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Record W2111910543 · doi:10.1109/ccece.1999.807171

Robust frame rate detection for variable rate transmission in CDMA

2003· article· en· W2111910543 on OpenAlexaff
Guu-Chang Yang, Slim Kallel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceFrame (networking)Code division multiple accessBit error rateAdditive white Gaussian noiseOverhead (engineering)Channel (broadcasting)Transmission (telecommunications)Real-time computingVariable (mathematics)Electronic engineeringComputer networkAlgorithmTelecommunicationsEngineeringMathematics

Abstract

fetched live from OpenAlex

The transmitted data rate in the forward traffic channel in the existing IS-95 CDMA system is variable from frame to frame. The purpose of this variable data rate transmission is to maximize the use of the multiple access channel. In order to reduce the overhead in a frame, however, the data rate information is not provided to mobile station receivers. This paper presents a robust frame rate detection scheme for variable data rate transmission systems like the IS-95 CDMA system. Simulation results show that the proposed rate detection scheme can provide a gain of up to 1.8 dB over the conventional method in terms of the required bit energy to noise ratio E/sub b//N/sub o/ at a detection error rate of 10/sup -4/ in the AWGN environment.

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)0.002
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.047
GPT teacher head0.277
Teacher spread0.230 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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