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Record W2168982656 · doi:10.1109/wcnc.2011.5779163

QoS-aware bit scheduling in multi-user OFDM systems

2011· article· en· W2168982656 on OpenAlex
Chi En Huang, Cyril Leung

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 British Columbia
Fundersnot available
KeywordsComputer scienceComputer networkQuality of serviceMulti-userScheduling (production processes)JitterOrthogonal frequency-division multiplexingNetwork packetReal-time computingChannel (broadcasting)

Abstract

fetched live from OpenAlex

Radio resource management (RRM) is widely regarded as a critical component in improving spectral efficiency of beyond third generation (3G) cellular air interfaces. Much of the published work in Orthogonal Frequency Division Multiplexing (OFDM) RRM focuses on exploiting multi-user, multi-channel and multi-application diversity. In this paper, we propose a Quality of Service (QoS)-aware bit scheduling framework to increase the flexibility and granularity of the resource allocation algorithms by adaptively matching the QoS requirements of the application bits of users to the characteristics of the OFDM subcarriers in a mixed-traffic environment. We show that with the finesse control of QoS-aware bit scheduling, it is possible to simultaneously achieve both an increase in user throughput and a reduction in user packet drop probability by accepting a within packet drop threshold increase in user latency. The performance gains obtainable are quantified in terms of user throughput, user latency, user jitter and user packet drop probability.

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 score0.885
Threshold uncertainty score0.481

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 head0.034
GPT teacher head0.223
Teacher spread0.190 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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