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Record W2766193075 · doi:10.1002/itl2.13

Outage probability for a decode‐and‐forward SWIPT relaying system in Nakagami fading

2017· article· en· W2766193075 on OpenAlex
Farhan Nawaz, Syed Ali Hassan, Sonia Aı̈ssa, Sajid Saleem

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

VenueInternet Technology Letters · 2017
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité du Québec à Montréal
Fundersnot available
KeywordsNakagami distributionFadingRelayMaximum power transfer theoremComputer scienceRayleigh fadingWirelessElectronic engineeringEnergy harvestingEnergy (signal processing)TelecommunicationsPower (physics)Decoding methodsEngineeringStatisticsMathematicsPhysics

Abstract

fetched live from OpenAlex

The outage probability of a decode‐and‐forward (DF) relaying system based on simultaneous wireless information and power transfer (SWIPT) in the presence of Nakagami fading is investigated. The relaying model considers both the source‐destination direct link in addition to the source‐relay‐destination link. The power splitter at the relaying device provides energy to the relay by splitting the received signal power into energy harvesting and information transfer parts. The derived outage expression is verified using simulation results. The results show an impressive amount of percentage decrease in outage probability for Nakagami fading with different values of shape parameter in comparison to Rayleigh fading.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.765
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.012
GPT teacher head0.220
Teacher spread0.209 · 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