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Record W2056720576 · doi:10.1049/iet-com.2013.0596

Performance analysis of two‐way opportunistic decode‐and‐forward based systems in Nakagami‐ <i>m</i> fading environments

2014· article· en· W2056720576 on OpenAlexafffund
Kaïs Ben Fredj, Salama Ikki, Sonia Aı̈ssa

Bibliographic record

VenueIET Communications · 2014
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsLakehead UniversityInstitut National de la Recherche ScientifiqueUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFadingNakagami distributionComputer scienceTelecommunicationsDecoding methods

Abstract

fetched live from OpenAlex

This paper studies the performance of a two‐way relay‐based communication system with opportunistic relay selection in Nakagami‐ m fading environments. The authors consider a two‐way wireless communication system where two nodes, acting as sources and using different modulation schemes for transmission, are unable to exchange data because of deep fading on their direct link and proceed via L relay terminals. They provide closed‐form expression for the probability density function of the link between the ‘selected’ best relay and each source, and use this result to derive a closed‐form expression for the average symbol error probability which, to the best knowledge of the authors, has never been done before. This result is further approximated for the high signal‐to‐noise ratio regions and used to develop closed‐form expressions for the optimised power allocated to each node involved in the communication process. The authors asset their formulae with numerical results and interpretations to complete this work.

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)0.001
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 score0.832
Threshold uncertainty score0.550

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.049
GPT teacher head0.289
Teacher spread0.239 · 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.

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

Citations6
Published2014
Admission routes2
Has abstractyes

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