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Record W2156367905 · doi:10.1109/milcom.1991.258373

A new rapid acquisition scheme for burst mode DS spread spectrum packet radio

2002· article· en· W2156367905 on OpenAlexaff
Peter F. Driessen, Zhen-Liang Shi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPreambleNetwork packetSynchronization (alternating current)Computer scienceBurst mode (computing)Frame (networking)Spread spectrumPacket radioCode (set theory)Real-time computingScheme (mathematics)Pseudorandom noiseAlgorithmComputer networkChannel (broadcasting)Mathematics

Abstract

fetched live from OpenAlex

A rapid acquisition scheme for direct-sequence (DS) spread-spectrum packet radio systems using PN matched filters is described. The system operates in burst mode, with limited permitted time for synchronization using a fixed length preamble at the beginning of each data burst. Multiple PN codes are available for acquisition at the first portion of the preamble. The second portion of the preamble consists of several PN codes which are modulated with a marker. The receiver may achieve code acquisition anywhere within the first portion of the preamble. Since it is not known a priori in which of the several code periods acquisition will occur, coincidence detection is done using the marker for frame synchronization. The analysis shows that the scheme yields better performance than some other previous schemes in packet radio systems.>

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)0.001
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.044
GPT teacher head0.293
Teacher spread0.250 · 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

Citations9
Published2002
Admission routes1
Has abstractyes

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