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Record W2153578293 · doi:10.1109/glocom.2006.821

WLC35-5: User-Aided Adaptive TDMA for Real-Time Services in an OFDM Based Cellular System

2006· article· en· W2153578293 on OpenAlex
Changqin Huo, A.B. Sesay, Abraham O. Fapojuwo

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

VenueGlobecom · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTime division multiple accessComputer scienceOrthogonal frequency-division multiplexingComputer networkChannel (broadcasting)Channel allocation schemesSpectral efficiencyCellular networkResource allocationReal-time computingScheme (mathematics)Link adaptationDistributed computingFadingWirelessTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

In this paper, a user-aided adaptive TDMA (UAAT) algorithm is developed for real-time services to improve the system efficiency of OFDM based cellular networks. In the UAAT scheme, a subchannel is shared by multiple users adaptively in a TDMA manner based on their instantaneous channel conditions. The system efficiency is improved dramatically by applying adaptive modulation schemes to all real-time users and using each subchannel more efficiently. The performance of the proposed algorithm is evaluated and compared with that of other resource allocation schemes. Results show that the proposed algorithm provides up to 100% improvement in the system efficiency or, equivalently, the user capacity of OFDM based cellular networks.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
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
Bibliometrics0.0000.000
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 head0.005
GPT teacher head0.189
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