving. We compare the performance of our scheduler with another well known MIMO scheduler when it is performing in the packet level with transmit beamforming. Simulations that consider the traffic characteristics show the low average packet transmission delay and demonstrate the fairness capabilities of PF-ZB.

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 score0.558
Threshold uncertainty score0.589

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 head0.234
Teacher spread0.219 · 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
Published2009
Admission routes1
Has abstractyes

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