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Record W2292953472 · doi:10.23919/oceans.2015.7404597

Joint packet detection and decoding for maritime data exchange systems

2015· article· en· W2292953472 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
FieldEngineering
TopicIoT Networks and Protocols
Canadian institutionsDalhousie University
Fundersnot available
KeywordsDecoding methodsNetwork packetComputer scienceRandom accessTelecommunications linkComputer networkJoint (building)Transmission (telecommunications)Real-time computingCommunications satelliteSatelliteTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

A random access technique based on spatially coupling information transmission modulation is proposed. We consider an application of the method to the maritime VHF data exchange system (VDES) in which a large pool of vessels attempt uplink ship-to-satellite communication in an uncoordinated fashion using short data packets. The proposed receiver performs joint packet detection and data decoding of the stream of interfering (coupled) incoming packets. An efficient receiver architecture is designed using a low-complexity approximate message passing (AMP) algorithm. It is demonstrated that the proposed random access technique can successfully accommodate traffic loads that are considerably higher than loads achievable with competing random access mechanisms.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.227

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.139
GPT teacher head0.282
Teacher spread0.143 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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