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Record W1861283520 · doi:10.1109/icc.1996.542268

Stability of slotted ALOHA access with capture provided by an adaptive array

2002· article· en· W1861283520 on OpenAlexaff
Gary Leung, S.E. Tavares, P.J. McLane

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIoT Networks and Protocols
Canadian institutionsQueen's University
Fundersnot available
KeywordsAlohaRetransmissionTelecommunications linkComputer scienceNetwork packetThroughputComputer networkRandom accessCommunications satelliteRobustness (evolution)Capture effectReal-time computingSatelliteTelecommunicationsEngineeringWireless

Abstract

fetched live from OpenAlex

We study slotted ALOHA multiple access when a satellite contains an on-board antenna array to attenuate interference. This leads to a capture phenomenon in slotted ALOHA that is provided by the adaptive array. As expected, and as earlier reported in the literature, the adaptive array can improve system throughput. We find that it also improves system robustness. That is, the probabilities of new packet generation and retransmission can vary over a wider range than for slotted ALOHA and still maintain nearly maximum throughput. The same is true for the average packet delay and average system backlog. As in the earlier literature the adaptive beamforming capability on-board the satellite is taken to be ideal. For a system with two uplink and two downlink beams the throughput increase relative to slotted ALOHA is 128% for a wide range of system parameters.

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)0.006
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.235
Teacher spread0.209 · 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
Published2002
Admission routes1
Has abstractyes

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