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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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.712
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.047
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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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