MétaCan
Menu
Back to cohort
Record W1880215430 · doi:10.1109/vetec.1988.195391

Analysis of system frame synchronization on a FH-BFSK system performance for mobile radio applications

2003· article· en· W1880215430 on OpenAlexaff
Guiling Wu, M. Lecours, K. Defly, G.Y. Delisle

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsRician fadingBit error rateAdditive white Gaussian noiseComputer scienceFrequency-shift keyingSynchronization (alternating current)Frame (networking)Spread spectrumFrequency agilityCommunications systemFadingInterference (communication)Electronic engineeringWhite noiseTelecommunicationsCode division multiple accessDecoding methodsEngineeringDemodulationChannel (broadcasting)

Abstract

fetched live from OpenAlex

The effect of system frame synchronization in a frequency-hopped (FH) spread-spectrum digital mobile radio communication system is evaluated. A novel mathematical approach is used for modeling the FH-BFSK mobile radio system in the presence of Rician fading, multiuser interference and Gaussian white noise. Besides the synchronization error between users, the influence of propagation conditions in different types of region, and the effect of coding are considered. The results show that the multiuser interference is a serious problem which limits the system's capacity. Performance degradation increases quickly with the frame synchronization error. A good frame is maintained to minimize the bit error rate (BER). System performance can be improved by increasing the signal-to-noise ratio, only where there is a good system frame synchronization.>

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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.272
Teacher spread0.256 · 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

Explore more

Same topicWireless Communication Networks ResearchFrench-language works237,207