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Record W2117144501 · doi:10.1049/iet-com.2008.0340

Multiuser scheduling in high speed downlink packet access

2009· article· en· W2117144501 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

VenueIET Communications · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceTelecommunications linkScheduling (production processes)Network packetChannel state informationComputer networkDistributed computingReal-time computingWirelessMathematical optimizationTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

Multiuser scheduling is an important aspect in the performance optimisation of a wireless network as it allows multiple users to efficiently access a shared channel by exploiting multiuser diversity. For example, the 3GPP cellular standard supports multiuser scheduling in the high speed downlink packet access (HSDPA) feature. To perform efficient scheduling, channel state information (CSI) for users is required, and is obtained via their respective feedback channels. Multiuser scheduling is studied assuming the availability of perfect CSI, which would require a high bandwidth overhead. A more realistic imperfect CSI feedback in the form of a finite set of channel quality indicator values is assumed, as specified in the HSDPA standard. A global optimal approach and a simulated annealing (CSA) approach are used to solve the optimisation problem. Simulation results suggest that the performances of the two approaches are very close even though the complexity of the simulated annealing (SA) approach is much lower. The performance of a simple greedy approach is found to be significantly worse.

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: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.572

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 science0.0010.000
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 head0.028
GPT teacher head0.298
Teacher spread0.271 · 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