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Record W1977329051 · doi:10.1080/17445760.2012.660485

Transmission rate enhancement via adaptive relaying in wireless networks

2012· article· en· W1977329051 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

VenueInternational Journal of Parallel Emergent and Distributed Systems · 2012
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsFadingTransmission (telecommunications)Computer scienceWirelessComputer networkChannel (broadcasting)Constraint (computer-aided design)Link adaptationTransmission rateWireless networkEnergy (signal processing)Electronic engineeringTelecommunicationsEngineeringMathematicsStatistics

Abstract

fetched live from OpenAlex

Recently, the cooperative communication has been employed as an effective technique to combat the effects of channel fading and to conserve the energy in wireless networks. The impact of cooperative communication on transmission rate, however, has not been well addressed yet. In this paper, we address the transmission rate enhancement issue via adaptive relaying in wireless networks. For a given transmitting power level and a desired probability of success, we investigate how much average transmission rate can be increased by adaptive relaying. Moreover, we study the impact of maximal ratio combiner and energy constraint on adaptive relaying. The extensive evaluation results reveal that the average transmission rate can be substantially improved through such adaptive cooperation.

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 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 score0.966
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.288
Teacher spread0.253 · 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