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Record W1507329928 · doi:10.1109/vetecs.2006.1682841

Two-Level Fractional Guard Channels for Priority Access in Cellular Systems

2006· article· en· W1507329928 on OpenAlex
Dinh Van Tung, Chong Wong, J.W. Mark, Kee Chaing Chua

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
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsGuard (computer science)HandoverComputer networkBlocking (statistics)Computer scienceCall blockingChannel (broadcasting)

Abstract

fetched live from OpenAlex

A two-level fractional guard channels (TLFGC) scheme to efficiently provide priority access for handoff calls over new calls in cellular systems is proposed. The switching between the levels is controlled by a dropped call. The first level has a small number of guard channels like the fixed guard channel (FGC) scheme, while the second level has a larger number of guard channels and a smaller number of fractional guard channels. An analytical formulation of the steady state probabilities, new call blocking probability, handoff call blocking probability, system utilization, probabilities in each level and the equivalent number of guard channels is presented. Numerical results show that the performance of TLFGC is almost the same as a fixed guard channels (FGC) scheme under light load. However, the advantage of the TLFGC scheme is demonstrated under heavy load where the handoff call blocking probability is much better than that of a FGC scheme, giving more priority and protection to handoff calls over new calls.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.964
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
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 head0.086
GPT teacher head0.352
Teacher spread0.265 · 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

Citations7
Published2006
Admission routes1
Has abstractyes

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