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Cognitive Radio for Smart Grid Communications

2010· article· en· W2015672965 on OpenAlexaff
A. Ghassemi, Sara Bavarian, Lutz Lampe

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCognitive Radio Networks and Spectrum Sensing
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBackupComputer scienceComputer networkCognitive radioTelecommunicationsIEEE 802WirelessDatabase

Abstract

fetched live from OpenAlex

One of the key foundations of smart grid (SG) is a reliable communications infrastructure which is a sophisticated, multi-layer network carrying different classes of data. SG communications needs to be designed to accommodate the current energy management requirements as well as the potential demand of future applications. In this paper, we propose the application of cognitive radio (CR) based on the IEEE 802.22 standard in the SG wide area networks (WANs). We discuss the benefits of the proposed scheme including opportunistic access of TV bands, extended coverage, ease of upgradability, self-healing and fault-tolerant design. The proposed scheme can work as a secondary radio particularly in urban areas and as a backup in disaster management. In rural areas, however, a stand-alone radio based on IEEE 802.22 can effectively provide broadband access because of the wide area coverage due to the good propagation characteristics of TV bands.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.281
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), 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

Citations141
Published2010
Admission routes1
Has abstractyes

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