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Record W2741251792 · doi:10.1109/icc.2017.7996444

Distance based duplex mode selection in large scale peer-to-peer wireless networks

2017· article· en· W2741251792 on OpenAlex
Kasun T. Hemachandra, Abraham O. Fapojuwo

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFull-Duplex Wireless Communications
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDuplex (building)Computer scienceThroughputWireless networkWirelessComputer networkTelecommunications

Abstract

fetched live from OpenAlex

A throughput analysis is conducted for a large scale peer-to-peer wireless network whose devices are capable of operating in both full- and half-duplex modes, using the tools of stochastic geometry. Each device selects its operating duplex mode based on the distance to its partner node. In both duplex modes, the energy consumption and the hardware configurations of the nodes are made equivalent for fair comparisons between full-duplex and half-duplex operations. Using the results of the analysis, an approach is proposed to determine a distance threshold value for duplex mode selection, and the proposed distance threshold can be computed offline. It is found that the throughput performance of the hybrid full-/half-duplex network generated with the proposed distance threshold based duplex mode selection technique outperforms both the pure half-duplex and pure full-duplex network settings for most practically common network parameter values.

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 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 score0.354
Threshold uncertainty score0.996

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 head0.262
Teacher spread0.250 · 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

Quick stats

Citations6
Published2017
Admission routes1
Has abstractyes

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