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Record W2155527417

SIMULATION FOR SPECTRUM SENSING OF MULTIPLE COGNITIVE RADIO SYSTEMS AND RADIO COMPATIBILITY

2013· article· en· W2155527417 on OpenAlexaff
Sowndarya Sundar, M. Meenakshi

Bibliographic record

VenueInternational Conference on Electrical and Electronics Engineering · 2013
Typearticle
Languageen
FieldComputer Science
TopicCognitive Radio Networks and Spectrum Sensing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCognitive radioComputer scienceWirelessCompatibility (geochemistry)Spectrum managementRadio frequencyElectronic engineeringFadingElectromagnetic compatibilityComputer networkTelecommunicationsEngineering
DOInot available

Abstract

fetched live from OpenAlex

With the exponential increase in the use of high powered wireless devices, there is a demand to utilize the spectrum efficiently, intelligently and optimally. Cognitive Radio is an attractive concept and solution, capable of addressing this issue. This paper investigates a statistical simulation model for spectrum sensing of cognitive radio and the associated interference probability calculation methodologies. The capability to simulate multiple cognitive radio systems with issues of complex range of spectrum engineering and radio compatibility are explored. The results show that the model was able to simulate mutual positioning of the systems under consideration with spatial and temporal distributions of the signals taken into account. The model has restrictions to simulate CDMA/OFDMA modules as victim. Research on simulation models of dynamic spectrum management has the capability to shape the communication protocols and technologies of future.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.827
Threshold uncertainty score0.655

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 head0.020
GPT teacher head0.245
Teacher spread0.225 · 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
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

Citations1
Published2013
Admission routes1
Has abstractyes

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