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Record W1978464445 · doi:10.1002/dac.780

QoS‐aware call admission control in wideband CDMA wireless networks

2006· article· en· W1978464445 on OpenAlexaff
Hossam S. Hassanein, Alex Oliver, Nidal Nasser, Ehab S. Elmallah

Bibliographic record

VenueInternational Journal of Communication Systems · 2006
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of AlbertaUniversity of GuelphQueen's University
Fundersnot available
KeywordsUMTS frequency bandsComputer scienceQuality of serviceComputer networkCall Admission ControlThroughputTelecommunications linkPower controlRadio resource managementAir interfaceWidebandWirelessCellular networkAdmission controlWireless networkCode division multiple accessPower (physics)TelecommunicationsBase stationEngineeringElectronic engineering

Abstract

fetched live from OpenAlex

Abstract Efficient call admission control (CAC) technique plays a major role in ensuring the quality of service (QoS) requirements of different traffic classes and achieving flexible radio resource utilization in wideband CDMA system like universal mobile telecommunication system (UMTS). In this paper, we propose a novel QoS‐aware CAC framework for radio access in wideband wireless UMTS networks. It features an efficient CAC algorithm coupled with a QoS class‐separation mechanism based on the transmitted power of each individual mobile terminal. Three inter‐relating components have been introduced to extend a currently existing UMTS uplink admission control scheme. First, we introduce a measurement‐based component to calculate the current load of the system; second, this measurement‐based component is integrated with a power prediction module to estimate the load increment that the new call will bring into the system; and third, the proposed framework feeds the results obtained to a CAC algorithm with a QoS‐enforcing mechanism that gives each class of traffic different treatment based on the QoS requirement of the connections. To the best of our knowledge, ours is a first attempt towards combining the above components into one uplink CAC framework that aims to enhance system performance and to achieve per‐class QoS objectives. Simulation results show the major impact on the performance of UMTS which is reflected in increased throughput and lower blocking and dropping. Copyright © 2006 John Wiley & Sons, Ltd.

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 categoriesOpen science
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 score0.975
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0060.001
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 head0.015
GPT teacher head0.290
Teacher spread0.275 · 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.

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

Citations0
Published2006
Admission routes1
Has abstractyes

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