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Record W2117317879 · doi:10.1109/wcnc.2011.5779296

Performance analysis of IEEE 802.15.6 under saturation condition and error-prone channel

2011· article· en· W2117317879 on OpenAlex

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
TopicWireless Body Area Networks
Canadian institutionsToronto Metropolitan UniversityUniversity of Manitoba
Fundersnot available
KeywordsComputer scienceIEEE 802.11WirelessProbabilistic logicBody area networkChannel (broadcasting)IEEE 802.15IEEE 802.11b-1999Saturation (graph theory)Computer networkWireless networkTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

Due to lack of an appropriate wireless technology which satisfies all the requirements of Wireless Body Area Networks (WBANs) the IEEE 802.15.6 Task Group introduced the IEEE 802.15.6 communication standard optimized for low power devices and operation on, in or around the human body. In this work we develop an analytical model for performance evaluation of an IEEE 802.15.6-based WBAN under saturation condition and error prone channel. We model the backoff procedure as specified in the standard employing a probabilistic approach. We validate results of the analytical model with a simulation model. Our results indicate that under saturation condition the medium is mostly utilized by the nodes with highest priority while other user priorities are starving.

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 score0.221
Threshold uncertainty score0.328

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 science0.0000.000
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 head0.023
GPT teacher head0.212
Teacher spread0.189 · 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

Citations75
Published2011
Admission routes1
Has abstractyes

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