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Record W2101554857 · doi:10.1109/cnsr.2007.20

Capacity of Cellular CDMA Systems with Integrated Voice and Data Services

2007· article· en· W2101554857 on OpenAlexafffund
Zixin Liu, Jalal Almhana, R. McGorman, C. Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsNortel (Canada)Université de Moncton
FundersAtlantic Canada Opportunities AgencyNortel Networks Inc
KeywordsComputer scienceInterference (communication)Log-normal distributionBlocking (statistics)Data as a servicePoisson distributionCode division multiple accessComputer networkTelecommunicationsAlgorithmStatisticsMathematics

Abstract

fetched live from OpenAlex

In this paper we analyze the capacity of a CDMA system supporting integrated voice and data services. The bit energy-to-interference ratios for voice and data services are each modeled using lognormal distributions, and an integrated capacity formula based on a lognormal approximation is proposed. The capacity formula defines an admission scheme to guarantee with a predefined probability the total interference is less than the maximum acceptable interference. Under the assumption of Poisson arrivals for voice and data services, Kaufman's method is applied to calculate the blocking probabilities for voice and data services. Numerical results are provided to illustrate the proposed procedure.

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 score0.981
Threshold uncertainty score0.506

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 integrity0.0000.000
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 head0.053
GPT teacher head0.290
Teacher spread0.236 · 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

Citations0
Published2007
Admission routes2
Has abstractyes

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