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Record W2065320671 · doi:10.1109/glocom.2011.6133612

A Distributed Spectrum Sharing Method for Improving Coexistence of IEEE 802.15.4 Networks

2011· article· en· W2065320671 on OpenAlexaff
Hesham ElSawy, Ekram Hossain, Sergio Camorlinga

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSuperframeIEEE 802.15Computer scienceComputer networkIEEE 802.11b-1999Inter-Access Point ProtocolInterference (communication)IEEE 802.11IEEE 802.11g-2003IEEE 802.11sService setNetwork allocation vectorWirelessWireless networkChannel (broadcasting)Wi-FiWireless sensor networkTelecommunications

Abstract

fetched live from OpenAlex

Defined for low-rate, low-power and short-range applications, IEEE 802.15.4 offers complementary services to IEEE 802.11 and IEEE 802.15.1. However, since IEEE 802.15.4-based wireless personal area networks (WPANs) are very prone to interference, efficient coexistence of IEEE 802.15.4 WPANs in the ISM band is a challenging problem. In this work, we propose a distributed coexistence method for IEEE 802.15.4 operating in the beacon- enabled mode. In this method, each network coordinator learns about the surrounding environment, and schedules its superframe properly to minimize the mutual interference. Using this method, multiple IEEE 802.15.4-based WPANs can colocate in the same logical channel, hence, increasing their coexistence capability in the ISM band. The proposed method considers spatial distribution of the WPANs and a physical interference model. Also, the method does not require any global information about the coexisting WPANs. We evaluate the performance of the proposed method through simulations.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.963
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.052
GPT teacher head0.294
Teacher spread0.241 · 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
GenreMethods

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

Citations7
Published2011
Admission routes1
Has abstractyes

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