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Record W2101446075 · doi:10.1109/ccece.2007.164

Distributed Admission Control for Power-Constrained Cellular Wireless Systems

2007· article· en· W2101446075 on OpenAlexaff
Gaurav Bansal, Anoop Chaturvedi, Vijay K. Bhargava

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTelecommunications linkConstraint (computer-aided design)Power controlComputer scienceCall Admission ControlPower (physics)WirelessMathematical optimizationPareto principleComputer networkDistributed computingWireless networkTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

In the literature distributed call admission control (CAC) schemes exist in which, an infeasible call is rejected early and incurs only a small disturbance to existing calls, while a feasible call is admitted and the system converges to the Pareto optimal power assignment. However, these schemes exist only for unconstrained systems (systems that have no constraint on maximum transmitted power level). In practical systems, a power constraint exists in both uplink and downlink. In this paper we propose a method by which an incoming call whose inclusion in the system can force one of the existing calls to violate the maximum power constraint, is rejected. This method can be used at call admission stage in practical systems which are power constrained. Simulation results have been provided.

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.

How this classification was reachedexpand

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)0.002
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 score0.984
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0020.000
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 head0.019
GPT teacher head0.283
Teacher spread0.263 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2007
Admission routes1
Has abstractyes

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