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Opportunistic Energy Efficient Cooperative Communication

2012· article· en· W1995434282 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

VenueIEEE Wireless Communications Letters · 2012
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRelayComputer scienceEfficient energy useMetric (unit)Transmission (telecommunications)Signal-to-noise ratio (imaging)Energy (signal processing)Computer networkWirelessSelection (genetic algorithm)Performance metricScheme (mathematics)TelecommunicationsEngineeringMathematicsElectrical engineeringPower (physics)

Abstract

fetched live from OpenAlex

Inspired by the green communication trend of next-generation wireless networks, we present an opportunistic energy-efficient cooperative communication method. Different from classical relaying selection schemes, which adopt either end-to-end signal-to-noise ratio or capacity as selection metrics, our opportunistic relaying scheme uses an energy efficiency metric for selecting the best relay or resorting to direct transmission. Simulation results demonstrate the significant energy savings achieved by our scheme when compared with opportunistic decode-and-forward based on capacity. In addition to that, dynamic time allocation and increasing the number of participating relays are shown to have a notable effect on energy efficiency.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0060.002
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 head0.053
GPT teacher head0.284
Teacher spread0.231 · 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