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Record W2094399801 · doi:10.1109/bsc.2008.4563203

Cross-layer call admission control in packet CDMA wireless networks employing ARQ

2008· article· en· W2094399801 on OpenAlexaff
Wei Sheng, Steven D. Blostein

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer networkAutomatic repeat requestComputer scienceRetransmissionQuality of serviceCall Admission ControlNetwork packetSelective Repeat ARQHybrid automatic repeat requestCode division multiple accessCall controlThroughputPhysical layerGo-Back-N ARQWireless networkWirelessTelecommunications linkTelecommunications

Abstract

fetched live from OpenAlex

An optimal call/connection admission control (CAC) policy is proposed for a packet-switched code division multiple access (CDMA) beamforming system, which employs a truncated automatic retransmission request (ARQ) scheme to mitigate the packet transmission error. Compared with the previous research in which call level QoS is ignored, the proposed CAC policy is capable of guaranteeing quality-of-service (QoS) requirements in physical, call and packet levels, while simultaneously maximizing the system throughput. Numerical examples illustrate that the proposed CAC policy offers a more flexible tradeoff among physical-layer, packet-level and call level performances, and as a result, the multiple QoS constraints can be handled.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.757
Threshold uncertainty score0.795

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 communication0.0000.001
Open science0.0030.001
Research integrity0.0000.001
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 head0.047
GPT teacher head0.323
Teacher spread0.276 · 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
GenreEmpirical

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
Published2008
Admission routes1
Has abstractyes

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