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Record W1984516181 · doi:10.1109/jsac.2005.858887

A novel dynamic cell configuration scheme in next-generation situation-aware CDMA networks

2005· article· en· W1984516181 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 Journal on Selected Areas in Communications · 2005
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceCode division multiple accessHandoverComputer networkCellular networkPower controlScheme (mathematics)Radio resource managementSoft handoverReinforcement learningResource management (computing)Resource allocationCall Admission ControlDistributed computingPower (physics)Wireless networkWirelessTelecommunications

Abstract

fetched live from OpenAlex

To balance the time-varying traffic load between cells, caused by user mobility and diverse applications, it is crucial for next-generation code-division multiple-access (CDMA) cellular networks to configure cell coverage and capacity dynamically. In this paper, we show that pilot power allocation is highly coupled to other facets of radio resource management. We propose a novel dynamic cell configuration scheme for multimedia CDMA cellular networks, based on reinforcement-learning, which takes into account pilot, soft handoff, and maximum link power allocations, as well as call admission control mechanisms. Simulation results demonstrate the effectiveness of the proposed scheme in situation-aware CDMA 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)0.001
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: none
Teacher disagreement score0.846
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0040.000
Research integrity0.0000.002
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 head0.073
GPT teacher head0.323
Teacher spread0.250 · 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