MétaCan
Menu
Back to cohort
Record W2108248716 · doi:10.1155/wcn/2006/72493

A Novel Cluster-Based Cooperative MIMO Scheme for Multi-Hop Wireless Sensor Networks

2006· article· en· W2108248716 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

VenueEURASIP Journal on Wireless Communications and Networking · 2006
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of British Columbia
FundersKorea Science and Engineering Foundation
KeywordsCooperative MIMOComputer scienceMIMOHop (telecommunications)Computer networkEnergy consumptionWireless sensor networkFadingEfficient energy useWireless3G MIMODistributed computingChannel (broadcasting)Telecommunications

Abstract

fetched live from OpenAlex

A cluster-based cooperative multiple-input-multiple-output (MIMO) scheme is proposed to reduce the adverse impacts caused by radio irregularity and fading in multi-hop wireless sensor networks. This scheme extends the LEACH protocol to enable the multi-hop transmissions among clusters by incorporating a cooperative MIMO scheme into hop-by-hop transmissions. Through the adaptive selection of cooperative nodes and the coordination between multi-hop routing and cooperative MIMO transmissions, the scheme can gain effective performance improvement in terms of energy efficiency and reliability. Based on the energy consumption model developed in this paper, the optimal parameters to minimize the overall energy consumption are found, such as the number of clusters and the number of cooperative nodes. Simulation results exhibit that the proposed scheme can effectively save energy and prolong the network lifetime.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.079
GPT teacher head0.315
Teacher spread0.236 · 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