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Record W2979583438 · doi:10.1049/iet-com.2018.5411

Wireless information and power transfer with optimal transmit antenna selection

2019· article· en· W2979583438 on OpenAlexaff
Maymoona Hayajneh, T. Aaron Gulliver

Bibliographic record

VenueIET Communications · 2019
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsRelayComputer scienceTransmitter power outputMaximum power transfer theoremWirelessAntenna (radio)SplitterEnergy harvestingEnergy (signal processing)TelecommunicationsComputer networkPower (physics)Electronic engineeringMathematicsTransmitterPhysicsEngineeringChannel (broadcasting)Statistics

Abstract

fetched live from OpenAlex

A dual hop, half‐duplex amplify and forward (AF) relay is considered for a source equipped with multiple transmit antennas. A power splitter is employed at the relay to harvest energy from the signal received from the source. The outage probability (OP) is derived considering optimal antenna selection to maximise the end‐to‐end signal‐to‐noise ratio. It is shown that the performance of the proposed energy harvesting based scheme improves with the number of transmit antennas. The effect of the power splitting factor on the OP is studied for different relay locations. Further, the OP is examined for different distances between the source and relay.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.454

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 communication0.0000.001
Open science0.0000.000
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 head0.005
GPT teacher head0.187
Teacher spread0.181 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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