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Record W2142966661 · doi:10.1109/jsac.2005.858874

Capacity of future WCDMA networks supporting multimedia services

2005· article· en· W2142966661 on OpenAlexaff
Tallal Elshabrawy, Tho Le‐Ngoc

Bibliographic record

VenueIEEE Journal on Selected Areas in Communications · 2005
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceComputer networkQuality of serviceTelecommunications linkDimensioningSession (web analytics)Code division multiple accessData as a serviceChannel (broadcasting)MultimediaService (business)World Wide Web

Abstract

fetched live from OpenAlex

This paper presents an analytical model suitable to evaluate wideband code-division multiple-access (WCDMA) system capacity in terms of supported multimedia services achieving the required percentage of satisfied users. The satisfied-user criteria proposed by the Universal Mobile Telecommunications System introduce session-level performance measures, providing a more comprehensive notion of users' quality-of-service (QoS), but requiring knowledge of both outage probability and outage correlation behavior. By using a two-state (good-bad) Gilbert channel to represent the outage behavior, the model parameters and satisfied-user probability for both speech and data sessions are derived for different uplink and downlink scenarios. The proposed analytical model can be used for WCDMA system dimensioning to assess the throughput and session interruption probabilities of data services and their impact on the satisfied-user probability of speech services.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.033
GPT teacher head0.318
Teacher spread0.285 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2005
Admission routes1
Has abstractyes

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