MétaCan
Menu
Back to cohort
Record W1879264936 · doi:10.1109/icupc.1998.733695

Efficient ARQ error control strategies with adaptive packet length for mobile radio networks

2002· article· en· W1879264936 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer scienceSelective Repeat ARQAutomatic repeat requestHybrid automatic repeat requestComputer networkNetwork packetMobile radioError detection and correctionGo-Back-N ARQPacket radioAlgorithmTelecommunications link

Abstract

fetched live from OpenAlex

The throughput of conventional ARQ protocols, such as the stop-and-wait, go-back-N and selective-repeat, can be improved by dynamically adapting the protocol packet length with the changes in channel conditions. Such an action requires a method for sensing the channel state and detecting a change in it. This paper examines four simple algorithms to implement such an adaptive system in a slowly varying mobile radio channel. It is shown that these algorithms performs remarkably well in spite of their simplicity. In particular, the algorithm based on counting the contiguous positive and/or negative acknowledgment messages provides a reliable channel state information (CSI) within only a few block transmissions, and requires the shortest observation interval among the four schemes.

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.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.958
Threshold uncertainty score0.621

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0020.000
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 head0.034
GPT teacher head0.268
Teacher spread0.235 · 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

Quick stats

Citations19
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicWireless Communication Networks ResearchFrench-language works237,207