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Record W2114205786 · doi:10.1109/t-wc.2008.070586

Achievable Rates and Fairness in Rateless Coded Relaying Schemes

2008· article· en· W2114205786 on OpenAlexaff
Reza Nikjah, Norman C. Beaulieu

Bibliographic record

VenueIEEE Transactions on Wireless Communications · 2008
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer scienceConstraint (computer-aided design)Computer networkProtocol (science)ThroughputWirelessPower (physics)Decoding methodsAlgorithmTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

The average throughput of three decode-and-forward (DF) half-duplex (DFHD) and two DF full-duplex (DFFD) rateless coded relaying schemes are studied under a peak power constraint (PPC) and an average power constraint (APC). Two of the DFHD and one of the DFFD protocols are known. One new, much simpler, DFHD protocol, and one new DFFD protocol are proposed. The fairness in comparing the protocols in terms of energy cost is formulated, and the protocols are compared to each other in a power-fair regime. The two previously proposed DFHD protocols, one of which is superior to the other under the PPC, are found to have almost the same performances when compared power-fairly. The proposed protocols are built upon opportunistic communication and power optimization such that, although inferior to their predecessors in a PPC regime, they can slightly surpass them under the APC.

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 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 categoriesScience and technology studies
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 score0.915
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.062
GPT teacher head0.298
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

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

Citations19
Published2008
Admission routes1
Has abstractyes

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